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Vector Institute and Canada’s artificial intelligence sector

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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.

In addition, Vector is expected to receive funding from the Province of Ontario and more than 30 top Canadian and global companies eager to tap this pool of talent to grow their businesses. The institute will also work closely with other Ontario universities with AI talent.

(See my March 24, 2017 posting; scroll down about 25% for the science part, including the Pan-Canadian Artificial Intelligence Strategy of the budget.)

Not obvious in last week’s coverage of the Pan-Canadian Artificial Intelligence Strategy is that the much lauded Hinton has been living in the US and working for Google. These latest announcements (Pan-Canadian AI Strategy and Vector Institute) mean that he’s moving back.

A March 28, 2017 article by Kate Allen for TorontoStar.com provides more details about the Vector Institute, Hinton, and the Canadian ‘brain drain’ as it applies to artificial intelligence, (Note:  A link has been removed)

Toronto will host a new institute devoted to artificial intelligence, a major gambit to bolster a field of research pioneered in Canada but consistently drained of talent by major U.S. technology companies like Google, Facebook and Microsoft.

The Vector Institute, an independent non-profit affiliated with the University of Toronto, will hire about 25 new faculty and research scientists. It will be backed by more than $150 million in public and corporate funding in an unusual hybridization of pure research and business-minded commercial goals.

The province will spend $50 million over five years, while the federal government, which announced a $125-million Pan-Canadian Artificial Intelligence Strategy in last week’s budget, is providing at least $40 million, backers say. More than two dozen companies have committed millions more over 10 years, including $5 million each from sponsors including Google, Air Canada, Loblaws, and Canada’s five biggest banks [Bank of Montreal (BMO). Canadian Imperial Bank of Commerce ({CIBC} President’s Choice Financial},  Royal Bank of Canada (RBC), Scotiabank (Tangerine), Toronto-Dominion Bank (TD Canada Trust)].

The mode of artificial intelligence that the Vector Institute will focus on, deep learning, has seen remarkable results in recent years, particularly in image and speech recognition. Geoffrey Hinton, considered the “godfather” of deep learning for the breakthroughs he made while a professor at U of T, has worked for Google since 2013 in California and Toronto.

Hinton will move back to Canada to lead a research team based at the tech giant’s Toronto offices and act as chief scientific adviser of the new institute.

…

Researchers trained in Canadian artificial intelligence labs fill the ranks of major technology companies, working on tools like instant language translation, facial recognition, and recommendation services. Academic institutions and startups in Toronto, Waterloo, Montreal and Edmonton boast leaders in the field, but other researchers have left for U.S. universities and corporate labs.

The goals of the Vector Institute are to retain, repatriate and attract AI talent, to create more trained experts, and to feed that expertise into existing Canadian companies and startups.

…

Hospitals are expected to be a major partner, since health care is an intriguing application for AI. Last month, researchers from Stanford University announced they had trained a deep learning algorithm to identify potentially cancerous skin lesions with accuracy comparable to human dermatologists. The Toronto company Deep Genomics is using deep learning to read genomes and identify mutations that may lead to disease, among other things.

Intelligent algorithms can also be applied to tasks that might seem less virtuous, like reading private data to better target advertising. Zemel [Richard Zemel, the institute’s research director and a professor of computer science at U of T] says the centre is creating an ethics working group [emphasis mine] and maintaining ties with organizations that promote fairness and transparency in machine learning. As for privacy concerns, “that’s something we are well aware of. We don’t have a well-formed policy yet but we will fairly soon.”

The institute’s annual funding pales in comparison to the revenues of the American tech giants, which are measured in tens of billions. The risk the institute’s backers are taking is simply creating an even more robust machine learning PhD mill for the U.S.

“They obviously won’t all stay in Canada, but Toronto industry is very keen to get them,” Hinton said. “I think Trump might help there.” Two researchers on Hinton’s new Toronto-based team are Iranian, one of the countries targeted by U.S. President Donald Trump’s travel bans.

Ethics do seem to be a bit of an afterthought. Presumably the Vector Institute’s ‘ethics working group’ won’t include any regular folks. Is there any thought to what the rest of us think about these developments? As there will also be some collaboration with other proposed AI institutes including ones at the University of Montreal (Université de Montréal) and the University of Alberta (Kate McGillivray’s article coming up shortly mentions them), might the ethics group be centered in either Edmonton or Montreal? Interestingly, two Canadians (Timothy Caulfield at the University of Alberta and Eric Racine at Université de Montréa) testified at the US Commission for the Study of Bioethical Issues Feb. 10 – 11, 2014 meeting, the Brain research, ethics, and nanotechnology. Still speculating here but I imagine Caulfield and/or Racine could be persuaded to extend their expertise in ethics and the human brain to AI and its neural networks.

Getting back to the topic at hand the ‘AI sceneCanada’, Allen’s article is worth reading in its entirety if you have the time.

Kate McGillivray’s March 29, 2017 article for the Canadian Broadcasting Corporation’s (CBC) news online provides more details about the Canadian AI situation and the new strategies,

With artificial intelligence set to transform our world, a new institute is putting Toronto to the front of the line to lead the charge.

The Vector Institute for Artificial Intelligence, made possible by funding from the federal government revealed in the 2017 budget, will move into new digs in the MaRS Discovery District by the end of the year.

…

Vector’s funding comes partially from a $125 million investment announced in last Wednesday’s federal budget to launch a pan-Canadian artificial intelligence strategy, with similar institutes being established in Montreal and Edmonton.

“[A.I.] cuts across pretty well every sector of the economy,” said Dr. Alan Bernstein, CEO and president of the Canadian Institute for Advanced Research, the organization tasked with administering the federal program.

“Silicon Valley and England and other places really jumped on it, so we kind of lost the lead a little bit. I think the Canadian federal government has now realized that,” he said.

Stopping up the brain drain

Critical to the strategy’s success is building a homegrown base of A.I. experts and innovators — a problem in the last decade, despite pioneering work on so-called “Deep Learning” by Canadian scholars such as Yoshua Bengio and Geoffrey Hinton, a former University of Toronto professor who will now serve as Vector’s chief scientific advisor.

With few university faculty positions in Canada and with many innovative companies headquartered elsewhere, it has been tough to keep the few graduates specializing in A.I. in town.

“We were paying to educate people and shipping them south,” explained Ed Clark, chair of the Vector Institute and business advisor to Ontario Premier Kathleen Wynne.

…

The existence of that “fantastic science” will lean heavily on how much buy-in Vector and Canada’s other two A.I. centres get.

Toronto’s portion of the $125 million is a “great start,” said Bernstein, but taken alone, “it’s not enough money.”

“My estimate of the right amount of money to make a difference is a half a billion or so, and I think we will get there,” he said.

Jessica Murphy’s March 29, 2017 article for the British Broadcasting Corporation’s (BBC) news online offers some intriguing detail about the Canadian AI scene,

Canadian researchers have been behind some recent major breakthroughs in artificial intelligence. Now, the country is betting on becoming a big player in one of the hottest fields in technology, with help from the likes of Google and RBC [Royal Bank of Canada].

In an unassuming building on the University of Toronto’s downtown campus, Geoff Hinton laboured for years on the “lunatic fringe” of academia and artificial intelligence, pursuing research in an area of AI called neural networks.

Also known as “deep learning”, neural networks are computer programs that learn in similar way to human brains. The field showed early promise in the 1980s, but the tech sector turned its attention to other AI methods after that promise seemed slow to develop.

“The approaches that I thought were silly were in the ascendancy and the approach that I thought was the right approach was regarded as silly,” says the British-born [emphasis mine] professor, who splits his time between the university and Google, where he is a vice-president of engineering fellow.

…

Neural networks are used by the likes of Netflix to recommend what you should binge watch and smartphones with voice assistance tools. Google DeepMind’s AlphaGo AI used them to win against a human in the ancient game of Go in 2016.

…

Foteini Agrafioti, who heads up the new RBC Research in Machine Learning lab at the University of Toronto, said those recent innovations made AI attractive to researchers and the tech industry.

“Anything that’s powering Google’s engines right now is powered by deep learning,” she says.

Developments in the field helped jumpstart innovation and paved the way for the technology’s commercialisation. They also captured the attention of Google, IBM and Microsoft, and kicked off a hiring race in the field.

The renewed focus on neural networks has boosted the careers of early Canadian AI machine learning pioneers like Hinton, the University of Montreal’s Yoshua Bengio, and University of Alberta’s Richard Sutton.

Money from big tech is coming north, along with investments by domestic corporations like banking multinational RBC and auto parts giant Magna, and millions of dollars in government funding.

…

Former banking executive Ed Clark will head the institute, and says the goal is to make Toronto, which has the largest concentration of AI-related industries in Canada, one of the top five places in the world for AI innovation and business.

The founders also want it to serve as a magnet and retention tool for top talent aggressively head-hunted by US firms.

Clark says they want to “wake up” Canadian industry to the possibilities of AI, which is expected to have a massive impact on fields like healthcare, banking, manufacturing and transportation.

…

Google invested C$4.5m (US$3.4m/£2.7m) last November [2016] in the University of Montreal’s Montreal Institute for Learning Algorithms.

