Tag Archives: Google

AI (artificial intelligence) for Good Global Summit from May 15 – 17, 2018 in Geneva, Switzerland: details and an interview with Frederic Werner

With all the talk about artificial intelligence (AI), a lot more attention seems to be paid to apocalyptic scenarios: loss of jobs, financial hardship, loss of personal agency and privacy, and more with all of these impacts being described as global. Still, there are some folks who are considering and working on ‘AI for good’.

If you’d asked me, the International Telecommunications Union (ITU) would not have been my first guess (my choice would have been United Nations Educational, Scientific and Cultural Organization [UNESCO]) as an agency likely to host the 2018 AI for Good Global Summit. But, it turns out the ITU is a UN (United Nations agency) and, according to its Wikipedia entry, it’s an intergovernmental public-private partnership, which may explain the nature of the participants in the upcoming summit.

The news

First, there’s a May 4, 2018 ITU media advisory (received via email or you can find the full media advisory here) about the upcoming summit,

Artificial Intelligence (AI) is now widely identified as being able to address the greatest challenges facing humanity – supporting innovation in fields ranging from crisis management and healthcare to smart cities and communications networking.

The second annual ‘AI for Good Global Summit’ will take place 15-17 May [2018] in Geneva, and seeks to leverage AI to accelerate progress towards the United Nations’ Sustainable Development Goals and ultimately benefit humanity.

WHAT: Global event to advance ‘AI for Good’ with the participation of internationally recognized AI experts. The programme will include interactive high-level panels, while ‘AI Breakthrough Teams’ will propose AI strategies able to create impact in the near term, guided by an expert audience of mentors representing government, industry, academia and civil society – through interactive sessions. The summit will connect AI innovators with public and private-sector decision-makers, building collaboration to take promising strategies forward.

A special demo & exhibit track will feature innovative applications of AI designed to: protect women from sexual violence, avoid infant crib deaths, end child abuse, predict oral cancer, and improve mental health treatments for depression – as well as interactive robots including: Alice, a Dutch invention designed to support the aged; iCub, an open-source robot; and Sophia, the humanoid AI robot.

WHEN: 15-17 May 2018, beginning daily at 9 AM

WHERE: ITU Headquarters, 2 Rue de Varembé, Geneva, Switzerland (Please note: entrance to ITU is now limited for all visitors to the Montbrillant building entrance only on rue Varembé).

WHO: Confirmed participants to date include expert representatives from: Association for Computing Machinery, Bill and Melinda Gates Foundation, Cambridge University, Carnegie Mellon, Chan Zuckerberg Initiative, Consumer Trade Association, Facebook, Fraunhofer, Google, Harvard University, IBM Watson, IEEE, Intellectual Ventures, ITU, Microsoft, Massachusetts Institute of Technology (MIT), Partnership on AI, Planet Labs, Shenzhen Open Innovation Lab, University of California at Berkeley, University of Tokyo, XPRIZE Foundation, Yale University – and the participation of “Sophia” the humanoid robot and “iCub” the EU open source robotcub.

The interview

Frederic Werner, Senior Communications Officer at the International Telecommunication Union and** one of the organizers of the AI for Good Global Summit 2018 kindly took the time to speak to me and provide a few more details about the upcoming event.

Werner noted that the 2018 event grew out of a much smaller 2017 ‘workshop’ and first of its kind, about beneficial AI which this year has ballooned in size to 91 countries (about 15 participants are expected from Canada), 32 UN agencies, and substantive representation from the private sector. The 2017 event featured Dr. Yoshua Bengio of the University of Montreal  (Université de Montréal) was a featured speaker.

“This year, we’re focused on action-oriented projects that will help us reach our Sustainable Development Goals (SDGs) by 2030. We’re looking at near-term practical AI applications,” says Werner. “We’re matchmaking problem-owners and solution-owners.”

Academics, industry professionals, government officials, and representatives from UN agencies are gathering  to work on four tracks/themes:

In advance of this meeting, the group launched an AI repository (an action item from the 2017 meeting) on April 25, 2018 inviting people to list their AI projects (from the ITU’s April 25, 2018? AI repository news announcement),

ITU has just launched an AI Repository where anyone working in the field of artificial intelligence (AI) can contribute key information about how to leverage AI to help solve humanity’s greatest challenges.

This is the only global repository that identifies AI-related projects, research initiatives, think-tanks and organizations that aim to accelerate progress on the 17 United Nations’ Sustainable Development Goals (SDGs).

To submit a project, just press ‘Submit’ on the AI Repository site and fill in the online questionnaire, providing all relevant details of your project. You will also be asked to map your project to the relevant World Summit on the Information Society (WSIS) action lines and the SDGs. Approved projects will be officially registered in the repository database.

Benefits of participation on the AI Repository include:

WSIS Prizes recognize individuals, governments, civil society, local, regional and international agencies, research institutions and private-sector companies for outstanding success in implementing development oriented strategies that leverage the power of AI and ICTs.

Creating the AI Repository was one of the action items of last year’s AI for Good Global Summit.

We are looking forward to your submissions.

If you have any questions, please send an email to: ai@itu.int

“Your project won’t be visible immediately as we have to vet the submissions to weed out spam-type material and projects that are not in line with our goals,” says Werner. That said, there are already 29 projects in the repository. As you might expect, the UK, China, and US are in the repository but also represented are Egypt, Uganda, Belarus, Serbia, Peru, Italy, and other countries not commonly cited when discussing AI research.

Werner also pointed out in response to my surprise over the ITU’s role with regard to this AI initiative that the ITU is the only UN agency which has 192* member states (countries), 150 universities, and over 700 industry members as well as other member entities, which gives them tremendous breadth of reach. As well, the organization, founded originally in 1865 as the International Telegraph Convention, has extensive experience with global standardization in the information technology and telecommunications industries. (See more in their Wikipedia entry.)

Finally

There is a bit more about the summit on the ITU’s AI for Good Global Summit 2018 webpage,

The 2nd edition of the AI for Good Global Summit will be organized by ITU in Geneva on 15-17 May 2018, in partnership with XPRIZE Foundation, the global leader in incentivized prize competitions, the Association for Computing Machinery (ACM) and sister United Nations agencies including UNESCO, UNICEF, UNCTAD, UNIDO, Global Pulse, UNICRI, UNODA, UNIDIR, UNODC, WFP, IFAD, UNAIDS, WIPO, ILO, UNITAR, UNOPS, OHCHR, UN UniversityWHO, UNEP, ICAO, UNDP, The World Bank, UN DESA, CTBTOUNISDRUNOG, UNOOSAUNFPAUNECE, UNDPA, and UNHCR.

The AI for Good series is the leading United Nations platform for dialogue on AI. The action​​-oriented 2018 summit will identify practical applications of AI and supporting strategies to improve the quality and sustainability of life on our planet. The summit will continue to formulate strategies to ensure trusted, safe and inclusive development of AI technologies and equitable access to their benefits.

While the 2017 summit sparked the first ever inclusive global dialogue on beneficial AI, the action-oriented 2018 summit will focus on impactful AI solutions able to yield long-term benefits and help achieve the Sustainable Development Goals. ‘Breakthrough teams’ will demonstrate the potential of AI to map poverty and aid with natural disasters using satellite imagery, how AI could assist the delivery of citizen-centric services in smart cities, and new opportunities for AI to help achieve Universal Health Coverage, and finally to help achieve transparency and explainability in AI algorithms.

Teams will propose impactful AI strategies able to be enacted in the near term, guided by an expert audience of mentors representing government, industry, academia and civil society. Strategies will be evaluated by the mentors according to their feasibility and scalability, potential to address truly global challenges, degree of supporting advocacy, and applicability to market failures beyond the scope of government and industry. The exercise will connect AI innovators with public and private-sector decision-makers, building collaboration to take promising strategies forward.

“As the UN specialized agency for information and communication technologies, ITU is well placed to guide AI innovation towards the achievement of the UN Sustainable Development ​Goals. We are providing a neutral close quotation markplatform for international dialogue aimed at ​building a ​common understanding of the capabilities of emerging AI technologies.​​” Houlin Zhao, Secretary General ​of ITU​

Should you be close to Geneva, it seems that registration is still open. Just go to the ITU’s AI for Good Global Summit 2018 webpage, scroll the page down to ‘Documentation’ and you will find a link to the invitation and a link to online registration. Participation is free but I expect that you are responsible for your travel and accommodation costs.

For anyone unable to attend in person, the summit will be livestreamed (webcast in real time) and you can watch the sessions by following the link below,

https://www.itu.int/en/ITU-T/AI/2018/Pages/webcast.aspx

For those of us on the West Coast of Canada and other parts distant to Geneva, you will want to take the nine hour difference between Geneva (Switzerland) and here into account when viewing the proceedings. If you can’t manage the time difference, the sessions are being recorded and will be posted at a later date.

*’132 member states’ corrected to ‘192 member states’ on May 11, 2018 at 1500 hours PDT.

*Redundant ‘and’ removed on July 19, 2018.

AI fairytale and April 25, 2018 AI event at Canada Science and Technology Museum*** in Ottawa

These days it’s all about artificial intelligence (AI) or robots and often, it’s both. They’re everywhere and they will take everyone’s jobs, or not, depending on how you view them. Today, I’ve got two artificial intelligence items, the first of which may provoke writers’ anxieties.

Fairytales

The Princess and the Fox is a new fairytale by the Brothers Grimm or rather, their artificially intelligent surrogate according to an April 18, 2018 article on the British Broadcasting Corporation’s online news website,

It was recently reported that the meditation app Calm had published a “new” fairytale by the Brothers Grimm.

However, The Princess and the Fox was written not by the brothers, who died over 150 years ago, but by humans using an artificial intelligence (AI) tool.

It’s the first fairy tale written by an AI, claims Calm, and is the result of a collaboration with Botnik Studios – a community of writers, artists and developers. Calm says the technique could be referred to as “literary cloning”.

Botnik employees used a predictive-text program to generate words and phrases that might be found in the original Grimm fairytales. Human writers then pieced together sentences to form “the rough shape of a story”, according to Jamie Brew, chief executive of Botnik.

The full version is available to paying customers of Calm, but here’s a short extract:

“Once upon a time, there was a golden horse with a golden saddle and a beautiful purple flower in its hair. The horse would carry the flower to the village where the princess danced for joy at the thought of looking so beautiful and good.

Advertising for a meditation app?

Of course, it’s advertising and it’s ‘smart’ advertising (wordplay intended). Here’s a preview/trailer,

Blair Marnell’s April 18, 2018 article for SyFy Wire provides a bit more detail,

“You might call it a form of literary cloning,” said Calm co-founder Michael Acton Smith. Calm commissioned Botnik to use its predictive text program, Voicebox, to create a new Brothers Grimm story. But first, Voicebox was given the entire collected works of the Brothers Grimm to analyze, before it suggested phrases and sentences based upon those stories. Of course, human writers gave the program an assist when it came to laying out the plot. …

“The Brothers Grimm definitely have a reputation for darkness and many of their best-known tales are undoubtedly scary,” Peter Freedman told SYFY WIRE. Freedman is a spokesperson for Calm who was a part of the team behind the creation of this story. “In the process of machine-human collaboration that generated The Princess and The Fox, we did gently steer the story towards something with a more soothing, calm plot and vibe, that would make it work both as a new Grimm fairy tale and simultaneously as a Sleep Story on Calm.” [emphasis mine]

….

If Marnell’s article is to be believed, Peter Freedman doesn’t hold much hope for writers in the long-term future although we don’t need to start ‘battening down the hatches’ yet.

You can find Calm here.

You can find Botnik  here and Botnik Studios here.

 

AI at Ingenium [Canada Science and Technology Museum] on April 25, 2018

Formerly known (I believe) [*Read the comments for the clarification] as the Canada Science and Technology Museum, Ingenium is hosting a ‘sold out but there will be a livestream’ Google event. From Ingenium’s ‘Curiosity on Stage Evening Edition with Google – The AI Revolution‘ event page,

Join Google, Inc. and the Canada Science and Technology Museum for an evening of thought-provoking discussions about artificial intelligence.

[April 25, 2018
7:00 p.m. – 10:00 p.m. {ET}
Fees: Free]

Invited speakers from industry leaders Google, Facebook, Element AI and Deepmind will explore the intersection of artificial intelligence with robotics, arts, social impact and healthcare. The session will end with a panel discussion and question-and-answer period. Following the event, there will be a reception along with light refreshments and networking opportunities.

The event will be simultaneously translated into both official languages as well as available via livestream from the Museum’s YouTube channel.

Seating is limited

THIS EVENT IS NOW SOLD OUT. Please join us for the livestream from the Museum’s YouTube channel. https://www.youtube.com/cstmweb *** April 25, 2018: I received corrective information about the link for the livestream: https://youtu.be/jG84BIno5J4 from someone at Ingenium.***

Speakers

David Usher (Moderator)

David Usher is an artist, best-selling author, entrepreneur and keynote speaker. As a musician he has sold more than 1.4 million albums, won 4 Junos and has had #1 singles singing in English, French and Thai. When David is not making music, he is equally passionate about his other life, as a Geek. He is the founder of Reimagine AI, an artificial intelligence creative studio working at the intersection of art and artificial intelligence. David is also the founder and creative director of the non-profit, the Human Impact Lab at Concordia University [located in Montréal, Québec]. The Lab uses interactive storytelling to revisualize the story of climate change. David is the co-creator, with Dr. Damon Matthews, of the Climate Clock. Climate Clock has been presented all over the world including the United Nations COP 23 Climate Conference and is presently on a three-year tour with the Canada Museum of Science and Innovation’s Climate Change Exhibit.

Joelle Pineau (Facebook)

The AI Revolution:  From Ideas and Models to Building Smart Robots
Joelle Pineau is head of the Facebook AI Research Lab Montreal, and an Associate Professor and William Dawson Scholar at McGill University. Dr. Pineau’s research focuses on developing new models and algorithms for automatic planning and learning in partially-observable domains. She also applies these algorithms to complex problems in robotics, health-care, games and conversational agents. She serves on the editorial board of the Journal of Artificial Intelligence Research and the Journal of Machine Learning Research and is currently President of the International Machine Learning Society. She is a AAAI Fellow, a Senior Fellow of the Canadian Institute for Advanced Research (CIFAR) and in 2016 was named a member of the College of New Scholars, Artists and Scientists by the Royal Society of Canada.

Pablo Samuel Castro (Google)

Building an Intelligent Assistant for Music Creators
Pablo was born and raised in Quito, Ecuador, and moved to Montreal after high school to study at McGill. He stayed in Montreal for the next 10 years, finished his bachelors, worked at a flight simulator company, and then eventually obtained his masters and PhD at McGill, focusing on Reinforcement Learning. After his PhD Pablo did a 10-month postdoc in Paris before moving to Pittsburgh to join Google. He has worked at Google for almost 6 years, and is currently a research Software Engineer in Google Brain in Montreal, focusing on fundamental Reinforcement Learning research, as well as Machine Learning and Music. Aside from his interest in coding/AI/math, Pablo is an active musician (https://www.psctrio.com), loves running (5 marathons so far, including Boston!), and discussing politics and activism.

Philippe Beaudoin (Element AI)

Concrete AI-for-Good initiatives at Element AI
Philippe cofounded Element AI in 2016 and currently leads its applied lab and AI-for-Good initiatives. His team has helped tackle some of the biggest and most interesting business challenges using machine learning. Philippe holds a Ph.D in Computer Science and taught virtual bipeds to walk by themselves during his postdoc at UBC. He spent five years at Google as a Senior Developer and Technical Lead Manager, partly with the Chrome Machine Learning team. Philippe also founded ArcBees, specializing in cloud-based development. Prior to that he worked in the videogame and graphics hardware industries. When he has some free time, Philippe likes to invent new boardgames — the kind of games where he can still beat the AI!

Doina Precup (Deepmind)

Challenges and opportunities for the AI revolution in health care
Doina Precup splits her time between McGill University, where she co-directs the Reasoning and Learning Lab in the School of Computer Science, and DeepMind Montreal, where she leads the newly formed research team since October 2017.  She got her BSc degree in computer science form the Technical University Cluj-Napoca, Romania, and her MSc and PhD degrees from the University of Massachusetts-Amherst, where she was a Fulbright fellow. Her research interests are in the areas of reinforcement learning, deep learning, time series analysis, and diverse applications of machine learning in health care, automated control and other fields. She became a senior member of AAAI in 2015, a Canada Research Chair in Machine Learning in 2016 and a Senior Fellow of CIFAR in 2017.

Interesting, oui? Not a single expert from Ottawa or Toronto. Well, Element AI has an office in Toronto. Still, I wonder why this singular focus on AI in Montréal. After all, one of the current darlings of AI, machine learning, was developed at the University of Toronto which houses the Canadian Institute for Advanced Research (CIFAR),  the institution in charge of the Pan-Canadian Artificial Intelligence Strategy and the Vector Institutes (more about that in my March 31,2017 posting).