Microsoft is funding a Montreal startup, Element AI. The Seattle-based company also announced it would acquire Montreal-based Maluuba and help fund AI research at the University of Montreal and McGill University.

Thomson Reuters and General Motors both recently moved AI labs to Toronto.

…

RBC is also investing in the future of AI in Canada, including opening a machine learning lab headed by Agrafioti, co-funding a program to bring global AI talent and entrepreneurs to Toronto, and collaborating with Sutton and the University of Alberta’s Machine Intelligence Institute.

…

Canadian tech also sees the travel uncertainty created by the Trump administration in the US as making Canada more attractive to foreign talent. (One of Clark’s the selling points is that Toronto as an “open and diverse” city).

…

This may reverse the ‘brain drain’ but it appears Canada’s role as a ‘branch plant economy’ for foreign (usually US) companies could become an important discussion once more. From the ‘Foreign ownership of companies of Canada’ Wikipedia entry (Note: Links have been removed),

Historically, foreign ownership was a political issue in Canada in the late 1960s and early 1970s, when it was believed by some that U.S. investment had reached new heights (though its levels had actually remained stable for decades), and then in the 1980s, during debates over the Free Trade Agreement.

But the situation has changed, since in the interim period Canada itself became a major investor and owner of foreign corporations. Since the 1980s, Canada’s levels of investment and ownership in foreign companies have been larger than foreign investment and ownership in Canada. In some smaller countries, such as Montenegro, Canadian investment is sizable enough to make up a major portion of the economy. In Northern Ireland, for example, Canada is the largest foreign investor. By becoming foreign owners themselves, Canadians have become far less politically concerned about investment within Canada.

Of note is that Canada’s largest companies by value, and largest employers, tend to be foreign-owned in a way that is more typical of a developing nation than a G8 member. The best example is the automotive sector, one of Canada’s most important industries. It is dominated by American, German, and Japanese giants. Although this situation is not unique to Canada in the global context, it is unique among G-8 nations, and many other relatively small nations also have national automotive companies.

It’s interesting to note that sometimes Canadian companies are the big investors but that doesn’t change our basic position. And, as I’ve noted in other postings (including the March 24, 2017 posting), these government investments in science and technology won’t necessarily lead to a move away from our ‘branch plant economy’ towards an innovative Canada.

You can find out more about the Vector Institute for Artificial Intelligence here.

BTW, I noted that reference to Hinton as ‘British-born’ in the BBC article. He was educated in the UK and subsidized by UK taxpayers (from his Wikipedia entry; Note: Links have been removed),

Hinton was educated at King’s College, Cambridge graduating in 1970, with a Bachelor of Arts in experimental psychology.[1] He continued his study at the University of Edinburgh where he was awarded a PhD in artificial intelligence in 1977 for research supervised by H. Christopher Longuet-Higgins.[3][12]

It seems Canadians are not the only ones to experience  ‘brain drains’.

Finally, I wrote at length about a recent initiative taking place between the University of British Columbia (Vancouver, Canada) and the University of Washington (Seattle, Washington), the Cascadia Urban Analytics Cooperative in a Feb. 28, 2017 posting noting that the initiative is being funded by Microsoft to the tune $1M and is part of a larger cooperative effort between the province of British Columbia and the state of Washington. Artificial intelligence is not the only area where US technology companies are hedging their bets (against Trump’s administration which seems determined to terrify people from crossing US borders) by investing in Canada.

For anyone interested in a little more information about AI in the US and China, there’s today’s (March 31, 2017)earlier posting: China, US, and the race for artificial intelligence research domination.

China, US, and the race for artificial intelligence research domination

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John Markoff and Matthew Rosenberg have written a fascinating analysis of the competition between US and China regarding technological advances, specifically in the field of artificial intelligence. While the focus of the Feb. 3, 2017 NY Times article is military, the authors make it easy to extrapolate and apply the concepts to other sectors,

Robert O. Work, the veteran defense official retained as deputy secretary by President Trump, calls them his “A.I. dudes.” The breezy moniker belies their serious task: The dudes have been a kitchen cabinet of sorts, and have advised Mr. Work as he has sought to reshape warfare by bringing artificial intelligence to the battlefield.

Last spring, he asked, “O.K., you guys are the smartest guys in A.I., right?”

No, the dudes told him, “the smartest guys are at Facebook and Google,” Mr. Work recalled in an interview.

Now, increasingly, they’re also in China. The United States no longer has a strategic monopoly on the technology, which is widely seen as the key factor in the next generation of warfare.

The Pentagon’s plan to bring A.I. to the military is taking shape as Chinese researchers assert themselves in the nascent technology field. And that shift is reflected in surprising commercial advances in artificial intelligence among Chinese companies. [emphasis mine]

Having read Marshal McLuhan (de rigeur for any Canadian pursuing a degree in communications [sociology-based] anytime from the 1960s into the late 1980s [at least]), I took the movement of technology from military research to consumer applications as a standard. Television is a classic example but there are many others including modern plastic surgery. The first time, I encountered the reverse (consumer-based technology being adopted by the military) was in a 2004 exhibition “Massive Change: The Future of Global Design” produced by Bruce Mau for the Vancouver (Canada) Art Gallery.

Markoff and Rosenberg develop their thesis further (Note: Links have been removed),

Last year, for example, Microsoft researchers proclaimed that the company had created software capable of matching human skills in understanding speech.

Although they boasted that they had outperformed their United States competitors, a well-known A.I. researcher who leads a Silicon Valley laboratory for the Chinese web services company Baidu gently taunted Microsoft, noting that Baidu had achieved similar accuracy with the Chinese language two years earlier.

That, in a nutshell, is the challenge the United States faces as it embarks on a new military strategy founded on the assumption of its continued superiority in technologies such as robotics and artificial intelligence.

First announced last year by Ashton B. Carter, President Barack Obama’s defense secretary, the “Third Offset” strategy provides a formula for maintaining a military advantage in the face of a renewed rivalry with China and Russia.

…

As consumer electronics manufacturing has moved to Asia, both Chinese companies and the nation’s government laboratories are making major investments in artificial intelligence.

The advance of the Chinese was underscored last month when Qi Lu, a veteran Microsoft artificial intelligence specialist, left the company to become chief operating officer at Baidu, where he will oversee the company’s ambitious plan to become a global leader in A.I.

The authors note some recent military moves (Note: Links have been removed),

In August [2016], the state-run China Daily reported that the country had embarked on the development of a cruise missile system with a “high level” of artificial intelligence. The new system appears to be a response to a missile the United States Navy is expected to deploy in 2018 to counter growing Chinese military influence in the Pacific.

Known as the Long Range Anti-Ship Missile, or L.R.A.S.M., it is described as a “semiautonomous” weapon. According to the Pentagon, this means that though targets are chosen by human soldiers, the missile uses artificial intelligence technology to avoid defenses and make final targeting decisions.

The new Chinese weapon typifies a strategy known as “remote warfare,” said John Arquilla, a military strategist at the Naval Post Graduate School in Monterey, Calif. The idea is to build large fleets of small ships that deploy missiles, to attack an enemy with larger ships, like aircraft carriers.

“They are making their machines more creative,” he said. “A little bit of automation gives the machines a tremendous boost.”

Whether or not the Chinese will quickly catch the United States in artificial intelligence and robotics technologies is a matter of intense discussion and disagreement in the United States.

Markoff and Rosenberg return to the world of consumer electronics as they finish their article on AI and the military (Note: Links have been removed),

Moreover, while there appear to be relatively cozy relationships between the Chinese government and commercial technology efforts, the same cannot be said about the United States. The Pentagon recently restarted its beachhead in Silicon Valley, known as the Defense Innovation Unit Experimental facility, or DIUx. It is an attempt to rethink bureaucratic United States government contracting practices in terms of the faster and more fluid style of Silicon Valley.

The government has not yet undone the damage to its relationship with the Valley brought about by Edward J. Snowden’s revelations about the National Security Agency’s surveillance practices. Many Silicon Valley firms remain hesitant to be seen as working too closely with the Pentagon out of fear of losing access to China’s market.

“There are smaller companies, the companies who sort of decided that they’re going to be in the defense business, like a Palantir,” said Peter W. Singer, an expert in the future of war at New America, a think tank in Washington, referring to the Palo Alto, Calif., start-up founded in part by the venture capitalist Peter Thiel. “But if you’re thinking about the big, iconic tech companies, they can’t become defense contractors and still expect to get access to the Chinese market.”

Those concerns are real for Silicon Valley.

If you have the time, I recommend reading the article in its entirety.

Impact of the US regime on thinking about AI?

A March 24, 2017 article by Daniel Gross for Slate.com hints that at least one high level offician in the Trump administration may be a little naïve in his understanding of AI and its impending impact on US society (Note: Links have been removed),

Treasury Secretary Steven Mnuchin is a sharp guy. He’s a (legacy) alumnus of Yale and Goldman Sachs, did well on Wall Street, and was a successful movie producer and bank investor. He’s good at, and willing to, put other people’s money at risk alongside some of his own. While he isn’t the least qualified person to hold the post of treasury secretary in 2017, he’s far from the best qualified. For in his 54 years on this planet, he hasn’t expressed or displayed much interest in economic policy, or in grappling with the big picture macroeconomic issues that are affecting our world. It’s not that he is intellectually incapable of grasping them; they just haven’t been in his orbit.

Which accounts for the inanity he uttered at an Axios breakfast Friday morning about the impact of artificial intelligence on jobs.

“it’s not even on our radar screen…. 50-100 more years” away, he said. “I’m not worried at all” about robots displacing humans in the near future, he said, adding: “In fact I’m optimistic.”

…

A.I. is already affecting the way people work, and the work they do. (In fact, I’ve long suspected that Mike Allen, Mnuchin’s Axios interlocutor, is powered by A.I.) I doubt Mnuchin has spent much time in factories, for example. But if he did, he’d see that machines and software are increasingly doing the work that people used to do. They’re not just moving goods through an assembly line, they’re soldering, coating, packaging, and checking for quality. Whether you’re visiting a GE turbine plant in South Carolina, or a cable-modem factory in Shanghai, the thing you’ll notice is just how few people there actually are. It’s why, in the U.S., manufacturing output rises every year while manufacturing employment is essentially stagnant. It’s why it is becoming conventional wisdom that automation is destroying more manufacturing jobs than trade. And now we are seeing the prospect of dark factories, which can run without lights because there are no people in them, are starting to become a reality. The integration of A.I. into factories is one of the reasons Trump’s promise to bring back manufacturing employment is absurd. You’d think his treasury secretary would know something about that.

It goes far beyond manufacturing, of course. Programmatic advertising buying, Spotify’s recommendation engines, chatbots on customer service websites, Uber’s dispatching system—all of these are examples of A.I. doing the work that people used to do. …

…

Adding to Mnuchin’s lack of credibility on the topic of jobs and robots/AI, Matthew Rozsa’s March 28, 2017 article for Salon.com features a study from the US National Bureau of Economic Research (Note: Links have been removed),

A new study by the National Bureau of Economic Research shows that every fully autonomous robot added to an American factory has reduced employment by an average of 6.2 workers, according to a report by BuzzFeed. The study also found that for every fully autonomous robot per thousand workers, the employment rate dropped by 0.18 to 0.34 percentage points and wages fell by 0.25 to 0.5 percentage points.

I can’t help wondering if the US Secretary of the Treasury is so oblivious to what is going on in the workplace whether that’s representative of other top-tier officials such as the Secretary of Defense, Secretary of Labor, etc. What is going to happen to US research in fields such as robotics and AI?

I have two more questions, in future what happens to research which contradicts or makes a top tier Trump government official look foolish? Will it be suppressed?

You can find the report “Robots and Jobs: Evidence from US Labor Markets” by Daron Acemoglu and Pascual Restrepo. NBER (US National Bureau of Economic Research) WORKING PAPER SERIES (Working Paper 23285) released March 2017 here. The introduction featured some new information for me; the term ‘technological unemployment’ was introduced in 1930 by John Maynard Keynes.

Moving from a wholly US-centric view of AI

Naturally in a discussion about AI, it’s all US and the country considered its chief sceince rival, China, with a mention of its old rival, Russia. Europe did rate a mention, albeit as a totality. Having recently found out that Canadians were pioneers in a very important aspect of AI, machine-learning, I feel obliged to mention it. You can find more about Canadian AI efforts in my March 24, 2017 posting (scroll down about 40% of the way) where you’ll find a very brief history and mention of the funding for a newly launching, Pan-Canadian Artificial Intelligence Strategy.

If any of my readers have information about AI research efforts in other parts of the world, please feel free to write them up in the comments.

Ishiguro’s robots and Swiss scientist question artificial intelligence at SXSW (South by Southwest) 2017

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It seems unexpected to stumble across presentations on robots and on artificial intelligence at an entertainment conference such as South by South West (SXSW). Here’s why I thought so, from the SXSW Wikipedia entry (Note: Links have been removed),

South by Southwest (abbreviated as SXSW) is an annual conglomerate of film, interactive media, and music festivals and conferences that take place in mid-March in Austin, Texas, United States. It began in 1987, and has continued to grow in both scope and size every year. In 2011, the conference lasted for 10 days with SXSW Interactive lasting for 5 days, Music for 6 days, and Film running concurrently for 9 days.

Lifelike robots

The 2017 SXSW Interactive featured separate presentations by Japanese roboticist, Hiroshi Ishiguro (mentioned here a few times), and EPFL (École Polytechnique Fédérale de Lausanne; Switzerland) artificial intelligence expert, Marcel Salathé.

Ishiguro’s work is the subject of Harry McCracken’s March 14, 2017 article for Fast Company (Note: Links have been removed),

I’m sitting in the Japan Factory pavilion at SXSW in Austin, Texas, talking to two other attendees about whether human beings are more valuable than robots. I say that I believe human life to be uniquely precious, whereupon one of the others rebuts me by stating that humans allow cars to exist even though they kill humans.

It’s a reasonable point. But my fellow conventioneer has a bias: It’s a robot itself, with an ivory-colored, mask-like face and visible innards. So is the third participant in the conversation, a much more human automaton modeled on a Japanese woman and wearing a black-and-white blouse and a blue scarf.

We’re chatting as part of a demo of technologies developed by the robotics lab of Hiroshi Ishiguro, based at Osaka University, and Japanese telecommunications company NTT. Ishiguro has gained fame in the field by creating increasingly humanlike robots—that is, androids—with the ultimate goal of eliminating the uncanny valley that exists between people and robotic people.

I also caught up with Ishiguro himself at the conference—his second SXSW—to talk about his work. He’s a champion of the notion that people will respond best to robots who simulate humanity, thereby creating “a feeling of presence,” as he describes it. That gives him and his researchers a challenge that encompasses everything from technology to psychology. “Our approach is quite interdisciplinary,” he says, which is what prompted him to bring his work to SXSW.

A SXSW attendee talks about robots with two robots.

If you have the time, do read McCracken’t piece in its entirety.

You can find out more about the ‘uncanny valley’ in my March 10, 2011 posting about Ishiguro’s work if you scroll down about 70% of the way to find the ‘uncanny valley’ diagram and Masahiro Mori’s description of the concept he developed.

You can read more about Ishiguro and his colleague, Ryuichiro Higashinaka, on their SXSW biography page.

Artificial intelligence (AI)

In a March 15, 2017 EPFL press release by Hilary Sanctuary, scientist Marcel Salathé poses the question: Is Reliable Artificial Intelligence Possible?,

In the quest for reliable artificial intelligence, EPFL scientist Marcel Salathé argues that AI technology should be openly available. He will be discussing the topic at this year’s edition of South by South West on March 14th in Austin, Texas.

Will artificial intelligence (AI) change the nature of work? For EPFL theoretical biologist Marcel Salathé, the answer is invariably yes. To him, a more fundamental question that needs to be addressed is who owns that artificial intelligence?

“We have to hold AI accountable, and the only way to do this is to verify it for biases and make sure there is no deliberate misinformation,” says Salathé. “This is not possible if the AI is privatized.”

AI is both the algorithm and the data

So what exactly is AI? It is generally regarded as “intelligence exhibited by machines”. Today, it is highly task specific, specially designed to beat humans at strategic games like Chess and Go, or diagnose skin disease on par with doctors’ skills.

On a practical level, AI is implemented through what scientists call “machine learning”, which means using a computer to run specifically designed software that can be “trained”, i.e. process data with the help of algorithms and to correctly identify certain features from that data set. Like human cognition, AI learns by trial and error. Unlike humans, however, AI can process and recall large quantities of data, giving it a tremendous advantage over us.

Crucial to AI learning, therefore, is the underlying data. For Salathé, AI is defined by both the algorithm and the data, and as such, both should be publicly available.

Deep learning algorithms can be perturbed

Last year, Salathé created an algorithm to recognize plant diseases. With more than 50,000 photos of healthy and diseased plants in the database, the algorithm uses artificial intelligence to diagnose plant diseases with the help of your smartphone. As for human disease, a recent study by a Stanford Group on cancer showed that AI can be trained to recognize skin cancer slightly better than a group of doctors. The consequences are far-reaching: AI may one day diagnose our diseases instead of doctors. If so, will we really be able to trust its diagnosis?

These diagnostic tools use data sets of images to train and learn. But visual data sets can be perturbed that prevent deep learning algorithms from correctly classifying images. Deep neural networks are highly vulnerable to visual perturbations that are practically impossible to detect with the naked eye, yet causing the AI to misclassify images.

In future implementations of AI-assisted medical diagnostic tools, these perturbations pose a serious threat. More generally, the perturbations are real and may already be affecting the filtered information that reaches us every day. These vulnerabilities underscore the importance of certifying AI technology and monitoring its reliability.

h/t phys.org March 15, 2017 news item

As I noted earlier, these are not the kind of presentations you’d expect at an ‘entertainment’ festival.

The Canadian science scene and the 2017 Canadian federal budget

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There’s not much happening in the 2017-18 budget in terms of new spending according to Paul Wells’ March 22, 2017 article for TheStar.com,

This is the 22nd or 23rd federal budget I’ve covered. And I’ve never seen the like of the one Bill Morneau introduced on Wednesday [March 22, 2017].