Enough with my musing: For those of us on the West Coast, there’s an opportunity to attend via livestream from 4 pm to 7 pm on April 25, 2018 on xxxxxxxxx. *** April 25, 2018: I received corrective information about the link for the livestream: https://youtu.be/jG84BIno5J4 and clarification as the relationship between Ingenium and the Canada Science and Technology Museum from someone at Ingenium.***

For more about Element AI, go here; for more about DeepMind, go here for information about parent company in the UK and the most I dug up about their Montréal office was this job posting; and, finally , Reimagine.AI is here.

The Hedy Lamarr of international research: Canada’s Third assessment of The State of Science and Technology and Industrial Research and Development in Canada (2 of 2)

Taking up from where I left off with my comments on Competing in a Global Innovation Economy: The Current State of R and D in Canada or as I prefer to call it the Third assessment of Canadas S&T (science and technology) and R&D (research and development). (Part 1 for anyone who missed it).

Is it possible to get past Hedy?

Interestingly (to me anyway), one of our R&D strengths, the visual and performing arts, features sectors where a preponderance of people are dedicated to creating culture in Canada and don’t spend a lot of time trying to make money so they can retire before the age of 40 as so many of our start-up founders do. (Retiring before the age of 40 just reminded me of Hollywood actresses {Hedy] who found and still do find that work was/is hard to come by after that age. You may be able but I’m not sure I can get past Hedy.) Perhaps our business people (start-up founders) could take a leaf out of the visual and performing arts handbook? Or, not. There is another question.

Does it matter if we continue to be a ‘branch plant’ economy? Somebody once posed that question to me when I was grumbling that our start-ups never led to larger businesses and acted more like incubators (which could describe our R&D as well),. He noted that Canadians have a pretty good standard of living and we’ve been running things this way for over a century and it seems to work for us. Is it that bad? I didn’t have an  answer for him then and I don’t have one now but I think it’s a useful question to ask and no one on this (2018) expert panel or the previous expert panel (2013) seems to have asked.

I appreciate that the panel was constrained by the questions given by the government but given how they snuck in a few items that technically speaking were not part of their remit, I’m thinking they might have gone just a bit further. The problem with answering the questions as asked is that if you’ve got the wrong questions, your answers will be garbage (GIGO; garbage in, garbage out) or, as is said, where science is concerned, it’s the quality of your questions.

On that note, I would have liked to know more about the survey of top-cited researchers. I think looking at the questions could have been quite illuminating and I would have liked some information on from where (geographically and area of specialization) they got most of their answers. In keeping with past practice (2012 assessment published in 2013), there is no additional information offered about the survey questions or results. Still, there was this (from the report released April 10, 2018; Note: There may be some difference between the formatting seen here and that seen in the document),

3.1.2 International Perceptions of Canadian Research
As with the 2012 S&T report, the CCA commissioned a survey of top-cited researchers’ perceptions of Canada’s research strength in their field or subfield relative to that of other countries (Section 1.3.2). Researchers were asked to identify the top five countries in their field and subfield of expertise: 36% of respondents (compared with 37% in the 2012 survey) from across all fields of research rated Canada in the top five countries in their field (Figure B.1 and Table B.1 in the appendix). Canada ranks fourth out of all countries, behind the United States, United Kingdom, and Germany, and ahead of France. This represents a change of about 1 percentage point from the overall results of the 2012 S&T survey. There was a 4 percentage point decrease in how often France is ranked among the top five countries; the ordering of the top five countries, however, remains the same.

When asked to rate Canada’s research strength among other advanced countries in their field of expertise, 72% (4,005) of respondents rated Canadian research as “strong” (corresponding to a score of 5 or higher on a 7-point scale) compared with 68% in the 2012 S&T survey (Table 3.4). [pp. 40-41 Print; pp. 78-70 PDF]

Before I forget, there was mention of the international research scene,

Growth in research output, as estimated by number of publications, varies considerably for the 20 top countries. Brazil, China, India, Iran, and South Korea have had the most significant increases in publication output over the last 10 years. [emphases mine] In particular, the dramatic increase in China’s output means that it is closing the gap with the United States. In 2014, China’s output was 95% of that of the United States, compared with 26% in 2003. [emphasis mine]

Table 3.2 shows the Growth Index (GI), a measure of the rate at which the research output for a given country changed between 2003 and 2014, normalized by the world growth rate. If a country’s growth in research output is higher than the world average, the GI score is greater than 1.0. For example, between 2003 and 2014, China’s GI score was 1.50 (i.e., 50% greater than the world average) compared with 0.88 and 0.80 for Canada and the United States, respectively. Note that the dramatic increase in publication production of emerging economies such as China and India has had a negative impact on Canada’s rank and GI score (see CCA, 2016).

As long as I’ve been blogging (10 years), the international research community (in particular the US) has been looking over its shoulder at China.

Patents and intellectual property

As an inventor, Hedy got more than one patent. Much has been made of the fact that  despite an agreement, the US Navy did not pay her or her partner (George Antheil) for work that would lead to significant military use (apparently, it was instrumental in the Bay of Pigs incident, for those familiar with that bit of history), GPS, WiFi, Bluetooth, and more.

Some comments about patents. They are meant to encourage more innovation by ensuring that creators/inventors get paid for their efforts .This is true for a set time period and when it’s over, other people get access and can innovate further. It’s not intended to be a lifelong (or inheritable) source of income. The issue in Lamarr’s case is that the navy developed the technology during the patent’s term without telling either her or her partner so, of course, they didn’t need to compensate them despite the original agreement. They really should have paid her and Antheil.

The current patent situation, particularly in the US, is vastly different from the original vision. These days patents are often used as weapons designed to halt innovation. One item that should be noted is that the Canadian federal budget indirectly addressed their misuse (from my March 16, 2018 posting),

Surprisingly, no one else seems to have mentioned a new (?) intellectual property strategy introduced in the document (from Chapter 2: Progress; scroll down about 80% of the way, Note: The formatting has been changed),

Budget 2018 proposes measures in support of a new Intellectual Property Strategy to help Canadian entrepreneurs better understand and protect intellectual property, and get better access to shared intellectual property.

What Is a Patent Collective?
A Patent Collective is a way for firms to share, generate, and license or purchase intellectual property. The collective approach is intended to help Canadian firms ensure a global “freedom to operate”, mitigate the risk of infringing a patent, and aid in the defence of a patent infringement suit.

Budget 2018 proposes to invest $85.3 million over five years, starting in 2018–19, with $10 million per year ongoing, in support of the strategy. The Minister of Innovation, Science and Economic Development will bring forward the full details of the strategy in the coming months, including the following initiatives to increase the intellectual property literacy of Canadian entrepreneurs, and to reduce costs and create incentives for Canadian businesses to leverage their intellectual property:

  • To better enable firms to access and share intellectual property, the Government proposes to provide $30 million in 2019–20 to pilot a Patent Collective. This collective will work with Canada’s entrepreneurs to pool patents, so that small and medium-sized firms have better access to the critical intellectual property they need to grow their businesses.
  • To support the development of intellectual property expertise and legal advice for Canada’s innovation community, the Government proposes to provide $21.5 million over five years, starting in 2018–19, to Innovation, Science and Economic Development Canada. This funding will improve access for Canadian entrepreneurs to intellectual property legal clinics at universities. It will also enable the creation of a team in the federal government to work with Canadian entrepreneurs to help them develop tailored strategies for using their intellectual property and expanding into international markets.
  • To support strategic intellectual property tools that enable economic growth, Budget 2018 also proposes to provide $33.8 million over five years, starting in 2018–19, to Innovation, Science and Economic Development Canada, including $4.5 million for the creation of an intellectual property marketplace. This marketplace will be a one-stop, online listing of public sector-owned intellectual property available for licensing or sale to reduce transaction costs for businesses and researchers, and to improve Canadian entrepreneurs’ access to public sector-owned intellectual property.

The Government will also consider further measures, including through legislation, in support of the new intellectual property strategy.

Helping All Canadians Harness Intellectual Property
Intellectual property is one of our most valuable resources, and every Canadian business owner should understand how to protect and use it.

To better understand what groups of Canadians are benefiting the most from intellectual property, Budget 2018 proposes to provide Statistics Canada with $2 million over three years to conduct an intellectual property awareness and use survey. This survey will help identify how Canadians understand and use intellectual property, including groups that have traditionally been less likely to use intellectual property, such as women and Indigenous entrepreneurs. The results of the survey should help the Government better meet the needs of these groups through education and awareness initiatives.

The Canadian Intellectual Property Office will also increase the number of education and awareness initiatives that are delivered in partnership with business, intermediaries and academia to ensure Canadians better understand, integrate and take advantage of intellectual property when building their business strategies. This will include targeted initiatives to support underrepresented groups.

Finally, Budget 2018 also proposes to invest $1 million over five years to enable representatives of Canada’s Indigenous Peoples to participate in discussions at the World Intellectual Property Organization related to traditional knowledge and traditional cultural expressions, an important form of intellectual property.

It’s not wholly clear what they mean by ‘intellectual property’. The focus seems to be on  patents as they are the only intellectual property (as opposed to copyright and trademarks) singled out in the budget. As for how the ‘patent collective’ is going to meet all its objectives, this budget supplies no clarity on the matter. On the plus side, I’m glad to see that indigenous peoples’ knowledge is being acknowledged as “an important form of intellectual property” and I hope the discussions at the World Intellectual Property Organization are fruitful.

As for the patent situation in Canada (from the report released April 10, 2018),

Over the past decade, the Canadian patent flow in all technical sectors has consistently decreased. Patent flow provides a partial picture of how patents in Canada are exploited. A negative flow represents a deficit of patented inventions owned by Canadian assignees versus the number of patented inventions created by Canadian inventors. The patent flow for all Canadian patents decreased from about −0.04 in 2003 to −0.26 in 2014 (Figure 4.7). This means that there is an overall deficit of 26% of patent ownership in Canada. In other words, fewer patents were owned by Canadian institutions than were invented in Canada.

This is a significant change from 2003 when the deficit was only 4%. The drop is consistent across all technical sectors in the past 10 years, with Mechanical Engineering falling the least, and Electrical Engineering the most (Figure 4.7). At the technical field level, the patent flow dropped significantly in Digital Communication and Telecommunications. For example, the Digital Communication patent flow fell from 0.6 in 2003 to −0.2 in 2014. This fall could be partially linked to Nortel’s US$4.5 billion patent sale [emphasis mine] to the Rockstar consortium (which included Apple, BlackBerry, Ericsson, Microsoft, and Sony) (Brickley, 2011). Food Chemistry and Microstructural [?] and Nanotechnology both also showed a significant drop in patent flow. [p. 83 Print; p. 121 PDF]

Despite a fall in the number of parents for ‘Digital Communication’, we’re still doing well according to statistics elsewhere in this report. Is it possible that patents aren’t that big a deal? Of course, it’s also possible that we are enjoying the benefits of past work and will miss out on future work. (Note: A video of the April 10, 2018 report presentation by Max Blouw features him saying something like that.)

One last note, Nortel died many years ago. Disconcertingly, this report, despite more than one reference to Nortel, never mentions the company’s demise.

Boxed text

While the expert panel wasn’t tasked to answer certain types of questions, as I’ve noted earlier they managed to sneak in a few items.  One of the strategies they used was putting special inserts into text boxes including this (from the report released April 10, 2018),

Box 4.2
The FinTech Revolution

Financial services is a key industry in Canada. In 2015, the industry accounted for 4.4%

of Canadia jobs and about 7% of Canadian GDP (Burt, 2016). Toronto is the second largest financial services hub in North America and one of the most vibrant research hubs in FinTech. Since 2010, more than 100 start-up companies have been founded in Canada, attracting more than $1 billion in investment (Moffatt, 2016). In 2016 alone, venture-backed investment in Canadian financial technology companies grew by 35% to $137.7 million (Ho, 2017). The Toronto Financial Services Alliance estimates that there are approximately 40,000 ICT specialists working in financial services in Toronto alone.

AI, blockchain, [emphasis mine] and other results of ICT research provide the basis for several transformative FinTech innovations including, for example, decentralized transaction ledgers, cryptocurrencies (e.g., bitcoin), and AI-based risk assessment and fraud detection. These innovations offer opportunities to develop new markets for established financial services firms, but also provide entry points for technology firms to develop competing service offerings, increasing competition in the financial services industry. In response, many financial services companies are increasing their investments in FinTech companies (Breznitz et al., 2015). By their own account, the big five banks invest more than $1 billion annually in R&D of advanced software solutions, including AI-based innovations (J. Thompson, personal communication, 2016). The banks are also increasingly investing in university research and collaboration with start-up companies. For instance, together with several large insurance and financial management firms, all big five banks have invested in the Vector Institute for Artificial Intelligence (Kolm, 2017).

I’m glad to see the mention of blockchain while AI (artificial intelligence) is an area where we have innovated (from the report released April 10, 2018),

AI has attracted researchers and funding since the 1960s; however, there were periods of stagnation in the 1970s and 1980s, sometimes referred to as the “AI winter.” During this period, the Canadian Institute for Advanced Research (CIFAR), under the direction of Fraser Mustard, started supporting AI research with a decade-long program called Artificial Intelligence, Robotics and Society, [emphasis mine] which was active from 1983 to 1994. In 2004, a new program called Neural Computation and Adaptive Perception was initiated and renewed twice in 2008 and 2014 under the title, Learning in Machines and Brains. Through these programs, the government provided long-term, predictable support for high- risk research that propelled Canadian researchers to the forefront of global AI development. In the 1990s and early 2000s, Canadian research output and impact on AI were second only to that of the United States (CIFAR, 2016). NSERC has also been an early supporter of AI. According to its searchable grant database, NSERC has given funding to research projects on AI since at least 1991–1992 (the earliest searchable year) (NSERC, 2017a).

The University of Toronto, the University of Alberta, and the Université de Montréal have emerged as international centres for research in neural networks and deep learning, with leading experts such as Geoffrey Hinton and Yoshua Bengio. Recently, these locations have expanded into vibrant hubs for research in AI applications with a diverse mix of specialized research institutes, accelerators, and start-up companies, and growing investment by major international players in AI development, such as Microsoft, Google, and Facebook. Many highly influential AI researchers today are either from Canada or have at some point in their careers worked at a Canadian institution or with Canadian scholars.

As international opportunities in AI research and the ICT industry have grown, many of Canada’s AI pioneers have been drawn to research institutions and companies outside of Canada. According to the OECD, Canada’s share of patents in AI declined from 2.4% in 2000 to 2005 to 2% in 2010 to 2015. Although Canada is the sixth largest producer of top-cited scientific publications related to machine learning, firms headquartered in Canada accounted for only 0.9% of all AI-related inventions from 2012 to 2014 (OECD, 2017c). Canadian AI researchers, however, remain involved in the core nodes of an expanding international network of AI researchers, most of whom continue to maintain ties with their home institutions. Compared with their international peers, Canadian AI researchers are engaged in international collaborations far more often than would be expected by Canada’s level of research output, with Canada ranking fifth in collaboration. [p. 97-98 Print; p. 135-136 PDF]

The only mention of robotics seems to be here in this section and it’s only in passing. This is a bit surprising given its global importance. I wonder if robotics has been somehow hidden inside the term artificial intelligence, although sometimes it’s vice versa with robot being used to describe artificial intelligence. I’m noticing this trend of assuming the terms are synonymous or interchangeable not just in Canadian publications but elsewhere too.  ’nuff said.

Getting back to the matter at hand, t he report does note that patenting (technometric data) is problematic (from the report released April 10, 2018),

The limitations of technometric data stem largely from their restricted applicability across areas of R&D. Patenting, as a strategy for IP management, is similarly limited in not being equally relevant across industries. Trends in patenting can also reflect commercial pressures unrelated to R&D activities, such as defensive or strategic patenting practices. Finally, taxonomies for assessing patents are not aligned with bibliometric taxonomies, though links can be drawn to research publications through the analysis of patent citations. [p. 105 Print; p. 143 PDF]

It’s interesting to me that they make reference to many of the same issues that I mention but they seem to forget and don’t use that information in their conclusions.

There is one other piece of boxed text I want to highlight (from the report released April 10, 2018),

Box 6.3
Open Science: An Emerging Approach to Create New Linkages

Open Science is an umbrella term to describe collaborative and open approaches to
undertaking science, which can be powerful catalysts of innovation. This includes
the development of open collaborative networks among research performers, such
as the private sector, and the wider distribution of research that usually results when
restrictions on use are removed. Such an approach triggers faster translation of ideas
among research partners and moves the boundaries of pre-competitive research to
later, applied stages of research. With research results freely accessible, companies
can focus on developing new products and processes that can be commercialized.