Not even in the last days of the Harper Conservatives did a budget provide for so little new spending — $1.3 billion in the current budget year, total, in all fields of government. That’s a little less than half of one per cent of all federal program spending for this year.

But times are tight. The future is a place where we can dream. So the dollars flow more freely in later years. In 2021-22, the budget’s fifth planning year, new spending peaks at $8.2 billion. Which will be about 2.4 per cent of all program spending.

…

He’s not alone in this 2017 federal budget analysis; CBC (Canadian Broadcasting Corporation) pundits, Chantal Hébert, Andrew Coyne, and Jennifer Ditchburn said much the same during their ‘At Issue’ segment of the March 22, 2017 broadcast of The National (news).

Before I focus on the science and technology budget, here are some general highlights from the CBC’s March 22, 2017 article on the 2017-18 budget announcement (Note: Links have been removed,

Here are highlights from the 2017 federal budget:

  • Deficit: $28.5 billion, up from $25.4 billion projected in the fall.
  • Trend: Deficits gradually decline over next five years — but still at $18.8 billion in 2021-22.
  • Housing: $11.2 billion over 11 years, already budgeted, will go to a national housing strategy.
  • Child care: $7 billion over 10 years, already budgeted, for new spaces, starting 2018-19.
  • Indigenous: $3.4 billion in new money over five years for infrastructure, health and education.
  • Defence: $8.4 billion in capital spending for equipment pushed forward to 2035.
  • Care givers: New care-giving benefit up to 15 weeks, starting next year.
  • Skills: New agency to research and measure skills development, starting 2018-19.
  • Innovation: $950 million over five years to support business-led “superclusters.”
  • Startups: $400 million over three years for a new venture capital catalyst initiative.
  • AI: $125 million to launch a pan-Canadian Artificial Intelligence Strategy.
  • Coding kids: $50 million over two years for initiatives to teach children to code.
  • Families: Option to extend parental leave up to 18 months.
  • Uber tax: GST to be collected on ride-sharing services.
  • Sin taxes: One cent more on a bottle of wine, five cents on 24 case of beer.
  • Bye-bye: No more Canada Savings Bonds.
  • Transit credit killed: 15 per cent non-refundable public transit tax credit phased out this year.

You can find the entire 2017-18 budget here.

Science and the 2017-18 budget

For anyone interested in the science news, you’ll find most of that in the 2017 budget’s Chapter 1 — Skills, Innovation and Middle Class jobs. As well, Wayne Kondro has written up a précis in his March 22, 2017 article for Science (magazine),

Finance officials, who speak on condition of anonymity during the budget lock-up, indicated the budgets of the granting councils, the main source of operational grants for university researchers, will be “static” until the government can assess recommendations that emerge from an expert panel formed in 2015 and headed by former University of Toronto President David Naylor to review basic science in Canada [highlighted in my June 15, 2016 posting ; $2M has been allocated for the advisor and associated secretariat]. Until then, the officials said, funding for the Natural Sciences and Engineering Research Council of Canada (NSERC) will remain at roughly $848 million, whereas that for the Canadian Institutes of Health Research (CIHR) will remain at $773 million, and for the Social Sciences and Humanities Research Council [SSHRC] at $547 million.

NSERC, though, will receive $8.1 million over 5 years to administer a PromoScience Program that introduces youth, particularly unrepresented groups like Aboriginal people and women, to science, technology, engineering, and mathematics through measures like “space camps and conservation projects.” CIHR, meanwhile, could receive modest amounts from separate plans to identify climate change health risks and to reduce drug and substance abuse, the officials added.

… Canada’s Innovation and Skills Plan, would funnel $600 million over 5 years allocated in 2016, and $112.5 million slated for public transit and green infrastructure, to create Silicon Valley–like “super clusters,” which the budget defined as “dense areas of business activity that contain large and small companies, post-secondary institutions and specialized talent and infrastructure.” …

…

… The Canadian Institute for Advanced Research will receive $93.7 million [emphasis mine] to “launch a Pan-Canadian Artificial Intelligence Strategy … (to) position Canada as a world-leading destination for companies seeking to invest in artificial intelligence and innovation.”

…

… Among more specific measures are vows to: Use $87.7 million in previous allocations to the Canada Research Chairs program to create 25 “Canada 150 Research Chairs” honoring the nation’s 150th year of existence, provide $1.5 million per year to support the operations of the office of the as-yet-unappointed national science adviser [see my Dec. 7, 2016 post for information about the job posting, which is now closed]; provide $165.7 million [emphasis mine] over 5 years for the nonprofit organization Mitacs to create roughly 6300 more co-op positions for university students and grads, and provide $60.7 million over five years for new Canadian Space Agency projects, particularly for Canadian participation in the National Aeronautics and Space Administration’s next Mars Orbiter Mission.

Kondros was either reading an earlier version of the budget or made an error regarding Mitacs (from the budget in the “A New, Ambitious Approach to Work-Integrated Learning” subsection),

Mitacs has set an ambitious goal of providing 10,000 work-integrated learning placements for Canadian post-secondary students and graduates each year—up from the current level of around 3,750 placements. Budget 2017 proposes to provide $221 million [emphasis mine] over five years, starting in 2017–18, to achieve this goal and provide relevant work experience to Canadian students.

As well, the budget item for the Pan-Canadian Artificial Intelligence Strategy is $125M.

Moving from Kondros’ précis, the budget (in the “Positioning National Research Council Canada Within the Innovation and Skills Plan” subsection) announces support for these specific areas of science,

Stem Cell Research

The Stem Cell Network, established in 2001, is a national not-for-profit organization that helps translate stem cell research into clinical applications, commercial products and public policy. Its research holds great promise, offering the potential for new therapies and medical treatments for respiratory and heart diseases, cancer, diabetes, spinal cord injury, multiple sclerosis, Crohn’s disease, auto-immune disorders and Parkinson’s disease. To support this important work, Budget 2017 proposes to provide the Stem Cell Network with renewed funding of $6 million in 2018–19.

Space Exploration

Canada has a long and proud history as a space-faring nation. As our international partners prepare to chart new missions, Budget 2017 proposes investments that will underscore Canada’s commitment to innovation and leadership in space. Budget 2017 proposes to provide $80.9 million on a cash basis over five years, starting in 2017–18, for new projects through the Canadian Space Agency that will demonstrate and utilize Canadian innovations in space, including in the field of quantum technology as well as for Mars surface observation. The latter project will enable Canada to join the National Aeronautics and Space Administration’s (NASA’s) next Mars Orbiter Mission.

Quantum Information

The development of new quantum technologies has the potential to transform markets, create new industries and produce leading-edge jobs. The Institute for Quantum Computing is a world-leading Canadian research facility that furthers our understanding of these innovative technologies. Budget 2017 proposes to provide the Institute with renewed funding of $10 million over two years, starting in 2017–18.

Social Innovation

Through community-college partnerships, the Community and College Social Innovation Fund fosters positive social outcomes, such as the integration of vulnerable populations into Canadian communities. Following the success of this pilot program, Budget 2017 proposes to invest $10 million over two years, starting in 2017–18, to continue this work.

International Research Collaborations

The Canadian Institute for Advanced Research (CIFAR) connects Canadian researchers with collaborative research networks led by eminent Canadian and international researchers on topics that touch all humanity. Past collaborations facilitated by CIFAR are credited with fostering Canada’s leadership in artificial intelligence and deep learning. Budget 2017 proposes to provide renewed and enhanced funding of $35 million over five years, starting in 2017–18.

Earlier this week, I highlighted Canada’s strength in the field of regenerative medicine, specifically stem cells in a March 21, 2017 posting. The $6M in the current budget doesn’t look like increased funding but rather a one-year extension. I’m sure they’re happy to receive it  but I imagine it’s a little hard to plan major research projects when you’re not sure how long your funding will last.

As for Canadian leadership in artificial intelligence, that was news to me. Here’s more from the budget,

Canada a Pioneer in Deep Learning in Machines and Brains

CIFAR’s Learning in Machines & Brains program has shaken up the field of artificial intelligence by pioneering a technique called “deep learning,” a computer technique inspired by the human brain and neural networks, which is now routinely used by the likes of Google and Facebook. The program brings together computer scientists, biologists, neuroscientists, psychologists and others, and the result is rich collaborations that have propelled artificial intelligence research forward. The program is co-directed by one of Canada’s foremost experts in artificial intelligence, the Université de Montréal’s Yoshua Bengio, and for his many contributions to the program, the University of Toronto’s Geoffrey Hinton, another Canadian leader in this field, was awarded the title of Distinguished Fellow by CIFAR in 2014.

Meanwhile, from chapter 1 of the budget in the subsection titled “Preparing for the Digital Economy,” there is this provision for children,

Providing educational opportunities for digital skills development to Canadian girls and boys—from kindergarten to grade 12—will give them the head start they need to find and keep good, well-paying, in-demand jobs. To help provide coding and digital skills education to more young Canadians, the Government intends to launch a competitive process through which digital skills training organizations can apply for funding. Budget 2017 proposes to provide $50 million over two years, starting in 2017–18, to support these teaching initiatives.

I wonder if BC Premier Christy Clark is heaving a sigh of relief. At the 2016 #BCTECH Summit, she announced that students in BC would learn to code at school and in newly enhanced coding camp programmes (see my Jan. 19, 2016 posting). Interestingly, there was no mention of additional funding to support her initiative. I guess this money from the federal government comes at a good time as we will have a provincial election later this spring where she can announce the initiative again and, this time, mention there’s money for it.

Attracting brains from afar

Ivan Semeniuk in his March 23, 2017 article (for the Globe and Mail) reads between the lines to analyze the budget’s possible impact on Canadian science,

But a between-the-lines reading of the budget document suggests the government also has another audience in mind: uneasy scientists from the United States and Britain.

The federal government showed its hand at the 2017 #BCTECH Summit. From a March 16, 2017 article by Meera Bains for the CBC news online,

At the B.C. tech summit, Navdeep Bains, Canada’s minister of innovation, said the government will act quickly to fast track work permits to attract highly skilled talent from other countries.

“We’re taking the processing time, which takes months, and reducing it to two weeks for immigration processing for individuals [who] need to come here to help companies grow and scale up,” Bains said.

“So this is a big deal. It’s a game changer.”

That change will happen through the Global Talent Stream, a new program under the federal government’s temporary foreign worker program.  It’s scheduled to begin on June 12, 2017.

U.S. companies are taking notice and a Canadian firm, True North, is offering to help them set up shop.

“What we suggest is that they think about moving their operations, or at least a chunk of their operations, to Vancouver, set up a Canadian subsidiary,” said the company’s founder, Michael Tippett.

“And that subsidiary would be able to house and accommodate those employees.”

Industry experts says while the future is unclear for the tech sector in the U.S., it’s clear high tech in B.C. is gearing up to take advantage.

US business attempts to take advantage of Canada’s relative stability and openness to immigration would seem to be the motive for at least one cross border initiative, the Cascadia Urban Analytics Cooperative. From my Feb. 28, 2017 posting,

There was some big news about the smallest version of the Cascadia region on Thursday, Feb. 23, 2017 when the University of British Columbia (UBC) , the University of Washington (state; UW), and Microsoft announced the launch of the Cascadia Urban Analytics Cooperative. From the joint Feb. 23, 2017 news release (read on the UBC website or read on the UW website),

In an expansion of regional cooperation, the University of British Columbia and the University of Washington today announced the establishment of the Cascadia Urban Analytics Cooperative to use data to help cities and communities address challenges from traffic to homelessness. The largest industry-funded research partnership between UBC and the UW, the collaborative will bring faculty, students and community stakeholders together to solve problems, and is made possible thanks to a $1-million gift from Microsoft.

…

Today’s announcement follows last September’s [2016] Emerging Cascadia Innovation Corridor Conference in Vancouver, B.C. The forum brought together regional leaders for the first time to identify concrete opportunities for partnerships in education, transportation, university research, human capital and other areas.

A Boston Consulting Group study unveiled at the conference showed the region between Seattle and Vancouver has “high potential to cultivate an innovation corridor” that competes on an international scale, but only if regional leaders work together. The study says that could be possible through sustained collaboration aided by an educated and skilled workforce, a vibrant network of research universities and a dynamic policy environment.

It gets better, it seems Microsoft has been positioning itself for a while if Matt Day’s analysis is correct (from my Feb. 28, 2017 posting),

Matt Day in a Feb. 23, 2017 article for the The Seattle Times provides additional perspective (Note: Links have been removed),

Microsoft’s effort to nudge Seattle and Vancouver, B.C., a bit closer together got an endorsement Thursday [Feb. 23, 2017] from the leading university in each city.

…

The partnership has its roots in a September [2016] conference in Vancouver organized by Microsoft’s public affairs and lobbying unit [emphasis mine.] That gathering was aimed at tying business, government and educational institutions in Microsoft’s home region in the Seattle area closer to its Canadian neighbor.

Microsoft last year [2016] opened an expanded office in downtown Vancouver with space for 750 employees, an outpost partly designed to draw to the Northwest more engineers than the company can get through the U.S. guest worker system [emphasis mine].

This was all prior to President Trump’s legislative moves in the US, which have at least one Canadian observer a little more gleeful than I’m comfortable with. From a March 21, 2017 article by Susan Lum  for CBC News online,

U.S. President Donald Trump’s efforts to limit travel into his country while simultaneously cutting money from science-based programs provides an opportunity for Canada’s science sector, says a leading Canadian researcher.

“This is Canada’s moment. I think it’s a time we should be bold,” said Alan Bernstein, president of CIFAR [which on March 22, 2017 was awarded $125M to launch the Pan Canada Artificial Intelligence Strategy in the Canadian federal budget announcement], a global research network that funds hundreds of scientists in 16 countries.

Bernstein believes there are many reasons why Canada has become increasingly attractive to scientists around the world, including the political climate in the United States and the Trump administration’s travel bans.

Thankfully, Bernstein calms down a bit,

“It used to be if you were a bright young person anywhere in the world, you would want to go to Harvard or Berkeley or Stanford, or what have you. Now I think you should give pause to that,” he said. “We have pretty good universities here [emphasis mine]. We speak English. We’re a welcoming society for immigrants.”​

…

Bernstein cautions that Canada should not be seen to be poaching scientists from the United States — but there is an opportunity.

“It’s as if we’ve been in a choir of an opera in the back of the stage and all of a sudden the stars all left the stage. And the audience is expecting us to sing an aria. So we should sing,” Bernstein said.

Bernstein said the federal government, with this week’s so-called innovation budget, can help Canada hit the right notes.

“Innovation is built on fundamental science, so I’m looking to see if the government is willing to support, in a big way, fundamental science in the country.”

Pretty good universities, eh? Thank you, Dr. Bernstein, for keeping some of the boosterism in check. Let’s leave the chest thumping to President Trump and his cronies.

Ivan Semeniuk’s March 23, 2017 article (for the Globe and Mail) provides more details about the situation in the US and in Britain,

Last week, Donald Trump’s first budget request made clear the U.S. President would significantly reduce or entirely eliminate research funding in areas such as climate science and renewable energy if permitted by Congress. Even the National Institutes of Health, which spearheads medical research in the United States and is historically supported across party lines, was unexpectedly targeted for a $6-billion (U.S.) cut that the White House said could be achieved through “efficiencies.”

In Britain, a recent survey found that 42 per cent of academics were considering leaving the country over worries about a less welcoming environment and the loss of research money that a split with the European Union is expected to bring.

In contrast, Canada’s upbeat language about science in the budget makes a not-so-subtle pitch for diversity and talent from abroad, including $117.6-million to establish 25 research chairs with the aim of attracting “top-tier international scholars.”

For good measure, the budget also includes funding for science promotion and $2-million annually for Canada’s yet-to-be-hired Chief Science Advisor, whose duties will include ensuring that government researchers can speak freely about their work.

“What we’ve been hearing over the last few months is that Canada is seen as a beacon, for its openness and for its commitment to science,” said Ms. Duncan [Kirsty Duncan, Minister of Science], who did not refer directly to either the United States or Britain in her comments.

Providing a less optimistic note, Erica Alini in her March 22, 2017 online article for Global News mentions a perennial problem, the Canadian brain drain,

The budget includes a slew of proposed reforms and boosted funding for existing training programs, as well as new skills-development resources for unemployed and underemployed Canadians not covered under current EI-funded programs.

There are initiatives to help women and indigenous people get degrees or training in science, technology, engineering and mathematics (the so-called STEM subjects) and even to teach kids as young as kindergarten-age to code.

But there was no mention of how to make sure Canadians with the right skills remain in Canada, TD’s DePratto {Toronto Dominion Bank} Economics; TD is currently experiencing a scandal {March 13, 2017 Huffington Post news item}] told Global News.

Canada ranks in the middle of the pack compared to other advanced economies when it comes to its share of its graduates in STEM fields, but the U.S. doesn’t shine either, said DePratto [Brian DePratto, senior economist at TD .

The key difference between Canada and the U.S. is the ability to retain domestic talent and attract brains from all over the world, he noted.

To be blunt, there may be some opportunities for Canadian science but it does well to remember (a) US businesses have no particular loyalty to Canada and (b) all it takes is an election to change any perceived advantages to disadvantages.

Digital policy and intellectual property issues

Dubbed by some as the ‘innovation’ budget (official title:  Building a Strong Middle Class), there is an attempt to address a longstanding innovation issue (from a March 22, 2017 posting by Michael Geist on his eponymous blog (Note: Links have been removed),

The release of today’s [march 22, 2017] federal budget is expected to include a significant emphasis on innovation, with the government revealing how it plans to spend (or re-allocate) hundreds of millions of dollars that is intended to support innovation. Canada’s dismal innovation record needs attention, but spending our way to a more innovative economy is unlikely to yield the desired results. While Navdeep Bains, the Innovation, Science and Economic Development Minister, has talked for months about the importance of innovation, Toronto Star columnist Paul Wells today delivers a cutting but accurate assessment of those efforts:

“This government is the first with a minister for innovation! He’s Navdeep Bains. He frequently posts photos of his meetings on Twitter, with the hashtag “#innovation.” That’s how you know there is innovation going on. A year and a half after he became the minister for #innovation, it’s not clear what Bains’s plans are. It’s pretty clear that within the government he has less than complete control over #innovation. There’s an advisory council on economic growth, chaired by the McKinsey guru Dominic Barton, which periodically reports to the government urging more #innovation.