Two Canadian organizations exemplify the development of such models. In June
2017, Genome Canada, the Ontario government, and pharmaceutical companies
invested $33 million in the Structural Genomics Consortium (SGC) (Genome Canada,
2017). Formed in 2004, the SGC is at the forefront of the Canadian open science
movement and has contributed to many key research advancements towards new
treatments (SGC, 2018). McGill University’s Montréal Neurological Institute and
Hospital has also embraced the principles of open science. Since 2016, it has been
sharing its research results with the scientific community without restriction, with
the objective of expanding “the impact of brain research and accelerat[ing] the
discovery of ground-breaking therapies to treat patients suffering from a wide range
of devastating neurological diseases” (neuro, n.d.).

This is exciting stuff and I’m happy the panel featured it. (I wrote about the Montréal Neurological Institute initiative in a Jan. 22, 2016 posting.)

More than once, the report notes the difficulties with using bibliometric and technometric data as measures of scientific achievement and progress and open science (along with its cousins, open data and open access) are contributing to the difficulties as James Somers notes in his April 5, 2018 article ‘The Scientific Paper is Obsolete’ for The Atlantic (Note: Links have been removed),

The scientific paper—the actual form of it—was one of the enabling inventions of modernity. Before it was developed in the 1600s, results were communicated privately in letters, ephemerally in lectures, or all at once in books. There was no public forum for incremental advances. By making room for reports of single experiments or minor technical advances, journals made the chaos of science accretive. Scientists from that point forward became like the social insects: They made their progress steadily, as a buzzing mass.

The earliest papers were in some ways more readable than papers are today. They were less specialized, more direct, shorter, and far less formal. Calculus had only just been invented. Entire data sets could fit in a table on a single page. What little “computation” contributed to the results was done by hand and could be verified in the same way.

The more sophisticated science becomes, the harder it is to communicate results. Papers today are longer than ever and full of jargon and symbols. They depend on chains of computer programs that generate data, and clean up data, and plot data, and run statistical models on data. These programs tend to be both so sloppily written and so central to the results that it’s [sic] contributed to a replication crisis, or put another way, a failure of the paper to perform its most basic task: to report what you’ve actually discovered, clearly enough that someone else can discover it for themselves.

Perhaps the paper itself is to blame. Scientific methods evolve now at the speed of software; the skill most in demand among physicists, biologists, chemists, geologists, even anthropologists and research psychologists, is facility with programming languages and “data science” packages. And yet the basic means of communicating scientific results hasn’t changed for 400 years. Papers may be posted online, but they’re still text and pictures on a page.

What would you get if you designed the scientific paper from scratch today? A little while ago I spoke to Bret Victor, a researcher who worked at Apple on early user-interface prototypes for the iPad and now runs his own lab in Oakland, California, that studies the future of computing. Victor has long been convinced that scientists haven’t yet taken full advantage of the computer. “It’s not that different than looking at the printing press, and the evolution of the book,” he said. After Gutenberg, the printing press was mostly used to mimic the calligraphy in bibles. It took nearly 100 years of technical and conceptual improvements to invent the modern book. “There was this entire period where they had the new technology of printing, but they were just using it to emulate the old media.”Victor gestured at what might be possible when he redesigned a journal article by Duncan Watts and Steven Strogatz, “Collective dynamics of ‘small-world’ networks.” He chose it both because it’s one of the most highly cited papers in all of science and because it’s a model of clear exposition. (Strogatz is best known for writing the beloved “Elements of Math” column for The New York Times.)

The Watts-Strogatz paper described its key findings the way most papers do, with text, pictures, and mathematical symbols. And like most papers, these findings were still hard to swallow, despite the lucid prose. The hardest parts were the ones that described procedures or algorithms, because these required the reader to “play computer” in their head, as Victor put it, that is, to strain to maintain a fragile mental picture of what was happening with each step of the algorithm.Victor’s redesign interleaved the explanatory text with little interactive diagrams that illustrated each step. In his version, you could see the algorithm at work on an example. You could even control it yourself….

For anyone interested in the evolution of how science is conducted and communicated, Somers’ article is a fascinating and in depth look at future possibilities.

Subregional R&D

I didn’t find this quite as compelling as the last time and that may be due to the fact that there’s less information and I think the 2012 report was the first to examine the Canadian R&D scene with a subregional (in their case, provinces) lens. On a high note, this report also covers cities (!) and regions, as well as, provinces.

Here’s the conclusion (from the report released April 10, 2018),

Ontario leads Canada in R&D investment and performance. The province accounts for almost half of R&D investment and personnel, research publications and collaborations, and patents. R&D activity in Ontario produces high-quality publications in each of Canada’s five R&D strengths, reflecting both the quantity and quality of universities in the province. Quebec lags Ontario in total investment, publications, and patents, but performs as well (citations) or better (R&D intensity) by some measures. Much like Ontario, Quebec researchers produce impactful publications across most of Canada’s five R&D strengths. Although it invests an amount similar to that of Alberta, British Columbia does so at a significantly higher intensity. British Columbia also produces more highly cited publications and patents, and is involved in more international research collaborations. R&D in British Columbia and Alberta clusters around Vancouver and Calgary in areas such as physics and ICT and in clinical medicine and energy, respectively. [emphasis mine] Smaller but vibrant R&D communities exist in the Prairies and Atlantic Canada [also referred to as the Maritime provinces or Maritimes] (and, to a lesser extent, in the Territories) in natural resource industries.

Globally, as urban populations expand exponentially, cities are likely to drive innovation and wealth creation at an increasing rate in the future. In Canada, R&D activity clusters around five large cities: Toronto, Montréal, Vancouver, Ottawa, and Calgary. These five cities create patents and high-tech companies at nearly twice the rate of other Canadian cities. They also account for half of clusters in the services sector, and many in advanced manufacturing.

Many clusters relate to natural resources and long-standing areas of economic and research strength. Natural resource clusters have emerged around the location of resources, such as forestry in British Columbia, oil and gas in Alberta, agriculture in Ontario, mining in Quebec, and maritime resources in Atlantic Canada. The automotive, plastics, and steel industries have the most individual clusters as a result of their economic success in Windsor, Hamilton, and Oshawa. Advanced manufacturing industries tend to be more concentrated, often located near specialized research universities. Strong connections between academia and industry are often associated with these clusters. R&D activity is distributed across the country, varying both between and within regions. It is critical to avoid drawing the wrong conclusion from this fact. This distribution does not imply the existence of a problem that needs to be remedied. Rather, it signals the benefits of diverse innovation systems, with differentiation driven by the needs of and resources available in each province. [pp.  132-133 Print; pp. 170-171 PDF]

Intriguingly, there’s no mention that in British Columbia (BC), there are leading areas of research: Visual & Performing Arts, Psychology & Cognitive Sciences, and Clinical Medicine (according to the table on p. 117 Print, p. 153 PDF).

As I said and hinted earlier, we’ve got brains; they’re just not the kind of brains that command respect.

Final comments

My hat’s off to the expert panel and staff of the Council of Canadian Academies. Combining two previous reports into one could not have been easy. As well, kudos to their attempts to broaden the discussion by mentioning initiative such as open science and for emphasizing the problems with bibliometrics, technometrics, and other measures. I have covered only parts of this assessment, (Competing in a Global Innovation Economy: The Current State of R&D in Canada), there’s a lot more to it including a substantive list of reference materials (bibliography).

While I have argued that perhaps the situation isn’t quite as bad as the headlines and statistics may suggest, there are some concerning trends for Canadians but we have to acknowledge that many countries have stepped up their research game and that’s good for all of us. You don’t get better at anything unless you work with and play with others who are better than you are. For example, both India and Italy surpassed us in numbers of published research papers. We slipped from 7th place to 9th. Thank you, Italy and India. (And, Happy ‘Italian Research in the World Day’ on April 15, 2018, the day’s inaugural year. In Italian: Piano Straordinario “Vivere all’Italiana” – Giornata della ricerca Italiana nel mondo.)

Unfortunately, the reading is harder going than previous R&D assessments in the CCA catalogue. And in the end, I can’t help thinking we’re just a little bit like Hedy Lamarr. Not really appreciated in all of our complexities although the expert panel and staff did try from time to time. Perhaps the government needs to find better ways of asking the questions.

***ETA April 12, 2018 at 1500 PDT: Talking about missing the obvious! I’ve been ranting on about how research strength in visual and performing arts and in philosophy and theology, etc. is perfectly fine and could lead to ‘traditional’ science breakthroughs without underlining the point by noting that Antheil was a musician, Lamarr was as an actress and they set the foundation for work by electrical engineers (or people with that specialty) for their signature work leading to WiFi, etc.***

There is, by the way, a Hedy-Canada connection. In 1998, she sued Canadian software company Corel, for its unauthorized use of her image on their Corel Draw 8 product packaging. She won.

More stuff

For those who’d like to see and hear the April 10, 2017 launch for “Competing in a Global Innovation Economy: The Current State of R&D in Canada” or the Third Assessment as I think of it, go here.

The report can be found here.

For anyone curious about ‘Bombshell: The Hedy Lamarr Story’ to be broadcast on May 18, 2018 as part of PBS’s American Masters series, there’s this trailer,

For the curious, I did find out more about the Hedy Lamarr and Corel Draw. John Lettice’s December 2, 1998 article The Rgister describes the suit and her subsequent victory in less than admiring terms,

Our picture doesn’t show glamorous actress Hedy Lamarr, who yesterday [Dec. 1, 1998] came to a settlement with Corel over the use of her image on Corel’s packaging. But we suppose that following the settlement we could have used a picture of Corel’s packaging. Lamarr sued Corel earlier this year over its use of a CorelDraw image of her. The picture had been produced by John Corkery, who was 1996 Best of Show winner of the Corel World Design Contest. Corel now seems to have come to an undisclosed settlement with her, which includes a five-year exclusive (oops — maybe we can’t use the pack-shot then) licence to use “the lifelike vector illustration of Hedy Lamarr on Corel’s graphic software packaging”. Lamarr, bless ‘er, says she’s looking forward to the continued success of Corel Corporation,  …

There’s this excerpt from a Sept. 21, 2015 posting (a pictorial essay of Lamarr’s life) by Shahebaz Khan on The Blaze Blog,

6. CorelDRAW:
For several years beginning in 1997, the boxes of Corel DRAW’s software suites were graced by a large Corel-drawn image of Lamarr. The picture won Corel DRAW’s yearly software suite cover design contest in 1996. Lamarr sued Corel for using the image without her permission. Corel countered that she did not own rights to the image. The parties reached an undisclosed settlement in 1998.

There’s also a Nov. 23, 1998 Corel Draw 8 product review by Mike Gorman on mymac.com, which includes a screenshot of the packaging that precipitated the lawsuit. Once they settled, it seems Corel used her image at least one more time.

The Hedy Lamarr of international research: Canada’s Third assessment of The State of Science and Technology and Industrial Research and Development in Canada (1 of 2)

Before launching into the assessment, a brief explanation of my theme: Hedy Lamarr was considered to be one of the great beauties of her day,

“Ziegfeld Girl” Hedy Lamarr 1941 MGM *M.V.
Titles: Ziegfeld Girl
People: Hedy Lamarr
Image courtesy mptvimages.com [downloaded from https://www.imdb.com/title/tt0034415/mediaviewer/rm1566611456]

Aside from starring in Hollywood movies and, before that, movies in Europe, she was also an inventor and not just any inventor (from a Dec. 4, 2017 article by Laura Barnett for The Guardian), Note: Links have been removed,

Let’s take a moment to reflect on the mercurial brilliance of Hedy Lamarr. Not only did the Vienna-born actor flee a loveless marriage to a Nazi arms dealer to secure a seven-year, $3,000-a-week contract with MGM, and become (probably) the first Hollywood star to simulate a female orgasm on screen – she also took time out to invent a device that would eventually revolutionise mobile communications.

As described in unprecedented detail by the American journalist and historian Richard Rhodes in his new book, Hedy’s Folly, Lamarr and her business partner, the composer George Antheil, were awarded a patent in 1942 for a “secret communication system”. It was meant for radio-guided torpedoes, and the pair gave to the US Navy. It languished in their files for decades before eventually becoming a constituent part of GPS, Wi-Fi and Bluetooth technology.

(The article goes on to mention other celebrities [Marlon Brando, Barbara Cartland, Mark Twain, etc] and their inventions.)

Lamarr’s work as an inventor was largely overlooked until the 1990’s when the technology community turned her into a ‘cultish’ favourite and from there her reputation grew and acknowledgement increased culminating in Rhodes’ book and the documentary by Alexandra Dean, ‘Bombshell: The Hedy Lamarr Story (to be broadcast as part of PBS’s American Masters series on May 18, 2018).

Canada as Hedy Lamarr

There are some parallels to be drawn between Canada’s S&T and R&D (science and technology; research and development) and Ms. Lamarr. Chief amongst them, we’re not always appreciated for our brains. Not even by people who are supposed to know better such as the experts on the panel for the ‘Third assessment of The State of Science and Technology and Industrial Research and Development in Canada’ (proper title: Competing in a Global Innovation Economy: The Current State of R&D in Canada) from the Expert Panel on the State of Science and Technology and Industrial Research and Development in Canada.

A little history

Before exploring the comparison to Hedy Lamarr further, here’s a bit more about the history of this latest assessment from the Council of Canadian Academies (CCA), from the report released April 10, 2018,

This assessment of Canada’s performance indicators in science, technology, research, and innovation comes at an opportune time. The Government of Canada has expressed a renewed commitment in several tangible ways to this broad domain of activity including its Innovation and Skills Plan, the announcement of five superclusters, its appointment of a new Chief Science Advisor, and its request for the Fundamental Science Review. More specifically, the 2018 Federal Budget demonstrated the government’s strong commitment to research and innovation with historic investments in science.

The CCA has a decade-long history of conducting evidence-based assessments about Canada’s research and development activities, producing seven assessments of relevance:

The State of Science and Technology in Canada (2006) [emphasis mine]
•Innovation and Business Strategy: Why Canada Falls Short (2009)
•Catalyzing Canada’s Digital Economy (2010)
•Informing Research Choices: Indicators and Judgment (2012)
The State of Science and Technology in Canada (2012) [emphasis mine]
The State of Industrial R&D in Canada (2013) [emphasis mine]
•Paradox Lost: Explaining Canada’s Research Strength and Innovation Weakness (2013)

Using similar methods and metrics to those in The State of Science and Technology in Canada (2012) and The State of Industrial R&D in Canada (2013), this assessment tells a similar and familiar story: Canada has much to be proud of, with world-class researchers in many domains of knowledge, but the rest of the world is not standing still. Our peers are also producing high quality results, and many countries are making significant commitments to supporting research and development that will position them to better leverage their strengths to compete globally. Canada will need to take notice as it determines how best to take action. This assessment provides valuable material for that conversation to occur, whether it takes place in the lab or the legislature, the bench or the boardroom. We also hope it will be used to inform public discussion. [p. ix Print, p. 11 PDF]

This latest assessment succeeds the general 2006 and 2012 reports, which were mostly focused on academic research, and combines it with an assessment of industrial research, which was previously separate. Also, this third assessment’s title (Competing in a Global Innovation Economy: The Current State of R&D in Canada) makes what was previously quietly declared in the text, explicit from the cover onwards. It’s all about competition, despite noises such as the 2017 Naylor report (Review of fundamental research) about the importance of fundamental research.

One other quick comment, I did wonder in my July 1, 2016 posting (featuring the announcement of the third assessment) how combining two assessments would impact the size of the expert panel and the size of the final report,

Given the size of the 2012 assessment of science and technology at 232 pp. (PDF) and the 2013 assessment of industrial research and development at 220 pp. (PDF) with two expert panels, the imagination boggles at the potential size of the 2016 expert panel and of the 2016 assessment combining the two areas.

I got my answer with regard to the panel as noted in my Oct. 20, 2016 update (which featured a list of the members),

A few observations, given the size of the task, this panel is lean. As well, there are three women in a group of 13 (less than 25% representation) in 2016? It’s Ontario and Québec-dominant; only BC and Alberta rate a representative on the panel. I hope they will find ways to better balance this panel and communicate that ‘balanced story’ to the rest of us. On the plus side, the panel has representatives from the humanities, arts, and industry in addition to the expected representatives from the sciences.