There’s a science advisory panel, chaired by former University of Toronto president David Naylor, that delivered a report to Science Minister Kirsty Duncan more than three months ago. That report has vanished. One presumes that’s because it offered some advice. Whatever Bains proposes, it will have company.”

Wells is right. Bains has been very visible with plenty of meetings and public photo shoots but no obvious innovation policy direction. This represents a missed opportunity since Bains has plenty of policy tools at his disposal that could advance Canada’s innovation framework without focusing on government spending.

For example, Canada’s communications system – wireless and broadband Internet access – falls directly within his portfolio and is crucial for both business and consumers. Yet Bains has been largely missing in action on the file. He gave approval for the Bell – MTS merger that virtually everyone concedes will increase prices in the province and make the communications market less competitive. There are potential policy measures that could bring new competitors into the market (MVNOs [mobile virtual network operators] and municipal broadband) and that could make it easier for consumers to switch providers (ban on unlocking devices). Some of this falls to the CRTC, but government direction and emphasis would make a difference.

Even more troubling has been his near total invisibility on issues relating to new fees or taxes on Internet access and digital services. Canadian Heritage Minister Mélanie Joly has taken control of the issue with the possibility that Canadians could face increased costs for their Internet access or digital services through mandatory fees to contribute to Canadian content.  Leaving aside the policy objections to such an approach (reducing affordable access and the fact that foreign sources now contribute more toward Canadian English language TV production than Canadian broadcasters and distributors), Internet access and e-commerce are supposed to be Bains’ issue and they have a direct connection to the innovation file. How is it possible for the Innovation, Science and Economic Development Minister to have remained silent for months on the issue?

Bains has been largely missing on trade related innovation issues as well. My Globe and Mail column today focuses on a digital-era NAFTA, pointing to likely U.S. demands on data localization, data transfers, e-commerce rules, and net neutrality.  These are all issues that fall under Bains’ portfolio and will impact investment in Canadian networks and digital services. There are innovation opportunities for Canada here, but Bains has been content to leave the policy issues to others, who will be willing to sacrifice potential gains in those areas.

Intellectual property policy is yet another area that falls directly under Bains’ mandate with an obvious link to innovation, but he has done little on the file. Canada won a huge NAFTA victory late last week involving the Canadian patent system, which was challenged by pharmaceutical giant Eli Lilly. Why has Bains not promoted the decision as an affirmation of how Canada’s intellectual property rules?

On the copyright front, the government is scheduled to conduct a review of the Copyright Act later this year, but it is not clear whether Bains will take the lead or again cede responsibility to Joly. The Copyright Act is statutorily under the Industry Minister and reform offers the chance to kickstart innovation. …

For anyone who’s not familiar with this area, innovation is often code for commercialization of science and technology research efforts. These days, digital service and access policies and intellectual property policies are all key to research and innovation efforts.

The country that’s most often (except in mainstream Canadian news media) held up as an example of leadership in innovation is Estonia. The Economist profiled the country in a July 31, 2013 article and a July 7, 2016 article on apolitical.co provides and update.

Conclusions

Science monies for the tri-council science funding agencies (NSERC, SSHRC, and CIHR) are more or less flat but there were a number of line items in the federal budget which qualify as science funding. The $221M over five years for Mitacs, the $125M for the Pan-Canadian Artificial Intelligence Strategy, additional funding for the Canada research chairs, and some of the digital funding could also be included as part of the overall haul. This is in line with the former government’s (Stephen Harper’s Conservatives) penchant for keeping the tri-council’s budgets under control while spreading largesse elsewhere (notably the Perimeter Institute, TRIUMF [Canada’s National Laboratory for Particle and Nuclear Physics], and, in the 2015 budget, $243.5-million towards the Thirty Metre Telescope (TMT) — a massive astronomical observatory to be constructed on the summit of Mauna Kea, Hawaii, a $1.5-billion project). This has lead to some hard feelings in the past with regard to ‘big science’ projects getting what some have felt is an undeserved boost in finances while the ‘small fish’ are left scrabbling for the ever-diminishing (due to budget cuts in years past and inflation) pittances available from the tri-council agencies.

Mitacs, which started life as a federally funded Network Centre for Excellence focused on mathematics, has since shifted focus to become an innovation ‘champion’. You can find Mitacs here and you can find the organization’s March 2016 budget submission to the House of Commons Standing Committee on Finance here. At the time, they did not request a specific amount of money; they just asked for more.

The amount Mitacs expects to receive this year is over $40M which represents more than double what they received from the federal government and almost of 1/2 of their total income in the 2015-16 fiscal year according to their 2015-16 annual report (see p. 327 for the Mitacs Statement of Operations to March 31, 2016). In fact, the federal government forked over $39,900,189. in the 2015-16 fiscal year to be their largest supporter while Mitacs’ total income (receipts) was $81,993,390.

It’s a strange thing but too much money, etc. can be as bad as too little. I wish the folks Mitacs nothing but good luck with their windfall.

I don’t see anything in the budget that encourages innovation and investment from the industrial sector in Canada.

Finallyl, innovation is a cultural issue as much as it is a financial issue and having worked with a number of developers and start-up companies, the most popular business model is to develop a successful business that will be acquired by a large enterprise thereby allowing the entrepreneurs to retire before the age of 30 (or 40 at the latest). I don’t see anything from the government acknowledging the problem let alone any attempts to tackle it.

All in all, it was a decent budget with nothing in it to seriously offend anyone.

New principles for AI (artificial intelligence) research along with some history and a plea for a democratic discussion

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For almost a month I’ve been meaning to get to this Feb. 1, 2017 essay by Andrew Maynard (director of Risk Innovation Lab at Arizona State University) and Jack Stilgoe (science policy lecturer at University College London [UCL]) on the topic of artificial intelligence and principles (Note: Links have been removed). First, a walk down memory lane,

Today [Feb. 1, 2017] in Washington DC, leading US and UK scientists are meeting to share dispatches from the frontiers of machine learning – an area of research that is creating new breakthroughs in artificial intelligence (AI). Their meeting follows the publication of a set of principles for beneficial AI that emerged from a conference earlier this year at a place with an important history.

In February 1975, 140 people – mostly scientists, with a few assorted lawyers, journalists and others – gathered at a conference centre on the California coast. A magazine article from the time by Michael Rogers, one of the few journalists allowed in, reported that most of the four days’ discussion was about the scientific possibilities of genetic modification. Two years earlier, scientists had begun using recombinant DNA to genetically modify viruses. The Promethean nature of this new tool prompted scientists to impose a moratorium on such experiments until they had worked out the risks. By the time of the Asilomar conference, the pent-up excitement was ready to burst. It was only towards the end of the conference when a lawyer stood up to raise the possibility of a multimillion-dollar lawsuit that the scientists focussed on the task at hand – creating a set of principles to govern their experiments.

The 1975 Asilomar meeting is still held up as a beacon of scientific responsibility. However, the story told by Rogers, and subsequently by historians, is of scientists motivated by a desire to head-off top down regulation with a promise of self-governance. Geneticist Stanley Cohen said at the time, ‘If the collected wisdom of this group doesn’t result in recommendations, the recommendations may come from other groups less well qualified’. The mayor of Cambridge, Massachusetts was a prominent critic of the biotechnology experiments then taking place in his city. He said, ‘I don’t think these scientists are thinking about mankind at all. I think that they’re getting the thrills and the excitement and the passion to dig in and keep digging to see what the hell they can do’.

The concern in 1975 was with safety and containment in research, not with the futures that biotechnology might bring about. A year after Asilomar, Cohen’s colleague Herbert Boyer founded Genentech, one of the first biotechnology companies. Corporate interests barely figured in the conversations of the mainly university scientists.

Fast-forward 42 years and it is clear that machine learning, natural language processing and other technologies that come under the AI umbrella are becoming big business. The cast list of the 2017 Asilomar meeting included corporate wunderkinds from Google, Facebook and Tesla as well as researchers, philosophers, and other academics. The group was more intellectually diverse than their 1975 equivalents, but there were some notable absences – no public and their concerns, no journalists, and few experts in the responsible development of new technologies.

Maynard and Stilgoe offer a critique of the latest principles,

The principles that came out of the meeting are, at least at first glance, a comforting affirmation that AI should be ‘for the people’, and not to be developed in ways that could cause harm. They promote the idea of beneficial and secure AI, development for the common good, and the importance of upholding human values and shared prosperity.

This is good stuff. But it’s all rather Motherhood and Apple Pie: comforting and hard to argue against, but lacking substance. The principles are short on accountability, and there are notable absences, including the need to engage with a broader set of stakeholders and the public. At the early stages of developing new technologies, public concerns are often seen as an inconvenience. In a world in which populism appears to be trampling expertise into the dirt, it is easy to understand why scientists may be defensive.

I encourage you to read this thoughtful essay in its entirety although I do have one nit to pick:  Why only US and UK scientists? I imagine the answer may lie in funding and logistics issues but I find it surprising that the critique makes no mention of the international community as a nod to inclusion.

For anyone interested in the Asolimar AI principles (2017), you can find them here. You can also find videos of the two-day workshop (Jan. 31 – Feb. 1, 2017 workshop titled The Frontiers of Machine Learning (a Raymond and Beverly Sackler USA-UK Scientific Forum [US National Academy of Sciences]) here (videos for each session are available on Youtube).

Spintronics-based artificial intelligence

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Courtesy: Tohoku University

Japanese researchers have managed to mimic a synapse (artificial neural network) with a spintronics-based device according to a Dec. 19, 2016 Tohoku University press release (also on EurekAlert but dated Dec. 20, 2016),

Researchers at Tohoku University have, for the first time, successfully demonstrated the basic operation of spintronics-based artificial intelligence.

Artificial intelligence, which emulates the information processing function of the brain that can quickly execute complex and complicated tasks such as image recognition and weather prediction, has attracted growing attention and has already been partly put to practical use.

The currently-used artificial intelligence works on the conventional framework of semiconductor-based integrated circuit technology. However, this lacks the compactness and low-power feature of the human brain. To overcome this challenge, the implementation of a single solid-state device that plays the role of a synapse is highly promising.

The Tohoku University research group of Professor Hideo Ohno, Professor Shigeo Sato, Professor Yoshihiko Horio, Associate Professor Shunsuke Fukami and Assistant Professor Hisanao Akima developed an artificial neural network in which their recently-developed spintronic devices, comprising micro-scale magnetic material, are employed (Fig. 1). The used spintronic device is capable of memorizing arbitral values between 0 and 1 in an analogue manner unlike the conventional magnetic devices, and thus perform the learning function, which is served by synapses in the brain.

Using the developed network (Fig. 2), the researchers examined an associative memory operation, which is not readily executed by conventional computers. Through the multiple trials, they confirmed that the spintronic devices have a learning ability with which the developed artificial neural network can successfully associate memorized patterns (Fig. 3) from their input noisy versions just like the human brain can.

The proof-of-concept demonstration in this research is expected to open new horizons in artificial intelligence technology – one which is of a compact size, and which simultaneously achieves fast-processing capabilities and ultralow-power consumption. These features should enable the artificial intelligence to be used in a broad range of societal applications such as image/voice recognition, wearable terminals, sensor networks and nursing-care robots.

Here are Fig. 1 and Fig. 2, as mentioned in the press release,

Fig. 1. (a) Optical photograph of a fabricated spintronic device that serves as artificial synapse in the present demonstration. Measurement circuit for the resistance switching is also shown. (b) Measured relation between the resistance of the device and applied current, showing analogue-like resistance variation. (c) Photograph of spintronic device array mounted on a ceramic package, which is used for the developed artificial neural network. Courtesy: Tohoku University

Fig. 2. Block diagram of developed artificial neural network, consisting of PC, FPGA, and array of spintronics (spin-orbit torque; SOT) devices. Courtesy: Tohoku University

Here`s a link to and a citation for the paper,

Analogue spin–orbit torque device for artificial-neural-network-based associative memory operation by William A. Borders, Hisanao Akima1, Shunsuke Fukami, Satoshi Moriya, Shouta Kurihara, Yoshihiko Horio, Shigeo Sato, and Hideo Ohno. Applied Physics Express, Volume 10, Number 1 https://doi.org/10.7567/APEX.10.013007. Published 20 December 2016

© 2017 The Japan Society of Applied Physics

This is an open access paper.

For anyone interested in my other posts on memristors, artificial brains, and artificial intelligence, you can search this blog for those terms  and/or Neuromorphic Engineering in the Categories section.

Maths gallery at the UK’s Science Museum takes flight

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Mathematics: The Winton Gallery at the Science Museum, Zaha Hadid Architects’ only permanent public museum exhibition design. London. Photograph: Nicholas Guttridge/NIck Guttridge

This exhibition looks great in the picture, I wonder what the experience is like. Alex Bellos is certainly enthusiastic in his Dec. 7, 2016 posting on the Guardian’s website,

Mathematics underlies all science, so for a science museum to be worthy of the name, maths needs to included somewhere. Yet maths, which deals mainly in abstract objects, is [a] challenge for museums, which necessarily contain physical ones. The Science Museum’s approach in its new gallery is to tell historical stories about the influence of mathematics in the real world, rather than actually focussing directly on the mathematical ideas involved. The result is a stunning gallery, with fascinating objects beautifully laid out, yet which eschews explaining any maths. (If you want to learn simple mathematical ideas, you can always head to the museum’s new interactive gallery, Wonderlab).

Much of the attention on Mathematics: The Winton Gallery – the main funders are David Harding, founder and CEO of investment firm Winton, and his wife Claudia – has been on Zaha Hadid’s design. The gallery is the first UK project by Zaha Hadid Architects to open since her unexpected death in March [2016], and the only permanent public museum exhibition she designed. Her first degree was in maths, before she turned to architecture.

Hanging from the ceiling is an aeroplane – the Handley Page ‘Gugnunc’, built in 1929 for a competition to build safe aircraft – and surrounding it is a swirly ceiling sculpture that represents the mathematical equations that describe airflow. In fact, the entire gallery follows the contours of the flow, providing the positions of the cabinets below.

…

The Science Museum’s previous maths gallery, which had not been updated in decades, contained about 600 objects, including cabinets crammed with geometrical objects and many examples of the same thing, such as medieval slide rules or Victorian curve-drawing machines. The new gallery has less than a quarter of that number of objects in the same space.

Every object now is in its own cabinet, and the extra space means you can walk around them from all angles, as well as making the gallery feel more manageable. Rather than being bombarded with stuff, you are given a single object to contemplate that tells part of a wider story.

In a section on “form and beauty”, there is a modern replica of a 1920s chair based on French architect’s Le Corbusier’s Modulor system of proportions, and two J W Turner sketches from his Royal Academy lectures on perspective.

The section “trade and travel” has a 3-metre long replica of the 1973 Globtik Tokyo oil tanker, then the largest ship in the world. In its massive cabinet it looks as terrifying as a Damien Hirst shark. The maths link? Because British mathematician William Froode a century before had worked out that bulbous bows were better than sharp bows at the fronts of boats and ships.

…

The new maths gallery is a wonderfully attractive space, full of interesting and thought-provoking objects, and a very welcome addition [geddit?] to London’s museums. Go!

A Dec. 8 (?), 2016 [London, UK] Science Museum press release is the first example I’ve seen of the funders being highlighted quite so prominently, i.e., before the press release proper,

Mathematics: The Winton Gallery designed by Zaha Hadid Architects opens at the Science Museum

  • A stunning new permanent gallery that reveals the importance of mathematics in all our lives through remarkable historical artefacts, stories and design
  • Free to visit and open daily from 8 December 2016
  • The only permanent public museum exhibition designed by Zaha Hadid anywhere in the world

Principal Funder: David and Claudia Harding
Principal Sponsor: Samsung
Major Sponsor: MathWorks

On 8 December 2016 the Science Museum will open an inspirational new mathematics gallery, designed by Zaha Hadid Architects.

Mathematics: The Winton Gallery brings together remarkable stories, historical artefacts and design to highlight the central role of mathematical practice in all our lives, and explores how mathematicians, their tools and ideas have helped build the modern world over the past four centuries.

More than 100 treasures from the Science Museum’s world-class science, technology, engineering and mathematics collections have been selected to tell powerful stories about how mathematics has shaped, and been shaped by, some of our most fundamental human concerns – from trade and travel to war, peace, life, death, form and beauty.

Curator Dr David Rooney said, ‘At its heart this gallery reveals a rich cultural story of human endeavour that has helped transform the world over the last four hundred years. Mathematical practice underpins so many aspects of our lives and work, and we hope that bringing together these remarkable stories, people and exhibits will inspire visitors to think about the role of mathematics in a new light.’

Positioned at the centre of the gallery is the Handley Page ‘Gugnunc’ aeroplane, built in 1929 for a competition to construct safe aircraft. Ground-breaking aerodynamic research influenced the wing design of this experimental aeroplane, helping to shift public opinion about the safety of flying and to secure the future of the aviation industry. This aeroplane encapsulates the gallery’s overarching theme, illustrating how mathematical practice has helped solve real-world problems and in this instance paved the way for the safe passenger flights that we rely on today.

Mathematics also defines Zaha Hadid Architects’ enlightening design for the gallery. Inspired by the Handley Page aircraft, the design is driven by equations of airflow used in the aviation industry. The layout and lines of the gallery represent the air that would have flowed around this historic aircraft in flight, from the positioning of the showcases and benches to the three-dimensional curved surfaces of the central pod structure.

Mathematics: The Winton Gallery is the first permanent public museum exhibition designed by Zaha Hadid Architects anywhere in the world. The gallery is also the first of Zaha Hadid Architects’ projects to open in the UK since Dame Zaha Hadid’s sudden death in March 2016. The late Dame Zaha first became interested in geometry while studying mathematics at university. Mathematics and geometry have a strong connection with architecture and she continued to examine these relationships throughout each of her projects; with mathematics always central to her work. As Dame Zaha said, ‘When I was growing up in Iraq, math was an everyday part of life. We would play with math problems just as we would play with pens and paper to draw – math was like sketching.’