The imbalance I noted then was addressed, somewhat, with the selection of the reviewers (from the report released April 10, 2018),

The CCA wishes to thank the following individuals for their review of this report:

Ronald Burnett, C.M., O.B.C., RCA, Chevalier de l’ordre des arts et des
lettres, President and Vice-Chancellor, Emily Carr University of Art and Design
(Vancouver, BC)

Michelle N. Chretien, Director, Centre for Advanced Manufacturing and Design
Technologies, Sheridan College; Former Program and Business Development
Manager, Electronic Materials, Xerox Research Centre of Canada (Brampton,
ON)

Lisa Crossley, CEO, Reliq Health Technologies, Inc. (Ancaster, ON)
Natalie Dakers, Founding President and CEO, Accel-Rx Health Sciences
Accelerator (Vancouver, BC)

Fred Gault, Professorial Fellow, United Nations University-MERIT (Maastricht,
Netherlands)

Patrick D. Germain, Principal Engineering Specialist, Advanced Aerodynamics,
Bombardier Aerospace (Montréal, QC)

Robert Brian Haynes, O.C., FRSC, FCAHS, Professor Emeritus, DeGroote
School of Medicine, McMaster University (Hamilton, ON)

Susan Holt, Chief, Innovation and Business Relationships, Government of
New Brunswick (Fredericton, NB)

Pierre A. Mohnen, Professor, United Nations University-MERIT and Maastricht
University (Maastricht, Netherlands)

Peter J. M. Nicholson, C.M., Retired; Former and Founding President and
CEO, Council of Canadian Academies (Annapolis Royal, NS)

Raymond G. Siemens, Distinguished Professor, English and Computer Science
and Former Canada Research Chair in Humanities Computing, University of
Victoria (Victoria, BC) [pp. xii- xiv Print; pp. 15-16 PDF]

The proportion of women to men as reviewers jumped up to about 36% (4 of 11 reviewers) and there are two reviewers from the Maritime provinces. As usual, reviewers external to Canada were from Europe. Although this time, they came from Dutch institutions rather than UK or German institutions. Interestingly and unusually, there was no one from a US institution. When will they start using reviewers from other parts of the world?

As for the report itself, it is 244 pp. (PDF). (For the really curious, I have a  December 15, 2016 post featuring my comments on the preliminary data for the third assessment.)

To sum up, they had a lean expert panel tasked with bringing together two inquiries and two reports. I imagine that was daunting. Good on them for finding a way to make it manageable.

Bibliometrics, patents, and a survey

I wish more attention had been paid to some of the issues around open science, open access, and open data, which are changing how science is being conducted. (I have more about this from an April 5, 2018 article by James Somers for The Atlantic but more about that later.) If I understand rightly, they may not have been possible due to the nature of the questions posed by the government when requested the assessment.

As was done for the second assessment, there is an acknowledgement that the standard measures/metrics (bibliometrics [no. of papers published, which journals published them; number of times papers were cited] and technometrics [no. of patent applications, etc.] of scientific accomplishment and progress are not the best and new approaches need to be developed and adopted (from the report released April 10, 2018),

It is also worth noting that the Panel itself recognized the limits that come from using traditional historic metrics. Additional approaches will be needed the next time this assessment is done. [p. ix Print; p. 11 PDF]

For the second assessment and as a means of addressing some of the problems with metrics, the panel decided to take a survey which the panel for the third assessment has also done (from the report released April 10, 2018),

The Panel relied on evidence from multiple sources to address its charge, including a literature review and data extracted from statistical agencies and organizations such as Statistics Canada and the OECD. For international comparisons, the Panel focused on OECD countries along with developing countries that are among the top 20 producers of peer-reviewed research publications (e.g., China, India, Brazil, Iran, Turkey). In addition to the literature review, two primary research approaches informed the Panel’s assessment:
•a comprehensive bibliometric and technometric analysis of Canadian research publications and patents; and,
•a survey of top-cited researchers around the world.

Despite best efforts to collect and analyze up-to-date information, one of the Panel’s findings is that data limitations continue to constrain the assessment of R&D activity and excellence in Canada. This is particularly the case with industrial R&D and in the social sciences, arts, and humanities. Data on industrial R&D activity continue to suffer from time lags for some measures, such as internationally comparable data on R&D intensity by sector and industry. These data also rely on industrial categories (i.e., NAICS and ISIC codes) that can obscure important trends, particularly in the services sector, though Statistics Canada’s recent revisions to how this data is reported have improved this situation. There is also a lack of internationally comparable metrics relating to R&D outcomes and impacts, aside from those based on patents.

For the social sciences, arts, and humanities, metrics based on journal articles and other indexed publications provide an incomplete and uneven picture of research contributions. The expansion of bibliometric databases and methodological improvements such as greater use of web-based metrics, including paper views/downloads and social media references, will support ongoing, incremental improvements in the availability and accuracy of data. However, future assessments of R&D in Canada may benefit from more substantive integration of expert review, capable of factoring in different types of research outputs (e.g., non-indexed books) and impacts (e.g., contributions to communities or impacts on public policy). The Panel has no doubt that contributions from the humanities, arts, and social sciences are of equal importance to national prosperity. It is vital that such contributions are better measured and assessed. [p. xvii Print; p. 19 PDF]

My reading: there’s a problem and we’re not going to try and fix it this time. Good luck to those who come after us. As for this line: “The Panel has no doubt that contributions from the humanities, arts, and social sciences are of equal importance to national prosperity.” Did no one explain that when you use ‘no doubt’, you are introducing doubt? It’s a cousin to ‘don’t take this the wrong way’ and ‘I don’t mean to be rude but …’ .

Good news

This is somewhat encouraging (from the report released April 10, 2018),

Canada’s international reputation for its capacity to participate in cutting-edge R&D is strong, with 60% of top-cited researchers surveyed internationally indicating that Canada hosts world-leading infrastructure or programs in their fields. This share increased by four percentage points between 2012 and 2017. Canada continues to benefit from a highly educated population and deep pools of research skills and talent. Its population has the highest level of educational attainment in the OECD in the proportion of the population with
a post-secondary education. However, among younger cohorts (aged 25 to 34), Canada has fallen behind Japan and South Korea. The number of researchers per capita in Canada is on a par with that of other developed countries, andincreased modestly between 2004 and 2012. Canada’s output of PhD graduates has also grown in recent years, though it remains low in per capita terms relative to many OECD countries. [pp. xvii-xviii; pp. 19-20]

Don’t let your head get too big

Most of the report observes that our international standing is slipping in various ways such as this (from the report released April 10, 2018),

In contrast, the number of R&D personnel employed in Canadian businesses
dropped by 20% between 2008 and 2013. This is likely related to sustained and
ongoing decline in business R&D investment across the country. R&D as a share
of gross domestic product (GDP) has steadily declined in Canada since 2001,
and now stands well below the OECD average (Figure 1). As one of few OECD
countries with virtually no growth in total national R&D expenditures between
2006 and 2015, Canada would now need to more than double expenditures to
achieve an R&D intensity comparable to that of leading countries.

Low and declining business R&D expenditures are the dominant driver of this
trend; however, R&D spending in all sectors is implicated. Government R&D
expenditures declined, in real terms, over the same period. Expenditures in the
higher education sector (an indicator on which Canada has traditionally ranked
highly) are also increasing more slowly than the OECD average. Significant
erosion of Canada’s international competitiveness and capacity to participate
in R&D and innovation is likely to occur if this decline and underinvestment
continue.

Between 2009 and 2014, Canada produced 3.8% of the world’s research
publications, ranking ninth in the world. This is down from seventh place for
the 2003–2008 period. India and Italy have overtaken Canada although the
difference between Italy and Canada is small. Publication output in Canada grew
by 26% between 2003 and 2014, a growth rate greater than many developed
countries (including United States, France, Germany, United Kingdom, and
Japan), but below the world average, which reflects the rapid growth in China
and other emerging economies. Research output from the federal government,
particularly the National Research Council Canada, dropped significantly
between 2009 and 2014.(emphasis mine)  [p. xviii Print; p. 20 PDF]

For anyone unfamiliar with Canadian politics,  2009 – 2014 were years during which Stephen Harper’s Conservatives formed the government. Justin Trudeau’s Liberals were elected to form the government in late 2015.

During Harper’s years in government, the Conservatives were very interested in changing how the National Research Council of Canada operated and, if memory serves, the focus was on innovation over research. Consequently, the drop in their research output is predictable.

Given my interest in nanotechnology and other emerging technologies, this popped out (from the report released April 10, 2018),

When it comes to research on most enabling and strategic technologies, however, Canada lags other countries. Bibliometric evidence suggests that, with the exception of selected subfields in Information and Communication Technologies (ICT) such as Medical Informatics and Personalized Medicine, Canada accounts for a relatively small share of the world’s research output for promising areas of technology development. This is particularly true for Biotechnology, Nanotechnology, and Materials science [emphasis mine]. Canada’s research impact, as reflected by citations, is also modest in these areas. Aside from Biotechnology, none of the other subfields in Enabling and Strategic Technologies has an ARC rank among the top five countries. Optoelectronics and photonics is the next highest ranked at 7th place, followed by Materials, and Nanoscience and Nanotechnology, both of which have a rank of 9th. Even in areas where Canadian researchers and institutions played a seminal role in early research (and retain a substantial research capacity), such as Artificial Intelligence and Regenerative Medicine, Canada has lost ground to other countries.

Arguably, our early efforts in artificial intelligence wouldn’t have garnered us much in the way of ranking and yet we managed some cutting edge work such as machine learning. I’m not suggesting the expert panel should have or could have found some way to measure these kinds of efforts but I’m wondering if there could have been some acknowledgement in the text of the report. I’m thinking a couple of sentences in a paragraph about the confounding nature of scientific research where areas that are ignored for years and even decades then become important (e.g., machine learning) but are not measured as part of scientific progress until after they are universally recognized.

Still, point taken about our diminishing returns in ’emerging’ technologies and sciences (from the report released April 10, 2018),

The impression that emerges from these data is sobering. With the exception of selected ICT subfields, such as Medical Informatics, bibliometric evidence does not suggest that Canada excels internationally in most of these research areas. In areas such as Nanotechnology and Materials science, Canada lags behind other countries in levels of research output and impact, and other countries are outpacing Canada’s publication growth in these areas — leading to declining shares of world publications. Even in research areas such as AI, where Canadian researchers and institutions played a foundational role, Canadian R&D activity is not keeping pace with that of other countries and some researchers trained in Canada have relocated to other countries (Section 4.4.1). There are isolated exceptions to these trends, but the aggregate data reviewed by this Panel suggest that Canada is not currently a world leader in research on most emerging technologies.

The Hedy Lamarr treatment

We have ‘good looks’ (arts and humanities) but not the kind of brains (physical sciences and engineering) that people admire (from the report released April 10, 2018),

Canada, relative to the world, specializes in subjects generally referred to as the
humanities and social sciences (plus health and the environment), and does
not specialize as much as others in areas traditionally referred to as the physical
sciences and engineering. Specifically, Canada has comparatively high levels
of research output in Psychology and Cognitive Sciences, Public Health and
Health Services, Philosophy and Theology, Earth and Environmental Sciences,
and Visual and Performing Arts. [emphases mine] It accounts for more than 5% of world researchin these fields. Conversely, Canada has lower research output than expected
in Chemistry, Physics and Astronomy, Enabling and Strategic Technologies,
Engineering, and Mathematics and Statistics. The comparatively low research
output in core areas of the natural sciences and engineering is concerning,
and could impair the flexibility of Canada’s research base, preventing research
institutions and researchers from being able to pivot to tomorrow’s emerging
research areas. [p. xix Print; p. 21 PDF]

Couldn’t they have used a more buoyant tone? After all, science was known as ‘natural philosophy’ up until the 19th century. As for visual and performing arts, let’s include poetry as a performing and literary art (both have been the case historically and cross-culturally) and let’s also note that one of the great physics texts, (De rerum natura by Lucretius) was a multi-volume poem (from Lucretius’ Wikipedia entry; Note: Links have been removed).

His poem De rerum natura (usually translated as “On the Nature of Things” or “On the Nature of the Universe”) transmits the ideas of Epicureanism, which includes Atomism [the concept of atoms forming materials] and psychology. Lucretius was the first writer to introduce Roman readers to Epicurean philosophy.[15] The poem, written in some 7,400 dactylic hexameters, is divided into six untitled books, and explores Epicurean physics through richly poetic language and metaphors. Lucretius presents the principles of atomism; the nature of the mind and soul; explanations of sensation and thought; the development of the world and its phenomena; and explains a variety of celestial and terrestrial phenomena. The universe described in the poem operates according to these physical principles, guided by fortuna, “chance”, and not the divine intervention of the traditional Roman deities.[16]

Should you need more proof that the arts might have something to contribute to physical sciences, there’s this in my March 7, 2018 posting,

It’s not often you see research that combines biologically inspired engineering and a molecular biophysicist with a professional animator who worked at Peter Jackson’s (Lord of the Rings film trilogy, etc.) Park Road Post film studio. An Oct. 18, 2017 news item on ScienceDaily describes the project,

Like many other scientists, Don Ingber, M.D., Ph.D., the Founding Director of the Wyss Institute, [emphasis mine] is concerned that non-scientists have become skeptical and even fearful of his field at a time when technology can offer solutions to many of the world’s greatest problems. “I feel that there’s a huge disconnect between science and the public because it’s depicted as rote memorization in schools, when by definition, if you can memorize it, it’s not science,” says Ingber, who is also the Judah Folkman Professor of Vascular Biology at Harvard Medical School and the Vascular Biology Program at Boston Children’s Hospital, and Professor of Bioengineering at the Harvard Paulson School of Engineering and Applied Sciences (SEAS). [emphasis mine] “Science is the pursuit of the unknown. We have a responsibility to reach out to the public and convey that excitement of exploration and discovery, and fortunately, the film industry is already great at doing that.”

“Not only is our physics-based simulation and animation system as good as other data-based modeling systems, it led to the new scientific insight [emphasis mine] that the limited motion of the dynein hinge focuses the energy released by ATP hydrolysis, which causes dynein’s shape change and drives microtubule sliding and axoneme motion,” says Ingber. “Additionally, while previous studies of dynein have revealed the molecule’s two different static conformations, our animation visually depicts one plausible way that the protein can transition between those shapes at atomic resolution, which is something that other simulations can’t do. The animation approach also allows us to visualize how rows of dyneins work in unison, like rowers pulling together in a boat, which is difficult using conventional scientific simulation approaches.”

It comes down to how we look at things. Yes, physical sciences and engineering are very important. If the report is to be believed we have a very highly educated population and according to PISA scores our students rank highly in mathematics, science, and reading skills. (For more information on Canada’s latest PISA scores from 2015 see this OECD page. As for PISA itself, it’s an OECD [Organization for Economic Cooperation and Development] programme where 15-year-old students from around the world are tested on their reading, mathematics, and science skills, you can get some information from my Oct. 9, 2013 posting.)

Is it really so bad that we choose to apply those skills in fields other than the physical sciences and engineering? It’s a little bit like Hedy Lamarr’s problem except instead of being judged for our looks and having our inventions dismissed, we’re being judged for not applying ourselves to physical sciences and engineering and having our work in other closely aligned fields dismissed as less important.

Canada’s Industrial R&D: an oft-told, very sad story

Bemoaning the state of Canada’s industrial research and development efforts has been a national pastime as long as I can remember. Here’s this from the report released April 10, 2018,

There has been a sustained erosion in Canada’s industrial R&D capacity and competitiveness. Canada ranks 33rd among leading countries on an index assessing the magnitude, intensity, and growth of industrial R&D expenditures. Although Canada is the 11th largest spender, its industrial R&D intensity (0.9%) is only half the OECD average and total spending is declining (−0.7%). Compared with G7 countries, the Canadian portfolio of R&D investment is more concentrated in industries that are intrinsically not as R&D intensive. Canada invests more heavily than the G7 average in oil and gas, forestry, machinery and equipment, and finance where R&D has been less central to business strategy than in many other industries. …  About 50% of Canada’s industrial R&D spending is in high-tech sectors (including industries such as ICT, aerospace, pharmaceuticals, and automotive) compared with the G7 average of 80%. Canadian Business Enterprise Expenditures on R&D (BERD) intensity is also below the OECD average in these sectors. In contrast, Canadian investment in low and medium-low tech sectors is substantially higher than the G7 average. Canada’s spending reflects both its long-standing industrial structure and patterns of economic activity.

R&D investment patterns in Canada appear to be evolving in response to global and domestic shifts. While small and medium-sized enterprises continue to perform a greater share of industrial R&D in Canada than in the United States, between 2009 and 2013, there was a shift in R&D from smaller to larger firms. Canada is an increasingly attractive place to conduct R&D. Investment by foreign-controlled firms in Canada has increased to more than 35% of total R&D investment, with the United States accounting for more than half of that. [emphasis mine]  Multinational enterprises seem to be increasingly locating some of their R&D operations outside their country of ownership, possibly to gain proximity to superior talent. Increasing foreign-controlled R&D, however, also could signal a long-term strategic loss of control over intellectual property (IP) developed in this country, ultimately undermining the government’s efforts to support high-growth firms as they scale up. [pp. xxii-xxiii Print; pp. 24-25 PDF]

Canada has been known as a ‘branch plant’ economy for decades. For anyone unfamiliar with the term, it means that companies from other countries come here, open up a branch and that’s how we get our jobs as we don’t have all that many large companies here. Increasingly, multinationals are locating R&D shops here.

While our small to medium size companies fund industrial R&D, it’s large companies (multinationals) which can afford long-term and serious investment in R&D. Luckily for companies from other countries, we have a well-educated population of people looking for jobs.

In 2017, we opened the door more widely so we can scoop up talented researchers and scientists from other countries, from a June 14, 2017 article by Beckie Smith for The PIE News,

Universities have welcomed the inclusion of the work permit exemption for academic stays of up to 120 days in the strategy, which also introduces expedited visa processing for some highly skilled professions.

Foreign researchers working on projects at a publicly funded degree-granting institution or affiliated research institution will be eligible for one 120-day stay in Canada every 12 months.

And universities will also be able to access a dedicated service channel that will support employers and provide guidance on visa applications for foreign talent.

The Global Skills Strategy, which came into force on June 12 [2017], aims to boost the Canadian economy by filling skills gaps with international talent.

As well as the short term work permit exemption, the Global Skills Strategy aims to make it easier for employers to recruit highly skilled workers in certain fields such as computer engineering.

“Employers that are making plans for job-creating investments in Canada will often need an experienced leader, dynamic researcher or an innovator with unique skills not readily available in Canada to make that investment happen,” said Ahmed Hussen, Minister of Immigration, Refugees and Citizenship.

“The Global Skills Strategy aims to give those employers confidence that when they need to hire from abroad, they’ll have faster, more reliable access to top talent.”

Coincidentally, Microsoft, Facebook, Google, etc. have announced, in 2017, new jobs and new offices in Canadian cities. There’s a also Chinese multinational telecom company Huawei Canada which has enjoyed success in Canada and continues to invest here (from a Jan. 19, 2018 article about security concerns by Matthew Braga for the Canadian Broadcasting Corporation (CBC) online news,

For the past decade, Chinese tech company Huawei has found no shortage of success in Canada. Its equipment is used in telecommunications infrastructure run by the country’s major carriers, and some have sold Huawei’s phones.

The company has struck up partnerships with Canadian universities, and say it is investing more than half a billion dollars in researching next generation cellular networks here. [emphasis mine]

While I’m not thrilled about using patents as an indicator of progress, this is interesting to note (from the report released April 10, 2018),

Canada produces about 1% of global patents, ranking 18th in the world. It lags further behind in trademark (34th) and design applications (34th). Despite relatively weak performance overall in patents, Canada excels in some technical fields such as Civil Engineering, Digital Communication, Other Special Machines, Computer Technology, and Telecommunications. [emphases mine] Canada is a net exporter of patents, which signals the R&D strength of some technology industries. It may also reflect increasing R&D investment by foreign-controlled firms. [emphasis mine] [p. xxiii Print; p. 25 PDF]

Getting back to my point, we don’t have large companies here. In fact, the dream for most of our high tech startups is to build up the company so it’s attractive to buyers, sell, and retire (hopefully before the age of 40). Strangely, the expert panel doesn’t seem to share my insight into this matter,

Canada’s combination of high performance in measures of research output and impact, and low performance on measures of industrial R&D investment and innovation (e.g., subpar productivity growth), continue to be viewed as a paradox, leading to the hypothesis that barriers are impeding the flow of Canada’s research achievements into commercial applications. The Panel’s analysis suggests the need for a more nuanced view. The process of transforming research into innovation and wealth creation is a complex multifaceted process, making it difficult to point to any definitive cause of Canada’s deficit in R&D investment and productivity growth. Based on the Panel’s interpretation of the evidence, Canada is a highly innovative nation, but significant barriers prevent the translation of innovation into wealth creation. The available evidence does point to a number of important contributing factors that are analyzed in this report. Figure 5 represents the relationships between R&D, innovation, and wealth creation.

The Panel concluded that many factors commonly identified as points of concern do not adequately explain the overall weakness in Canada’s innovation performance compared with other countries. [emphasis mine] Academia-business linkages appear relatively robust in quantitative terms given the extent of cross-sectoral R&D funding and increasing academia-industry partnerships, though the volume of academia-industry interactions does not indicate the nature or the quality of that interaction, nor the extent to which firms are capitalizing on the research conducted and the resulting IP. The educational system is high performing by international standards and there does not appear to be a widespread lack of researchers or STEM (science, technology, engineering, and mathematics) skills. IP policies differ across universities and are unlikely to explain a divergence in research commercialization activity between Canadian and U.S. institutions, though Canadian universities and governments could do more to help Canadian firms access university IP and compete in IP management and strategy. Venture capital availability in Canada has improved dramatically in recent years and is now competitive internationally, though still overshadowed by Silicon Valley. Technology start-ups and start-up ecosystems are also flourishing in many sectors and regions, demonstrating their ability to build on research advances to develop and deliver innovative products and services.

You’ll note there’s no mention of a cultural issue where start-ups are designed for sale as soon as possible and this isn’t new. Years ago, there was an accounting firm that published a series of historical maps (the last one I saw was in 2005) of technology companies in the Vancouver region. Technology companies were being developed and sold to large foreign companies from the 19th century to present day.

Part 2

Tracking artificial intelligence

Researchers at Stanford University have developed an index for measuring (tracking) the progress made by artificial intelligence (AI) according to a January 9, 2018 news item on phys.org (Note: Links have been removed),

Since the term “artificial intelligence” (AI) was first used in print in 1956, the one-time science fiction fantasy has progressed to the very real prospect of driverless cars, smartphones that recognize complex spoken commands and computers that see.

In an effort to track the progress of this emerging field, a Stanford-led group of leading AI thinkers called the AI100 has launched an index that will provide a comprehensive baseline on the state of artificial intelligence and measure technological progress in the same way the gross domestic product and the S&P 500 index track the U.S. economy and the broader stock market.

For anyone curious about the AI100 initiative, I have a description of it in my Sept. 27, 2016 post highlighting the group’s first report or you can keep on reading.

Getting back to the matter at hand, a December 21, 2017 Stanford University press release by Andrew Myers, which originated the news item, provides more detail about the AI index,

“The AI100 effort realized that in order to supplement its regular review of AI, a more continuous set of collected metrics would be incredibly useful,” said Russ Altman, a professor of bioengineering and the faculty director of AI100. “We were very happy to seed the AI Index, which will inform the AI100 as we move forward.”

The AI100 was set in motion three years ago when Eric Horvitz, a Stanford alumnus and former president of the Association for the Advancement of Artificial Intelligence, worked with his wife, Mary Horvitz, to define and endow the long-term study. Its first report, released in the fall of 2016, sought to anticipate the likely effects of AI in an urban environment in the year 2030.

Among the key findings in the new index are a dramatic increase in AI startups and investment as well as significant improvements in the technology’s ability to mimic human performance.

Baseline metrics

The AI Index tracks and measures at least 18 independent vectors in academia, industry, open-source software and public interest, plus technical assessments of progress toward what the authors call “human-level performance” in areas such as speech recognition, question-answering and computer vision – algorithms that can identify objects and activities in 2D images. Specific metrics in the index include evaluations of academic papers published, course enrollment, AI-related startups, job openings, search-term frequency and media mentions, among others.

“In many ways, we are flying blind in our discussions about artificial intelligence and lack the data we need to credibly evaluate activity,” said Yoav Shoham, professor emeritus of computer science.

“The goal of the AI Index is to provide a fact-based measuring stick against which we can chart progress and fuel a deeper conversation about the future of the field,” Shoham said.

Shoham conceived of the index and assembled a steering committee including Ray Perrault from SRI International, Erik Brynjolfsson of the Massachusetts Institute of Technology and Jack Clark from OpenAI. The committee subsequently hired Calvin LeGassick as project manager.

“The AI Index will succeed only if it becomes a community effort,” Shoham said.

Although the authors say the AI Index is the first index to track either scientific or technological progress, there are many other non-financial indexes that provide valuable insight into equally hard-to-quantify fields. Examples include the Social Progress Index, the Middle East peace index and the Bangladesh empowerment index, which measure factors as wide-ranging as nutrition, sanitation, workload, leisure time, public sentiment and even public speaking opportunities.

Intriguing findings

Among the findings of this inaugural index is that the number of active AI startups has increased 14-fold since 2000. Venture capital investment has increased six times in the same period. In academia, publishing in AI has increased a similarly impressive nine times in the last 20 years while course enrollment has soared. Enrollment in the introductory AI-related machine learning course at Stanford, for instance, has grown 45-fold in the last 30 years.

In technical metrics, image and speech recognition are both approaching, if not surpassing, human-level performance. The authors noted that AI systems have excelled in such real-world applications as object detection, the ability to understand and answer questions and classification of photographic images of skin cancer cells

Shoham noted that the report is still very U.S.-centric and will need a greater international presence as well as a greater diversity of voices. He said he also sees opportunities to fold in government and corporate investment in addition to the venture capital funds that are currently included.

In terms of human-level performance, the AI Index suggests that in some ways AI has already arrived. This is true in game-playing applications including chess, the Jeopardy! game show and, most recently, the game of Go. Nonetheless, the authors note that computers continue to lag considerably in the ability to generalize specific information into deeper meaning.

“AI has made truly amazing strides in the past decade,” Shoham said, “but computers still can’t exhibit the common sense or the general intelligence of even a 5-year-old.”

The AI Index was made possible by funding from AI100, Google, Microsoft and Toutiao. Data supporting the various metrics were provided by Elsevier, TrendKite, Indeed.com, Monster.com, the Google Trends Team, the Google Brain Team, Sand Hill Econometrics, VentureSource, Crunchbase, Electronic Frontier Foundation, EuroMatrix, Geoff Sutcliffe, Kevin Leyton-Brown and Holger Hoose.

You can find the AI Index here. They’re featuring their 2017 report but you can also find data (on the menu bar on the upper right side of your screen), along with a few provisos. I was curious as to whether any AI had been used to analyze the data and/or write the report. A very cursory look at the 2017 report did not answer that question. I’m fascinated by the failure to address what I think is an obvious question. It suggests that even very, very bright people can become blind and I suspect that’s why the group seems quite eager to get others involved, from the 2017 AI Index Report,

As the report’s limitations illustrate, the AI Index will always paint a partial picture. For this reason, we include subjective commentary from a cross-section of AI experts. This Expert Forum helps animate the story behind the data in the report and adds interpretation the report lacks.

Finally, where the experts’ dialogue ends, your opportunity to Get Involved begins [emphasis mine]. We will need the feedback and participation of a larger community to address the issues identified in this report, uncover issues we have omitted, and build a productive process for tracking activity and progress in Artificial Intelligence. (p. 8)

Unfortunately, it’s not clear how one becomes involved. Is there a forum or do you get in touch with one of the team leaders?

I wish them good luck with their project and imagine that these minor hiccups will be dealt with in near term.

Machine learning, neural networks, and knitting

In a recent (Tuesday, March 6, 2018) live stream ‘conversation’ (‘Science in Canada; Investing in Canadian Innovation’ now published on YouTube) between Canadian Prime Minister, Justin Trudeau, and US science communicator, Bill Nye, at the University of Ottawa, they discussed, amongst many other topics, what AI (artificial intelligence) can and can’t do. They seemed to agree that AI can’t be creative, i.e., write poetry, create works of art, make jokes, etc. A conclusion which is both (in my opinion) true and not true.

There are times when I think the joke may be on us (humans). Take for example this March 6, 2018 story by Alexis Madrigal for The Atlantic magazine (Note: Links have been removed),

SkyKnit: How an AI Took Over an Adult Knitting Community

Ribald knitters teamed up with a neural-network creator to generate new types of tentacled, cozy shapes.

Janelle Shane is a humorist [Note: She describes herself as a “Research Scientist in optics. Plays with neural networks. …” in her Twitter bio.] who creates and mines her material from neural networks, the form of machine learning that has come to dominate the field of artificial intelligence over the last half-decade.

Perhaps you’ve seen the candy-heart slogans she generated for Valentine’s Day: DEAR ME, MY MY, LOVE BOT, CUTE KISS, MY BEAR, and LOVE BUN.

Or her new paint-color names: Parp Green, Shy Bather, Farty Red, and Bull Cream.

Or her neural-net-generated Halloween costumes: Punk Tree, Disco Monster, Spartan Gandalf, Starfleet Shark, and A Masked Box.

Her latest project, still ongoing, pushes the joke into a new, physical realm. Prodded by a knitter on the knitting forum Ravelry, Shane trained a type of neural network on a series of over 500 sets of knitting instructions. Then, she generated new instructions, which members of the Ravelry community have actually attempted to knit.

“The knitting project has been a particularly fun one so far just because it ended up being a dialogue between this computer program and these knitters that went over my head in a lot of ways,” Shane told me. “The computer would spit out a whole bunch of instructions that I couldn’t read and the knitters would say, this is the funniest thing I’ve ever read.”

It appears that the project evolved,

The human-machine collaboration created configurations of yarn that you probably wouldn’t give to your in-laws for Christmas, but they were interesting. The user citikas was the first to post a try at one of the earliest patterns, “reverss shawl.” It was strange, but it did have some charisma.

Shane nicknamed the whole effort “Project Hilarious Disaster.” The community called it SkyKnit.

I’m not sure what’s meant by “community” as mentioned in the previous excerpt. Are we talking about humans only, AI only, or both humans and AI?

Here’s some of what underlies Skyknit (Note: Links have been removed),

The different networks all attempt to model the data they’ve been fed by tuning a vast, funky flowchart. After you’ve created a statistical model that describes your real data, you can also roll the dice and generate new, never-before-seen data of the same kind.

How this works—like, the math behind it—is very hard to visualize because values inside the model can have hundreds of dimensions and we are humble three-dimensional creatures moving through time. But as the neural-network enthusiast Robin Sloan puts it, “So what? It turns out imaginary spaces are useful even if you can’t, in fact, imagine them.”

Out of that ferment, a new kind of art has emerged. Its practitioners use neural networks not to attain practical results, but to see what’s lurking in the these vast, opaque systems. What did the machines learn about the world as they attempted to understand the data they’d been fed? Famously, Google released DeepDream, which produced trippy visualizations that also demonstrated how that type of neural network processed the textures and objects in its source imagery.

Madrigal’s article is well worth reading if you have the time. You can also supplement Madrigal’s piece with an August 9, 2017 article about Janelle Shane’s algorithmic experiments by Jacob Brogan for slate.com.

I found some SkyKnit examples on Ravelry including this one from the Dollybird Workshop,

© Chatelaine

SkyKnit fancy addite rifopshent
by SkyKnit
Published in
Dollybird Workshop
SkyKnit
Craft
Knitting
Category
Stitch pattern
Published
February 2018
Suggested yarn
Yarn weight
Fingering (14 wpi) ?
Gauge
24 stitches and 30 rows = 4 inches
in stockinette stitch
Needle size
US 4 – 3.5 mm

written-pattern

This pattern is available as a free Ravelry download

SkyKnit is a type of machine learning algorithm called an artificial neural network. Its creator, Janelle Shane of AIweirdness.com, gave it 88,000 lines of knitting instructions from Stitch-Maps.com and Ravelry, and it taught itself how to make new patterns. Join the discussion!

SkyKnit seems to have created something that has paralell columns, and is reversible. Perhaps a scarf?

Test-knitting & image courtesy of Chatelaine

Patterns may include notes from testknitters; yarn, needles, and gauge are totally at your discretion.

About the designer
SkyKnit’s favorites include lace, tentacles, and totally not the elimination of the human race.
For more information, see: http://aiweirdness.com/

Shane’s website, aiweirdness.com, is where she posts musings such as this (from a March 2, [?] 2018 posting), Note: A link has been removed,

If you’ve been on the internet today, you’ve probably interacted with a neural network. They’re a type of machine learning algorithm that’s used for everything from language translation to finance modeling. One of their specialties is image recognition. Several companies – including Google, Microsoft, IBM, and Facebook – have their own algorithms for labeling photos. But image recognition algorithms can make really bizarre mistakes.

image

Microsoft Azure’s computer vision API [application programming interface] added the above caption and tags. But there are no sheep in the image of above. None. I zoomed all the way in and inspected every speck.

….

I have become quite interested in Shane’s self descriptions such as this one from the aiweirdness.com website,

Portrait/Logo

About

I train neural networks, a type of machine learning algorithm, to write unintentional humor as they struggle to imitate human datasets. Well, I intend the humor. The neural networks are just doing their best to understand what’s going on. Currently located on the occupied land of the Arapahoe Nation.
https://wandering.shop/@janellecshane

As for the joke being on us, I can’t help remembering the Facebook bots that developed their own language (Facebotlish), and were featured in my June 30, 2017 posting, There’s a certain eerieness to it all, which seems an appropriate response in a year celebrating the 200th anniversary of Mary Shelley’s 1818 book, Frankenstein; or, the Modern Prometheus. I’m closing with a video clip from the 1931 movie,

Happy Weekend!

China is world leader in nanotechnology and in other fields too?

State of Chinese nanoscience/nanotechnology

China claims to be the world leader in the field in a white paper announced in an August 29, 2017 Springer Nature press release,

Springer Nature, the National Center for Nanoscience and Technology, China and the National Science Library of the Chinese Academy of Sciences (CAS) released in both Chinese and English a white paper entitled “Small Science in Big China: An overview of the state of Chinese nanoscience and technology” at NanoChina 2017, an international conference on nanoscience and technology held August 28 and 29 in Beijing. The white paper looks at the rapid growth of China’s nanoscience research into its current role as the world’s leader [emphasis mine], examines China’s strengths and challenges, and makes some suggestions for how its contribution to the field can continue to thrive.

The white paper points out that China has become a strong contributor to nanoscience research in the world, and is a powerhouse of nanotechnology R&D. Some of China’s basic research is leading the world. China’s applied nanoscience research and the industrialization of nanotechnologies have also begun to take shape. These achievements are largely due to China’s strong investment in nanoscience and technology. China’s nanoscience research is also moving from quantitative increase to quality improvement and innovation, with greater emphasis on the applications of nanotechnologies.

“China took an initial step into nanoscience research some twenty years ago, and has since grown its commitment at an unprecedented rate, as it has for scientific research as a whole. Such a growth is reflected both in research quantity and, importantly, in quality. Therefore, I regard nanoscience as a window through which to observe the development of Chinese science, and through which we could analyze how that rapid growth has happened. Further, the experience China has gained in developing nanoscience and related technologies is a valuable resource for the other countries and other fields of research to dig deep into and draw on,” said Arnout Jacobs, President, Greater China, Springer Nature.

The white paper explores at China’s research output relative to the rest of the world in terms of research paper output, research contribution contained in the Nano database, and finally patents, providing insight into China’s strengths and expertise in nano research. The white paper also presents the results of a survey of experts from the community discussing the outlook for and challenges to the future of China’s nanoscience research.

China nano research output: strong rise in quantity and quality

In 1997, around 13,000 nanoscience-related papers were published globally. By 2016, this number had risen to more than 154,000 nano-related research papers. This corresponds to a compound annual growth rate of 14% per annum, almost four times the growth in publications across all areas of research of 3.7%. Over the same period of time, the nano-related output from China grew from 820 papers in 1997 to over 52,000 papers in 2016, a compound annual growth rate of 24%.

China’s contribution to the global total has been growing steadily. In 1997, Chinese researchers co-authored just 6% of the nano-related papers contained in the Science Citation Index (SCI). By 2010, this grew to match the output of the United States. They now contribute over a third of the world’s total nanoscience output — almost twice that of the United States.

Additionally, China’s share of the most cited nanoscience papers has kept increasing year on year, with a compound annual growth rate of 22% — more than three times the global rate. It overtook the United States in 2014 and its contribution is now many times greater than that of any other country in the world, manifesting an impressive progression in both quantity and quality.

The rapid growth of nanoscience in China has been enabled by consistent and strong financial support from the Chinese government. As early as 1990, the State Science and Technology Committee, the predecessor of the Ministry of Science and Technology (MOST), launched the Climbing Up project on nanomaterial science. During the 1990s, the National Natural Science Foundation of China (NSFC) also funded nearly 1,000 small-scale projects in nanoscience. In the National Guideline on Medium- and Long-Term Program for Science and Technology Development (for 2006−2020) issued in early 2006 by the Chinese central government, nanoscience was identified as one of four areas of basic research and received the largest proportion of research budget out of the four areas. The brain boomerang, with more and more foreign-trained Chinese researchers returning from overseas, is another contributor to China’s rapid rise in nanoscience.

The white paper clarifies the role of Chinese institutions, including CAS, in driving China’s rise to become the world’s leader in nanoscience. Currently, CAS is the world’s largest producer of high impact nano research, contributing more than twice as many papers in the 1% most-cited nanoscience literature than its closest competitors. In addition to CAS, five other Chinese institutions are ranked among the global top 20 in terms of output of top cited 1% nanoscience papers — Tsinghua University, Fudan University, Zhejiang University, University of Science and Technology of China and Peking University.

Nano database reveals advantages and focus of China’s nano research

The Nano database (http://nano.nature.com) is a comprehensive platform that has been recently developed by Nature Research – part of Springer Nature – which contains nanoscience-related papers published in 167 peer-reviewed journals including Advanced Materials, Nano Letters, Nature, Science and more. Analysis of the Nano database of nanomaterial-containing articles published in top 30 journals during 2014–2016 shows that Chinese scientists explore a wide range of nanomaterials, the five most common of which are nanostructured materials, nanoparticles, nanosheets, nanodevices and nanoporous materials.

In terms of the research of applications, China has a clear leading edge in catalysis research, which is the most popular area of the country’s quality nanoscience papers. Chinese nano researchers also contributed significantly to nanomedicine and energy-related applications. China is relatively weaker in nanomaterials for electronics applications, compared to other research powerhouses, but robotics and lasers are emerging applications areas of nanoscience in China, and nanoscience papers addressing photonics and data storage applications also see strong growth in China. Over 80% of research from China listed in the database explicitly mentions applications of the nanostructures and nanomaterials described, notably higher than from most other leading nations such as the United States, Germany, the UK, Japan and France.

Nano also reveals the extent of China’s international collaborations in nano research. China has seen the percentage of its internationally collaborated papers increasing from 36% in 2014 to 44% in 2016. This level of international collaboration, similar to that of South Korea, is still much lower than that of the western countries, and the rate of growth is also not as fast as those in the United States, France and Germany.

The United States is China’s biggest international collaborator, contributing to 55% of China’s internationally collaborated papers on nanoscience that are included in the top 30 journals in the Nano database. Germany, Australia and Japan follow in a descending order as China’s collaborators on nano-related quality papers.

China’s patent output: topping the world, mostly applied domestically

Analysis of the Derwent Innovation Index (DII) database of Clarivate Analytics shows that China’s accumulative total number of patent applications for the past 20 years, amounting to 209,344 applications, or 45% of the global total, is more than twice as many as that of the United States, the second largest contributor to nano-related patents. China surpassed the United States and ranked the top in the world since 2008.

Five Chinese institutions, including the CAS, Zhejiang University, Tsinghua University, Hon Hai Precision Industry Co., Ltd. and Tianjin University can be found among the global top 10 institutional contributors to nano-related patent applications. CAS has been at the top of the global rankings since 2008, with a total of 11,218 patent applications for the past 20 years. Interestingly, outside of China, most of the other big institutional contributors among the top 10 are commercial enterprises, while in China, research or academic institutions are leading in patent applications.

However, the number of nano-related patents China applied overseas is still very low, accounting for only 2.61% of its total patent applications for the last 20 years cumulatively, whereas the proportion in the United States is nearly 50%. In some European countries, including the UK and France, more than 70% of patent applications are filed overseas.

China has high numbers of patent applications in several popular technical areas for nanotechnology use, and is strongest in patents for polymer compositions and macromolecular compounds. In comparison, nano-related patent applications in the United States, South Korea and Japan are mainly for electronics or semiconductor devices, with the United States leading the world in the cumulative number of patents for semiconductor devices.

Outlook, opportunities and challenges

The white paper highlights that the rapid rise of China’s research output and patent applications has painted a rosy picture for the development of Chinese nanoscience, and in both the traditionally strong subjects and newly emerging areas, Chinese nanoscience shows great potential.

Several interviewed experts in the survey identify catalysis and catalytic nanomaterials as the most promising nanoscience area for China. The use of nanotechnology in the energy and medical sectors was also considered very promising.

Some of the interviewed experts commented that the industrial impact of China’s nanotechnology is limited and there is still a gap between nanoscience research and the industrialization of nanotechnologies. Therefore, they recommended that the government invest more in applied research to drive the translation of nanoscience research and find ways to encourage enterprises to invest more in R&D.

As more and more young scientists enter the field, the competition for research funding is becoming more intense. However, this increasing competition for funding was not found to concern most interviewed young scientists, rather, they emphasized that the soft environment is more important. They recommended establishing channels that allow the suggestions or creative ideas of the young to be heard. Also, some interviewed young researchers commented that they felt that the current evaluation system was geared towards past achievements or favoured overseas experience, and recommended the development of an improved talent selection mechanism to ensure a sustainable growth of China’s nanoscience.

I have taken a look at the white paper and found it to be well written. It also provides a brief but thorough history of nanotechnology/nanoscience even adding a bit of historical information that was new to me. As for the rest of the white paper, it relies on bibliometrics (number of published papers and number of citations) and number of patents filed to lay the groundwork for claiming Chinese leadership in nanotechnology. As I’ve stated many times before, these are problematic measures but as far as I can determine they are almost the only ones we have. Frankly, as a Canadian, it doesn’t much matter to me since Canada no matter how you slice or dice it is always in a lower tier relative to science leadership in major fields. It’s the Americans who might feel inclined to debate leadership with regard to nanotechnology and other major fields and I leave it to to US commentators to take up the cudgels should they be inclined. The big bonuses here are the history, the glimpse into the Chinese perspective on the field of nanotechnology/nanoscience, and the analysis of weaknesses and strengths.

Coming up fast on Google and Amazon

A November 16, 2017 article by Christina Bonnington for Slate explores the possibility that a Chinese tech giant, Baidu,  will provide Google and Amazon serious competition in their quests to dominate world markets (Note: Links have been removed,

raven_h
The company took a playful approach to the form—but it has functional reasons for the design, too. Baidu

 

One of the most interesting companies in tech right now isn’t based in Palo Alto, or San Francisco, or Seattle. Baidu, a Chinese company with headquarters in Beijing, is taking on America’s biggest and most innovative tech titans—with style.

Baidu, a titan in its own right, leapt onto the scene as a competitor to Google in the search engine space. Since then, the company, largely underappreciated here in the U.S., has focused on beefing up its artificial intelligence efforts. Former AI chief Andrew Ng, upon leaving the company in March, credited Baidu’s CEO Robin Li on being one of the first technology leaders to fully appreciate the value of deep learning. Baidu now has a 1,300 person AI group, and that investment in AI has helped the company catch up to older, more established companies like Google and Amazon—both in emerging spaces, such as autonomous vehicles, and in consumer tech, as its latest announcement shows.

On Thursday [November 16, 2017], Baidu debuted its entrants to the popular virtual assistant space: a connected speaker and two robots. Baidu aims for the speaker to compete against options such as Amazon’s Echo line, Google Home, and Apple HomePod. Inside, the $256 device will utilize Baidu’s DuerOS conversational artificial intelligence platform, which is already used in more than 100 different smart home brands’ products. DuerOS will let you use your voice to do things like ask the speaker for information, play music, or hail a cab. Called the Raven H, the speaker includes high-end audio components from Tymphany and a unique design jointly created by acquired startup Raven Tech and Swedish consumer electronics company Teenage Engineering.

While the focus is on exciting new technology products from Baidu, the subtext, such as it is, suggests US companies had best keep an eye on its Chinese competitor(s).

Dutch/Chinese partnership to produce nanoparticles at the touch of a button

Now back to China and nanotechnology leadership and the production of nanoparticles. This announcement was made in a November 17, 2017 news item on Azonano,

Delft University of Technology [Netherlands] spin-off VSPARTICLE enters the booming Chinese market with a radical technology that allows researchers to produce nanoparticles at the push of a button. VSPARTICLE’s nanoparticle generator uses atoms, the worlds’ smallest building blocks, to provide a controllable source of nanoparticles. The start-up from Delft signed a distribution agreement with Bio-Sun to make their VSP-G1 nanoparticle generator available in China.

A November 16, 2017 VSPARTICLE press release, which originated the news item,

“We are honoured to cooperate with VSPARTICLE and bring the innovative VSP-G1 nanoparticle generator into the Chinese market. The VSP-G1 will create new possibilities for researchers in catalysis, aerosol, healthcare and electronics,” says Yinghui Cai, CEO of Bio-Sun.

With an exponential growth in nanoparticle research in the last decade, China is one of the leading countries in the field of nanotechnology and its applications. Vincent Laban, CFO of VSPARTICLE, explains: “Due to its immense investments in IOT, sensors, semiconductor technology, renewable energy and healthcare applications, China will eventually become one of our biggest markets. The collaboration with Bio-Sun offers a valuable opportunity to enter the Chinese market at exactly the right time.”

NANOPARTICLES ARE THE BUILDING BLOCKS OF THE FUTURE

Increasingly, scientists are focusing on nanoparticles as a key technology in enabling the transition to a sustainable future. Nanoparticles are used to make new types of sensors and smart electronics; provide new imaging and treatment possibilities in healthcare; and reduce harmful waste in chemical processes.

CURRENT RESEARCH TOOLKIT LACKS A FAST WAY FOR MAKING SPECIFIC BUILDING BLOCKS

With the latest tools in nanotechnology, researchers are exploring the possibilities of building novel materials. This is, however, a trial-and-error method. Getting the right nanoparticles often is a slow struggle, as most production methods take a substantial amount of effort and time to develop.

VSPARTICLE’S VSP-G1 NANOPARTICLE GENERATOR

With the VSP-G1 nanoparticle generator, VSPARTICLE makes the production of nanoparticles as easy as pushing a button. . Easy and fast iterations enable researchers to fast forward their research cycle, and verify their hypotheses.

VSPARTICLE

Born out of the research labs of Delft University of Technology, with over 20 years of experience in the synthesis of aerosol, VSPARTICLE believes there is a whole new world of possibilities and materials at the nanoscale. The company was founded in 2014 and has an international sales network in Europe, Japan and China.

BIO-SUN

Bio-Sun was founded in Beijing in 2010 and is a leader in promoting nanotechnology and biotechnology instruments in China. It serves many renowned customers in life science, drug discovery and material science. Bio-Sun has four branch offices in Qingdao, Shanghai, Guangzhou and Wuhan City, and a nationwide sale network.

That’s all folks!

Alberta adds a newish quantum nanotechnology research hub to the Canada’s quantum computing research scene

One of the winners in Canada’s 2017 federal budget announcement of the Pan-Canadian Artificial Intelligence Strategy was Edmonton, Alberta. It’s a fact which sometimes goes unnoticed while Canadians marvel at the wonderfulness found in Toronto and Montréal where it seems new initiatives and monies are being announced on a weekly basis (I exaggerate) for their AI (artificial intelligence) efforts.

Alberta’s quantum nanotechnology hub (graduate programme)

Intriguingly, it seems that Edmonton has higher aims than (an almost unnoticed) leadership in AI. Physicists at the University of Alberta have announced hopes to be just as successful as their AI brethren in a Nov. 27, 2017 article by Juris Graney for the Edmonton Journal,

Physicists at the University of Alberta [U of A] are hoping to emulate the success of their artificial intelligence studying counterparts in establishing the city and the province as the nucleus of quantum nanotechnology research in Canada and North America.

Google’s artificial intelligence research division DeepMind announced in July [2017] it had chosen Edmonton as its first international AI research lab, based on a long-running partnership with the U of A’s 10-person AI lab.

Retaining the brightest minds in the AI and machine-learning fields while enticing a global tech leader to Alberta was heralded as a coup for the province and the university.

It is something U of A physics professor John Davis believes the university’s new graduate program, Quanta, can help achieve in the world of quantum nanotechnology.

The field of quantum mechanics had long been a realm of theoretical science based on the theory that atomic and subatomic material like photons or electrons behave both as particles and waves.

“When you get right down to it, everything has both behaviours (particle and wave) and we can pick and choose certain scenarios which one of those properties we want to use,” he said.

But, Davis said, physicists and scientists are “now at the point where we understand quantum physics and are developing quantum technology to take to the marketplace.”

“Quantum computing used to be realm of science fiction, but now we’ve figured it out, it’s now a matter of engineering,” he said.

Quantum computing labs are being bought by large tech companies such as Google, IBM and Microsoft because they realize they are only a few years away from having this power, he said.

Those making the groundbreaking developments may want to commercialize their finds and take the technology to market and that is where Quanta comes in.

East vs. West—Again?

Ivan Semeniuk in his article, Quantum Supremacy, ignores any quantum research effort not located in either Waterloo, Ontario or metro Vancouver, British Columbia to describe a struggle between the East and the West (a standard Canadian trope). From Semeniuk’s Oct. 17, 2017 quantum article [link follows the excerpts] for the Globe and Mail’s October 2017 issue of the Report on Business (ROB),

 Lazaridis [Mike], of course, has experienced lost advantage first-hand. As co-founder and former co-CEO of Research in Motion (RIM, now called Blackberry), he made the smartphone an indispensable feature of the modern world, only to watch rivals such as Apple and Samsung wrest away Blackberry’s dominance. Now, at 56, he is engaged in a high-stakes race that will determine who will lead the next technology revolution. In the rolling heartland of southwestern Ontario, he is laying the foundation for what he envisions as a new Silicon Valley—a commercial hub based on the promise of quantum technology.

Semeniuk skips over the story of how Blackberry lost its advantage. I came onto that story late in the game when Blackberry was already in serious trouble due to a failure to recognize that the field they helped to create was moving in a new direction. If memory serves, they were trying to keep their technology wholly proprietary which meant that developers couldn’t easily create apps to extend the phone’s features. Blackberry also fought a legal battle in the US with a patent troll draining company resources and energy in proved to be a futile effort.

Since then Lazaridis has invested heavily in quantum research. He gave the University of Waterloo a serious chunk of money as they named their Quantum Nano Centre (QNC) after him and his wife, Ophelia (you can read all about it in my Sept. 25, 2012 posting about the then new centre). The best details for Lazaridis’ investments in Canada’s quantum technology are to be found on the Quantum Valley Investments, About QVI, History webpage,

History-bannerHistory has repeatedly demonstrated the power of research in physics to transform society.  As a student of history and a believer in the power of physics, Mike Lazaridis set out in 2000 to make real his bold vision to establish the Region of Waterloo as a world leading centre for physics research.  That is, a place where the best researchers in the world would come to do cutting-edge research and to collaborate with each other and in so doing, achieve transformative discoveries that would lead to the commercialization of breakthrough  technologies.

Establishing a World Class Centre in Quantum Research:

The first step in this regard was the establishment of the Perimeter Institute for Theoretical Physics.  Perimeter was established in 2000 as an independent theoretical physics research institute.  Mike started Perimeter with an initial pledge of $100 million (which at the time was approximately one third of his net worth).  Since that time, Mike and his family have donated a total of more than $170 million to the Perimeter Institute.  In addition to this unprecedented monetary support, Mike also devotes his time and influence to help lead and support the organization in everything from the raising of funds with government and private donors to helping to attract the top researchers from around the globe to it.  Mike’s efforts helped Perimeter achieve and grow its position as one of a handful of leading centres globally for theoretical research in fundamental physics.

Stephen HawkingPerimeter is located in a Governor-General award winning designed building in Waterloo.  Success in recruiting and resulting space requirements led to an expansion of the Perimeter facility.  A uniquely designed addition, which has been described as space-ship-like, was opened in 2011 as the Stephen Hawking Centre in recognition of one of the most famous physicists alive today who holds the position of Distinguished Visiting Research Chair at Perimeter and is a strong friend and supporter of the organization.

Recognizing the need for collaboration between theorists and experimentalists, in 2002, Mike applied his passion and his financial resources toward the establishment of The Institute for Quantum Computing at the University of Waterloo.  IQC was established as an experimental research institute focusing on quantum information.  Mike established IQC with an initial donation of $33.3 million.  Since that time, Mike and his family have donated a total of more than $120 million to the University of Waterloo for IQC and other related science initiatives.  As in the case of the Perimeter Institute, Mike devotes considerable time and influence to help lead and support IQC in fundraising and recruiting efforts.  Mike’s efforts have helped IQC become one of the top experimental physics research institutes in the world.

Quantum ComputingMike and Doug Fregin have been close friends since grade 5.  They are also co-founders of BlackBerry (formerly Research In Motion Limited).  Doug shares Mike’s passion for physics and supported Mike’s efforts at the Perimeter Institute with an initial gift of $10 million.  Since that time Doug has donated a total of $30 million to Perimeter Institute.  Separately, Doug helped establish the Waterloo Institute for Nanotechnology at the University of Waterloo with total gifts for $29 million.  As suggested by its name, WIN is devoted to research in the area of nanotechnology.  It has established as an area of primary focus the intersection of nanotechnology and quantum physics.

With a donation of $50 million from Mike which was matched by both the Government of Canada and the province of Ontario as well as a donation of $10 million from Doug, the University of Waterloo built the Mike & Ophelia Lazaridis Quantum-Nano Centre, a state of the art laboratory located on the main campus of the University of Waterloo that rivals the best facilities in the world.  QNC was opened in September 2012 and houses researchers from both IQC and WIN.

Leading the Establishment of Commercialization Culture for Quantum Technologies in Canada:

In the Research LabFor many years, theorists have been able to demonstrate the transformative powers of quantum mechanics on paper.  That said, converting these theories to experimentally demonstrable discoveries has, putting it mildly, been a challenge.  Many naysayers have suggested that achieving these discoveries was not possible and even the believers suggested that it could likely take decades to achieve these discoveries.  Recently, a buzz has been developing globally as experimentalists have been able to achieve demonstrable success with respect to Quantum Information based discoveries.  Local experimentalists are very much playing a leading role in this regard.  It is believed by many that breakthrough discoveries that will lead to commercialization opportunities may be achieved in the next few years and certainly within the next decade.

Recognizing the unique challenges for the commercialization of quantum technologies (including risk associated with uncertainty of success, complexity of the underlying science and high capital / equipment costs) Mike and Doug have chosen to once again lead by example.  The Quantum Valley Investment Fund will provide commercialization funding, expertise and support for researchers that develop breakthroughs in Quantum Information Science that can reasonably lead to new commercializable technologies and applications.  Their goal in establishing this Fund is to lead in the development of a commercialization infrastructure and culture for Quantum discoveries in Canada and thereby enable such discoveries to remain here.

Semeniuk goes on to set the stage for Waterloo/Lazaridis vs. Vancouver (from Semeniuk’s 2017 ROB article),

… as happened with Blackberry, the world is once again catching up. While Canada’s funding of quantum technology ranks among the top five in the world, the European Union, China, and the US are all accelerating their investments in the field. Tech giants such as Google [also known as Alphabet], Microsoft and IBM are ramping up programs to develop companies and other technologies based on quantum principles. Meanwhile, even as Lazaridis works to establish Waterloo as the country’s quantum hub, a Vancouver-area company has emerged to challenge that claim. The two camps—one methodically focused on the long game, the other keen to stake an early commercial lead—have sparked an East-West rivalry that many observers of the Canadian quantum scene are at a loss to explain.

Is it possible that some of the rivalry might be due to an influential individual who has invested heavily in a ‘quantum valley’ and has a history of trying to ‘own’ a technology?

Getting back to D-Wave Systems, the Vancouver company, I have written about them a number of times (particularly in 2015; for the full list: input D-Wave into the blog search engine). This June 26, 2015 posting includes a reference to an article in The Economist magazine about D-Wave’s commercial opportunities while the bulk of the posting is focused on a technical breakthrough.

Semeniuk offers an overview of the D-Wave Systems story,

D-Wave was born in 1999, the same year Lazaridis began to fund quantum science in Waterloo. From the start, D-Wave had a more immediate goal: to develop a new computer technology to bring to market. “We didn’t have money or facilities,” says Geordie Rose, a physics PhD who co0founded the company and served in various executive roles. …

The group soon concluded that the kind of machine most scientists were pursing based on so-called gate-model architecture was decades away from being realized—if ever. …

Instead, D-Wave pursued another idea, based on a principle dubbed “quantum annealing.” This approach seemed more likely to produce a working system, even if the application that would run on it were more limited. “The only thing we cared about was building the machine,” says Rose. “Nobody else was trying to solve the same problem.”

D-Wave debuted its first prototype at an event in California in February 2007 running it through a few basic problems such as solving a Sudoku puzzle and finding the optimal seating plan for a wedding reception. … “They just assumed we were hucksters,” says Hilton [Jeremy Hilton, D.Wave senior vice-president of systems]. Federico Spedalieri, a computer scientist at the University of Southern California’s [USC} Information Sciences Institute who has worked with D-Wave’s system, says the limited information the company provided about the machine’s operation provoked outright hostility. “I think that played against them a lot in the following years,” he says.

It seems Lazaridis is not the only one who likes to hold company information tightly.

Back to Semeniuk and D-Wave,

Today [October 2017], the Los Alamos National Laboratory owns a D-Wave machine, which costs about $15million. Others pay to access D-Wave systems remotely. This year , for example, Volkswagen fed data from thousands of Beijing taxis into a machine located in Burnaby [one of the municipalities that make up metro Vancouver] to study ways to optimize traffic flow.

But the application for which D-Wave has the hights hope is artificial intelligence. Any AI program hings on the on the “training” through which a computer acquires automated competence, and the 2000Q [a D-Wave computer] appears well suited to this task. …

Yet, for all the buzz D-Wave has generated, with several research teams outside Canada investigating its quantum annealing approach, the company has elicited little interest from the Waterloo hub. As a result, what might seem like a natural development—the Institute for Quantum Computing acquiring access to a D-Wave machine to explore and potentially improve its value—has not occurred. …

I am particularly interested in this comment as it concerns public funding (from Semeniuk’s article),

Vern Brownell, a former Goldman Sachs executive who became CEO of D-Wave in 2009, calls the lack of collaboration with Waterloo’s research community “ridiculous,” adding that his company’s efforts to establish closer ties have proven futile, “I’ll be blunt: I don’t think our relationship is good enough,” he says. Brownell also point out that, while  hundreds of millions in public funds have flowed into Waterloo’s ecosystem, little funding is available for  Canadian scientists wishing to make the most of D-Wave’s hardware—despite the fact that it remains unclear which core quantum technology will prove the most profitable.

There’s a lot more to Semeniuk’s article but this is the last excerpt,

The world isn’t waiting for Canada’s quantum rivals to forge a united front. Google, Microsoft, IBM, and Intel are racing to develop a gate-model quantum computer—the sector’s ultimate goal. (Google’s researchers have said they will unveil a significant development early next year.) With the U.K., Australia and Japan pouring money into quantum, Canada, an early leader, is under pressure to keep up. The federal government is currently developing  a strategy for supporting the country’s evolving quantum sector and, ultimately, getting a return on its approximately $1-billion investment over the past decade [emphasis mine].

I wonder where the “approximately $1-billion … ” figure came from. I ask because some years ago MP Peter Julian asked the government for information about how much Canadian federal money had been invested in nanotechnology. The government replied with sheets of paper (a pile approximately 2 inches high) that had funding disbursements from various ministries. Each ministry had its own method with different categories for listing disbursements and the titles for the research projects were not necessarily informative for anyone outside a narrow specialty. (Peter Julian’s assistant had kindly sent me a copy of the response they had received.) The bottom line is that it would have been close to impossible to determine the amount of federal funding devoted to nanotechnology using that data. So, where did the $1-billion figure come from?

In any event, it will be interesting to see how the Council of Canadian Academies assesses the ‘quantum’ situation in its more academically inclined, “The State of Science and Technology and Industrial Research and Development in Canada,” when it’s released later this year (2018).

Finally, you can find Semeniuk’s October 2017 article here but be aware it’s behind a paywall.

Whither we goest?

Despite any doubts one might have about Lazaridis’ approach to research and technology, his tremendous investment and support cannot be denied. Without him, Canada’s quantum research efforts would be substantially less significant. As for the ‘cowboys’ in Vancouver, it takes a certain temperament to found a start-up company and it seems the D-Wave folks have more in common with Lazaridis than they might like to admit. As for the Quanta graduate  programme, it’s early days yet and no one should ever count out Alberta.

Meanwhile, one can continue to hope that a more thoughtful approach to regional collaboration will be adopted so Canada can continue to blaze trails in the field of quantum research.

A customized cruise experience with wearable technology (and decreased personal agency?)

The days when you went cruising to ‘get away from it all’ seem to have passed (if they ever really existed) with the introduction of wearable technology that will register your every preference and make life easier according to Cliff Kuang’s Oct. 19, 2017 article for Fast Company,

This month [October 2017], the 141,000-ton Regal Princess will push out to sea after a nine-figure revamp of mind-boggling scale. Passengers won’t be greeted by new restaurants, swimming pools, or onboard activities, but will instead step into a future augured by the likes of Netflix and Uber, where nearly everything is on demand and personally tailored. An ambitious new customization platform has been woven into the ship’s 19 passenger decks: some 7,000 onboard sensors and 4,000 “guest portals” (door-access panels and touch-screen TVs), all of them connected by 75 miles of internal cabling. As the Carnival-owned ship cruises to Nassau, Bahamas, and Grand Turk, its 3,500 passengers will have the option of carrying a quarter-size device, called the Ocean Medallion, which can be slipped into a pocket or worn on the wrist and is synced with a companion app.

The platform will provide a new level of service for passengers; the onboard sensors record their tastes and respond to their movements, and the app guides them around the ship and toward activities aligned with their preferences. Carnival plans to roll out the platform to another seven ships by January 2019. Eventually, the Ocean Medallion could be opening doors, ordering drinks, and scheduling activities for passengers on all 102 of Carnival’s vessels across 10 cruise lines, from the mass-market Princess ships to the legendary ocean liners of Cunard.

Kuang goes on to explain the reasoning behind this innovation,

The Ocean Medallion is Carnival’s attempt to address a problem that’s become increasingly vexing to the $35.5 billion cruise industry. Driven by economics, ships have exploded in size: In 1996, Carnival Destiny was the world’s largest cruise ship, carrying 2,600 passengers. Today, Royal Caribbean’s MS Harmony of the Seas carries up to 6,780 passengers and 2,300 crew. Larger ships expend less fuel per passenger; the money saved can then go to adding more amenities—which, in turn, are geared to attracting as many types of people as possible. Today on a typical ship you can do practically anything—from attending violin concertos to bungee jumping. And that’s just onboard. Most of a cruise is spent in port, where each day there are dozens of experiences available. This avalanche of choice can bury a passenger. It has also made personalized service harder to deliver. …

Kuang also wrote this brief description of how the technology works from the passenger’s perspective in an Oct. 19, 2017 item for Fast Company,

1. Pre-trip

On the web or on the app, you can book experiences, log your tastes and interests, and line up your days. That data powers the recommendations you’ll see. The Ocean Medallion arrives by mail and becomes the key to ship access.

2. Stateroom

When you draw near, your cabin-room door unlocks without swiping. The room’s unique 43-inch TV, which doubles as a touch screen, offers a range of Carnival’s bespoke travel shows. Whatever you watch is fed into your excursion suggestions.

3. Food

When you order something, sensors detect where you are, allowing your server to find you. Your allergies and preferences are also tracked, and shape the choices you’re offered. In all, the back-end data has 45,000 allergens tagged and manages 250,000 drink combinations.

4. Activities

The right algorithms can go beyond suggesting wines based on previous orders. Carnival is creating a massive semantic database, so if you like pricey reds, you’re more apt to be guided to a violin concerto than a limbo competition. Your onboard choices—the casino, the gym, the pool—inform your excursion recommendations.

In Kuang’s Oct. 19, 2017 article he notes that the cruise ship line is putting a lot of effort into retraining their staff and emphasizing the ‘soft’ skills that aren’t going to be found in this iteration of the technology. No mention is made of whether or not there will be reductions in the number of staff members on this cruise ship nor is the possibility that ‘soft’ skills may in the future be incorporated into this technological marvel.

Personalization/customization is increasingly everywhere

How do you feel about customized news feeds? As it turns out, this is not a rhetorical question as Adrienne LaFrance notes in her Oct. 19, 2017 article for The Atlantic (Note: Links have been removed),

Today, a Google search for news runs through the same algorithmic filtration system as any other Google search: A person’s individual search history, geographic location, and other demographic information affects what Google shows you. Exactly how your search results differ from any other person’s is a mystery, however. Not even the computer scientists who developed the algorithm could precisely reverse engineer it, given the fact that the same result can be achieved through numerous paths, and that ranking factors—deciding which results show up first—are constantly changing, as are the algorithms themselves.

We now get our news in real time, on demand, tailored to our interests, across multiple platforms, without knowing just how much is actually personalized. It was technology companies like Google and Facebook, not traditional newsrooms, that made it so. But news organizations are increasingly betting that offering personalized content can help them draw audiences to their sites—and keep them coming back.

Personalization extends beyond how and where news organizations meet their readers. Already, smartphone users can subscribe to push notifications for the specific coverage areas that interest them. On Facebook, users can decide—to some extent—which organizations’ stories they would like to appear in their news feeds. At the same time, devices and platforms that use machine learning to get to know their users will increasingly play a role in shaping ultra-personalized news products. Meanwhile, voice-activated artificially intelligent devices, such as Google Home and Amazon Echo, are poised to redefine the relationship between news consumers and the news [emphasis mine].

While news personalization can help people manage information overload by making individuals’ news diets unique, it also threatens to incite filter bubbles and, in turn, bias [emphasis mine]. This “creates a bit of an echo chamber,” says Judith Donath, author of The Social Machine: Designs for Living Online and a researcher affiliated with Harvard University ’s Berkman Klein Center for Internet and Society. “You get news that is designed to be palatable to you. It feeds into people’s appetite of expecting the news to be entertaining … [and] the desire to have news that’s reinforcing your beliefs, as opposed to teaching you about what’s happening in the world and helping you predict the future better.”

Still, algorithms have a place in responsible journalism. “An algorithm actually is the modern editorial tool,” says Tamar Charney, the managing editor of NPR One, the organization’s customizable mobile-listening app. A handcrafted hub for audio content from both local and national programs as well as podcasts from sources other than NPR, NPR One employs an algorithm to help populate users’ streams with content that is likely to interest them. But Charney assures there’s still a human hand involved: “The whole editorial vision of NPR One was to take the best of what humans do and take the best of what algorithms do and marry them together.” [emphasis mine]

The skimming and diving Charney describes sounds almost exactly like how Apple and Google approach their distributed-content platforms. With Apple News, users can decide which outlets and topics they are most interested in seeing, with Siri offering suggestions as the algorithm gets better at understanding your preferences. Siri now has have help from Safari. The personal assistant can now detect browser history and suggest news items based on what someone’s been looking at—for example, if someone is searching Safari for Reykjavík-related travel information, they will then see Iceland-related news on Apple News. But the For You view of Apple News isn’t 100 percent customizable, as it still spotlights top stories of the day, and trending stories that are popular with other users, alongside those curated just for you.

Similarly, with Google’s latest update to Google News, readers can scan fixed headlines, customize sidebars on the page to their core interests and location—and, of course, search. The latest redesign of Google News makes it look newsier than ever, and adds to many of the personalization features Google first introduced in 2010. There’s also a place where you can preprogram your own interests into the algorithm.

Google says this isn’t an attempt to supplant news organizations, nor is it inspired by them. The design is rather an embodiment of Google’s original ethos, the product manager for Google News Anand Paka says: “Just due to the deluge of information, users do want ways to control information overload. In other words, why should I read the news that I don’t care about?” [emphasis mine]

Meanwhile, in May [2017?], Google briefly tested a personalized search filter that would dip into its trove of data about users with personal Google and Gmail accounts and include results exclusively from their emails, photos, calendar items, and other personal data related to their query. [emphasis mine] The “personal” tab was supposedly “just an experiment,” a Google spokesperson said, and the option was temporarily removed, but seems to have rolled back out for many users as of August [2017?].

Now, Google, in seeking to settle a class-action lawsuit alleging that scanning emails to offer targeted ads amounts to illegal wiretapping, is promising that for the next three years it won’t use the content of its users’ emails to serve up targeted ads in Gmail. The move, which will go into effect at an unspecified date, doesn’t mean users won’t see ads, however. Google will continue to collect data from users’ search histories, YouTube, and Chrome browsing habits, and other activity.

The fear that personalization will encourage filter bubbles by narrowing the selection of stories is a valid one, especially considering that the average internet user or news consumer might not even be aware of such efforts. Elia Powers, an assistant professor of journalism and news media at Towson University in Maryland, studied the awareness of news personalization among students after he noticed those in his own classes didn’t seem to realize the extent to which Facebook and Google customized users’ results. “My sense is that they didn’t really understand … the role that people that were curating the algorithms [had], how influential that was. And they also didn’t understand that they could play a pretty active role on Facebook in telling Facebook what kinds of news they want them to show and how to prioritize [content] on Google,” he says.

The results of Powers’s study, which was published in Digital Journalism in February [2017], showed that the majority of students had no idea that algorithms were filtering the news content they saw on Facebook and Google. When asked if Facebook shows every news item, posted by organizations or people, in a users’ newsfeed, only 24 percent of those surveyed were aware that Facebook prioritizes certain posts and hides others. Similarly, only a quarter of respondents said Google search results would be different for two different people entering the same search terms at the same time. [emphasis mine; Note: Respondents in this study were students.]

This, of course, has implications beyond the classroom, says Powers: “People as news consumers need to be aware of what decisions are being made [for them], before they even open their news sites, by algorithms and the people behind them, and also be able to understand how they can counter the effects or maybe even turn off personalization or make tweaks to their feeds or their news sites so they take a more active role in actually seeing what they want to see in their feeds.”

On Google and Facebook, the algorithm that determines what you see is invisible. With voice-activated assistants, the algorithm suddenly has a persona. “We are being trained to have a relationship with the AI,” says Amy Webb, founder of the Future Today Institute and an adjunct professor at New York University Stern School of Business. “This is so much more catastrophically horrible for news organizations than the internet. At least with the internet, I have options. The voice ecosystem is not built that way. It’s being built so I just get the information I need in a pleasing way.”

LaFrance’s article is thoughtful and well worth reading in its entirety. Now, onto some commentary.

Loss of personal agency

I have been concerned for some time about the increasingly dull results I get from a Google search and while I realize the company has been gathering information about me via my searches , supposedly in service of giving me better searches, I had no idea how deeply the company can mine for personal data. It makes me wonder what would happen if Google and Facebook attempted a merger.

More cogently, I rather resent the search engines and artificial intelligence agents (e.g. Facebook bots) which have usurped my role as the arbiter of what interests me, in short, my increasing loss of personal agency.

I’m also deeply suspicious of what these companies are going to do with my data. Will it be used to manipulate me in some way? Presumably, the data will be sold and used for some purpose. In the US, they have married electoral data with consumer data as Brent Bambury notes in an Oct. 13, 2017 article for his CBC (Canadian Broadcasting Corporation) Radio show,

How much of your personal information circulates in the free-market ether of metadata? It could be more than you imagine, and it might be enough to let others change the way you vote.

A data firm that specializes in creating psychological profiles of voters claims to have up to 5,000 data points on 220 million Americans. Cambridge Analytica has deep ties to the American right and was hired by the campaigns of Ben Carson, Ted Cruz and Donald Trump.

During the U.S. election, CNN called them “Donald Trump’s mind readers” and his secret weapon.

David Carroll is a Professor at the Parsons School of Design in New York City. He is one of the millions of Americans profiled by Cambridge Analytica and he’s taking legal action to find out where the company gets its masses of data and how they use it to create their vaunted psychographic profiles of voters.

On Day 6 [Banbury’s CBC radio programme], he explained why that’s important.

“They claim to have figured out how to project our voting behavior based on our consumer behavior. So it’s important for citizens to be able to understand this because it would affect our ability to understand how we’re being targeted by campaigns and how the messages that we’re seeing on Facebook and television are being directed at us to manipulate us.” [emphasis mine]

The parent company of Cambridge Analytica, SCL Group, is a U.K.-based data operation with global ties to military and political activities. David Carroll says the potential for sharing personal data internationally is a cause for concern.

“It’s the first time that this kind of data is being collected and transferred across geographic boundaries,” he says.

But that also gives Carroll an opening for legal action. An individual has more rights to access their personal information in the U.K., so that’s where he’s launching his lawsuit.

Reports link Michael Flynn, briefly Trump’s National Security Adviser, to SCL Group and indicate that former White House strategist Steve Bannon is a board member of Cambridge Analytica. Billionaire Robert Mercer, who has underwritten Bannon’s Breitbart operations and is a major Trump donor, also has a significant stake in Cambridge Analytica.

In the world of data, Mercer’s credentials are impeccable.

“He is an important contributor to the field of artificial intelligence,” says David Carroll.

“His work at IBM is seminal and really important in terms of the foundational ideas that go into big data analytics, so the relationship between AI and big data analytics. …

Banbury’s piece offers a lot more, including embedded videos, than I’ve not included in that excerpt but I also wanted to include some material from Carole Cadwalladr’s Oct. 1, 2017 Guardian article about Carroll and his legal fight in the UK,

“There are so many disturbing aspects to this. One of the things that really troubles me is how the company can buy anonymous data completely legally from all these different sources, but as soon as it attaches it to voter files, you are re-identified. It means that every privacy policy we have ignored in our use of technology is a broken promise. It would be one thing if this information stayed in the US, if it was an American company and it only did voter data stuff.”

But, he [Carroll] argues, “it’s not just a US company and it’s not just a civilian company”. Instead, he says, it has ties with the military through SCL – “and it doesn’t just do voter targeting”. Carroll has provided information to the Senate intelligence committee and believes that the disclosures mandated by a British court could provide evidence helpful to investigators.

Frank Pasquale, a law professor at the University of Maryland, author of The Black Box Society and a leading expert on big data and the law, called the case a “watershed moment”.

“It really is a David and Goliath fight and I think it will be the model for other citizens’ actions against other big corporations. I think we will look back and see it as a really significant case in terms of the future of algorithmic accountability and data protection. …

Nobody is discussing personal agency directly but if you’re only being exposed to certain kinds of messages then your personal agency has been taken from you. Admittedly we don’t have complete personal agency in our lives but AI along with the data gathering done online and increasingly with wearable and smart technology means that another layer of control has been added to your life and it is largely invisible. After all, the students in Elia Powers’ study didn’t realize their news feeds were being pre-curated.

Artificial intelligence (AI) company (in Montréal, Canada) attracts $135M in funding from Microsoft, Intel, Nvidia and others

It seems there’s a push on to establish Canada as a centre for artificial intelligence research and, if the federal and provincial governments have their way, for commercialization of said research. As always, there seems to be a bit of competition between Toronto (Ontario) and Montréal (Québec) as to which will be the dominant hub for the Canadian effort if one is to take Braga’s word for the situation.

In any event, Toronto seemed to have a mild advantage over Montréal initially with the 2017 Canadian federal government  budget announcement that the Canadian Institute for Advanced Research (CIFAR), based in Toronto, would launch a Pan-Canadian Artificial Intelligence Strategy and with an announcement from the University of Toronto shortly after (from my March 31, 2017 posting),

On the heels of the March 22, 2017 federal budget announcement of $125M for a Pan-Canadian Artificial Intelligence Strategy, the University of Toronto (U of T) has announced the inception of the Vector Institute for Artificial Intelligence in a March 28, 2017 news release by Jennifer Robinson (Note: Links have been removed),

A team of globally renowned researchers at the University of Toronto is driving the planning of a new institute staking Toronto’s and Canada’s claim as the global leader in AI.

Geoffrey Hinton, a University Professor Emeritus in computer science at U of T and vice-president engineering fellow at Google, will serve as the chief scientific adviser of the newly created Vector Institute based in downtown Toronto.

“The University of Toronto has long been considered a global leader in artificial intelligence research,” said U of T President Meric Gertler. “It’s wonderful to see that expertise act as an anchor to bring together researchers, government and private sector actors through the Vector Institute, enabling them to aim even higher in leading advancements in this fast-growing, critical field.”

As part of the Government of Canada’s Pan-Canadian Artificial Intelligence Strategy, Vector will share $125 million in federal funding with fellow institutes in Montreal and Edmonton. All three will conduct research and secure talent to cement Canada’s position as a world leader in AI.

However, Montréal and the province of Québec are no slouches when it comes to supporting to technology. From a June 14, 2017 article by Matthew Braga for CBC (Canadian Broadcasting Corporation) news online (Note: Links have been removed),

One of the most promising new hubs for artificial intelligence research in Canada is going international, thanks to a $135 million investment with contributions from some of the biggest names in tech.

The company, Montreal-based Element AI, was founded last October [2016] to help companies that might not have much experience in artificial intelligence start using the technology to change the way they do business.

It’s equal parts general research lab and startup incubator, with employees working to develop new and improved techniques in artificial intelligence that might not be fully realized for years, while also commercializing products and services that can be sold to clients today.

It was co-founded by Yoshua Bengio — one of the pioneers of a type of AI research called machine learning — along with entrepreneurs Jean-François Gagné and Nicolas Chapados, and the Canadian venture capital fund Real Ventures.

In an interview, Bengio and Gagné said the money from the company’s funding round will be used to hire 250 new employees by next January. A hundred will be based in Montreal, but an additional 100 employees will be hired for a new office in Toronto, and the remaining 50 for an Element AI office in Asia — its first international outpost.

They will join more than 100 employees who work for Element AI today, having left jobs at Amazon, Uber and Google, among others, to work at the company’s headquarters in Montreal.

The expansion is a big vote of confidence in Element AI’s strategy from some of the world’s biggest technology companies. Microsoft, Intel and Nvidia all contributed to the round, and each is a key player in AI research and development.

The company has some not unexpected plans and partners (from the Braga, article, Note: A link has been removed),

The Series A round was led by Data Collective, a Silicon Valley-based venture capital firm, and included participation by Fidelity Investments Canada, National Bank of Canada, and Real Ventures.

What will it help the company do? Scale, its founders say.

“We’re looking at domain experts, artificial intelligence experts,” Gagné said. “We already have quite a few, but we’re looking at people that are at the top of their game in their domains.

“And at this point, it’s no longer just pure artificial intelligence, but people who understand, extremely well, robotics, industrial manufacturing, cybersecurity, and financial services in general, which are all the areas we’re going after.”

Gagné says that Element AI has already delivered 10 projects to clients in those areas, and have many more in development. In one case, Element AI has been helping a Japanese semiconductor company better analyze the data collected by the assembly robots on its factory floor, in a bid to reduce manufacturing errors and improve the quality of the company’s products.

There’s more to investment in Québec’s AI sector than Element AI (from the Braga article; Note: Links have been removed),

Element AI isn’t the only organization in Canada that investors are interested in.

In September, the Canadian government announced $213 million in funding for a handful of Montreal universities, while both Google and Microsoft announced expansions of their Montreal AI research groups in recent months alongside investments in local initiatives. The province of Quebec has pledged $100 million for AI initiatives by 2022.

Braga goes on to note some other initiatives but at that point the article’s focus is exclusively Toronto.

For more insight into the AI situation in Québec, there’s Dan Delmar’s May 23, 2017 article for the Montreal Express (Note: Links have been removed),

Advocating for massive government spending with little restraint admittedly deviates from the tenor of these columns, but the AI business is unlike any other before it. [emphasis misn] Having leaders acting as fervent advocates for the industry is crucial; resisting the coming technological tide is, as the Borg would say, futile.

The roughly 250 AI researchers who call Montreal home are not simply part of a niche industry. Quebec’s francophone character and Montreal’s multilingual citizenry are certainly factors favouring the development of language technology, but there’s ample opportunity for more ambitious endeavours with broader applications.

AI isn’t simply a technological breakthrough; it is the technological revolution. [emphasis mine] In the coming decades, modern computing will transform all industries, eliminating human inefficiencies and maximizing opportunities for innovation and growth — regardless of the ethical dilemmas that will inevitably arise.

“By 2020, we’ll have computers that are powerful enough to simulate the human brain,” said (in 2009) futurist Ray Kurzweil, author of The Singularity Is Near, a seminal 2006 book that has inspired a generation of AI technologists. Kurzweil’s projections are not science fiction but perhaps conservative, as some forms of AI already effectively replace many human cognitive functions. “By 2045, we’ll have expanded the intelligence of our human-machine civilization a billion-fold. That will be the singularity.”

The singularity concept, borrowed from physicists describing event horizons bordering matter-swallowing black holes in the cosmos, is the point of no return where human and machine intelligence will have completed their convergence. That’s when the machines “take over,” so to speak, and accelerate the development of civilization beyond traditional human understanding and capability.

The claims I’ve highlighted in Delmar’s article have been made before for other technologies, “xxx is like no other business before’ and “it is a technological revolution.”  Also if you keep scrolling down to the bottom of the article, you’ll find Delmar is a ‘public relations consultant’ which, if you look at his LinkedIn profile, you’ll find means he’s a managing partner in a PR firm known as Provocateur.

Bertrand Marotte’s May 20, 2017 article for the Montreal Gazette offers less hyperbole along with additional detail about the Montréal scene (Note: Links have been removed),

It might seem like an ambitious goal, but key players in Montreal’s rapidly growing artificial-intelligence sector are intent on transforming the city into a Silicon Valley of AI.

Certainly, the flurry of activity these days indicates that AI in the city is on a roll. Impressive amounts of cash have been flowing into academia, public-private partnerships, research labs and startups active in AI in the Montreal area.

…, researchers at Microsoft Corp. have successfully developed a computing system able to decipher conversational speech as accurately as humans do. The technology makes the same, or fewer, errors than professional transcribers and could be a huge boon to major users of transcription services like law firms and the courts.

Setting the goal of attaining the critical mass of a Silicon Valley is “a nice point of reference,” said tech entrepreneur Jean-François Gagné, co-founder and chief executive officer of Element AI, an artificial intelligence startup factory launched last year.

The idea is to create a “fluid, dynamic ecosystem” in Montreal where AI research, startup, investment and commercialization activities all mesh productively together, said Gagné, who founded Element with researcher Nicolas Chapados and Université de Montréal deep learning pioneer Yoshua Bengio.

“Artificial intelligence is seen now as a strategic asset to governments and to corporations. The fight for resources is global,” he said.

The rise of Montreal — and rival Toronto — as AI hubs owes a lot to provincial and federal government funding.

Ottawa promised $213 million last September to fund AI and big data research at four Montreal post-secondary institutions. Quebec has earmarked $100 million over the next five years for the development of an AI “super-cluster” in the Montreal region.

The provincial government also created a 12-member blue-chip committee to develop a strategic plan to make Quebec an AI hub, co-chaired by Claridge Investments Ltd. CEO Pierre Boivin and Université de Montréal rector Guy Breton.

But private-sector money has also been flowing in, particularly from some of the established tech giants competing in an intense AI race for innovative breakthroughs and the best brains in the business.

Montreal’s rich talent pool is a major reason Waterloo, Ont.-based language-recognition startup Maluuba decided to open a research lab in the city, said the company’s vice-president of product development, Mohamed Musbah.

“It’s been incredible so far. The work being done in this space is putting Montreal on a pedestal around the world,” he said.

Microsoft struck a deal this year to acquire Maluuba, which is working to crack one of the holy grails of deep learning: teaching machines to read like the human brain does. Among the company’s software developments are voice assistants for smartphones.

Maluuba has also partnered with an undisclosed auto manufacturer to develop speech recognition applications for vehicles. Voice recognition applied to cars can include such things as asking for a weather report or making remote requests for the vehicle to unlock itself.

Marotte’s Twitter profile describes him as a freelance writer, editor, and translator.