Ian Blatchford, Director of the Science Museum Group, said, ‘We were hugely impressed by the ideas and vision of the late Dame Zaha Hadid and Patrik Schumacher when they first presented their design for the new mathematics gallery over two years ago. It was a terrible shock for us all when Dame Zaha died suddenly in March this year, but I am sure that this gallery will be a lasting tribute to this world-changing architect and provide inspiration for our millions of visitors for many years to come.’

From a beautiful 17th century Islamic astrolabe that uses ancient mathematical techniques to map the night sky, to an early example of the famous Enigma machine, designed to resist even the most advanced mathematical techniques for code breaking during the Second World War, each historic object within the gallery has an important story to tell. Archive photography and film helps to capture these stories, and introduces the wide range of people who made, used or were impacted by each mathematical device or idea.

Some instruments and objects within the gallery clearly reference their mathematical origin. Others may surprise visitors and appear rooted in other disciplines, from classical architecture to furniture design. Visitors will see a box of glass eyes used by Francis Galton in his 1884 Anthropometric Laboratory to help measure the physical characteristics of the British public and develop statistics to support a wider social and political movement he termed ‘eugenics’. On the other side of the gallery is the pioneering Wisard pattern-recognition machine built in 1981 to attempt to re-create the ‘neural networks’ of the brain. This early Artificial Intelligence machine worked, until 1995, on a variety of projects, from banknote recognition to voice analysis, and from foetal growth monitoring in hospitals to covert surveillance for the Home Office.

A richly illustrated book has been published by Scala to accompany the new gallery. Mathematics: How it Shaped Our World, written by David Rooney, expands on the themes and stories that are celebrated in the gallery itself and includes a series of newly commissioned essays written by world-leading experts in the history and modern practice of mathematics.

David Harding, Principal Funder of the gallery and Founder and CEO of Winton said, ‘Mathematics, whilst difficult for many, is incredibly useful. To those with an aptitude for it, it is also beautiful. I’m delighted that this gallery will be both useful and beautiful.’

Mathematics: The Winton Gallery is free to visit and open daily from 8 December 2016. The gallery has been made possible through an unprecedented donation from long-standing supporters of science, David and Claudia Harding. It has also received generous support from Samsung as Principal Sponsor, MathWorks as Major Sponsor, with additional support from Adrian and Jacqui Beecroft, Iain and Jane Bratchie, the Keniston-Cooper Charitable Trust, Dr Martin Schoernig, Steve Mobbs and Pauline Thomas.

After the press release, there is the most extensive list of ‘Abouts’ I’ve seen yet (Note: This includes links to the Science Museum and other agencies),

About the Science Museum
The Science Museum’s world-class collection forms an enduring record of scientific, technological and medical achievements from across the globe. Welcoming over 3 million visitors a year, the Museum aims to make sense of the science that shapes our lives, inspiring visitors with iconic objects, award-winning exhibitions and incredible stories of scientific achievement. More information can be found at sciencemuseum.org.uk

About Curator David Rooney
Mathematics: The Winton Gallery has been curated by Dr David Rooney, who was responsible for the award-winning 2012 Science Museum exhibition Codebreaker: Alan Turing’s Life and Legacy as well as developing galleries on time and navigation at the National Maritime Museum, Greenwich. David writes and speaks widely on the history of technology and engineering. His critically acclaimed first book, Ruth Belville: The Greenwich Time Lady, was described by Jonathan Meades as ‘an engrossing and eccentric slice of London history’, and by the Daily Telegraph as ‘a gem of a book’. He has recently authored Mathematics: How It Shaped Our World, to accompany the new mathematics gallery, and is currently writing a political history of traffic.

About David and Claudia Harding
David and Claudia Harding are associated with Winton, one of the world’s leading quantitative investment management firms which David founded in 1997. Winton uses mathematical and scientific methods to devise, evaluate and execute investment ideas on behalf of clients all over the world. A British-based company, Winton and David and Claudia Harding have donated to numerous scientific and mathematical causes in the UK and internationally, including Cambridge University, the Crick Institute, the Max Planck Institute, and the Science Museum. The main themes of their philanthropy have been supporting basic scientific research and the communication of scientific ideas. David and Claudia reside in London.

About Samsung’s Citizenship Programmes
Samsung is committed to help close the digital divide and skills gap in the UK. Samsung Digital Classrooms in schools, charities/non-profit organisations and cultural partners provide access to the latest technology. Samsung is also providing the training and maintenance support necessary to help make the transition and integration of the new technology as smooth as possible. Samsung also offers qualifications and training in technology for young people and teachers through its Digital Academies. These initiatives will inspire young people, staff and teachers to learn and teach in new exciting ways and to help encourage young people into careers using technology. Find out more

About MathWorks
MathWorks is the leading developer of mathematical computing software. MATLAB, the language of technical computing, is a programming environment for algorithm development, data analysis, visualisation, and numeric computation. Simulink is a graphical environment for simulation and Model-Based Design for multidomain dynamic and embedded systems. Engineers and scientists worldwide rely on these product families to accelerate the pace of discovery, innovation, and development in automotive, aerospace, electronics, financial services, biotech-pharmaceutical, and other industries. MATLAB and Simulink are also fundamental teaching and research tools in the world’s universities and learning institutions. Founded in 1984, MathWorks employs more than 3000 people in 15 countries, with headquarters in Natick, Massachusetts, USA. For additional information, visit mathworks.com

About Zaha Hadid Architects
Zaha Hadid founded Zaha Hadid Architects (ZHA) in 1979. Each of ZHA’s projects builds on over thirty years of exploration and research in the interrelated fields of urbanism, architecture and design. Hadid’s pioneering vision redefined architecture for the 21st century and captured imaginations across the globe. Her legacy is embedded within the DNA of the design studio she created as ZHA’s projects combine the unwavering belief in the power of invention with concepts of connectivity and fluidity.

ZHA is currently working on a diversity of projects worldwide including the new Beijing Airport Terminal Building in Daxing, China, the Sleuk Rith Institute in Phnom Penh, Cambodia and 520 West 28th Street in New York City, USA. The practice’s portfolio includes cultural, academic, sporting, residential, and transportation projects across six continents.

About Discover South Kensington
Discover South Kensington brings together the Science Museum and other leading cultural and educational organisations to promote innovation and learning. South Kensington is the home of science, arts and inspiration. Discovery is at the core of what happens here and there is so much to explore every day. discoversouthken.com

About Zaha Hadid: Early Paintings and Drawings at the Serpentine Sackler Gallery
This week an exhibition of paintings and drawings by Zaha Hadid will open at the Serpentine Galleries that will reveal her as an artist with drawing at the very heart of her work. It will include calligraphic drawings and rarely seen private notebooks, showing her complex thoughts about architecture’s forms and relationship to the world we live in. Zaha Hadid: Early Paintings and Drawings at the Serpentine Sackler Gallery is free to visit and runs from 8th December 2016 – 12th February 2017.

I found the mentions of Zaha Hadid fascinating and so I looked her up on Wikipedia, where I found this (Note: Links have been removed),

Dame Zaha Mohammad Hadid, DBE (Arabic: زها حديد‎‎ Zahā Ḥadīd; 31 October 1950 – 31 March 2016) was an Iraqi-born British architect. She was the first woman to receive the Pritzker Architecture Prize, in 2004.[1] She received the UK’s most prestigious architectural award, the Stirling Prize, in 2010 and 2011. In 2012, she was made a Dame by Elizabeth II for services to architecture, and in 2015 she became the first woman to be awarded the Royal Gold Medal from the Royal Institute of British Architects.[2]

She was dubbed by The Guardian as the ‘Queen of the curve’.[3] She liberated architectural geometry[4] with the creation of highly expressive, sweeping fluid forms of multiple perspective points and fragmented geometry that evoke the chaos and flux of modern life.[5] A pioneer of parametricism, and an icon of neo-futurism, with a formidable personality, her acclaimed work and ground-breaking forms include the aquatic centre for the London 2012 Olympics, the Broad Art Museum in the US, and the Guangzhou Opera House in China.[6] At the time of her death in 2016, Zaha Hadid Architects in London was the fastest growing British architectural firm.[7] Many of her designs are to be released posthumously, ranging in variation from the 2017 Brit Awards statuette to a 2022 FIFA World Cup stadium.[8][9]

…

Dubbed ‘Queen of the curve’, Hadid has a reputation as the world’s top female architect,[3][62][63][64][65] although her reputation is not without criticism. She is considered an architect of unconventional thinking, whose buildings are organic, dynamic and sculptural.[66][67] Stanton and others also compliment her on her unique organic designs: “One of the main characteristics of her work is that however clearly recognizable, it can never be pigeonholed into a stylistic signature. Digital knowledge, technology-driven mutations, shapes inspired by the organic and biological world, as well as geometrical interpretation of the landscape are constant elements of her practice. Yet, the multiplicity and variety of the combination among these facets prevent the risk of self-referential solutions and repetitions.”[68] Allison Lee Palmer considers Hadid a leader of Deconstructivism in architecture, writing that, “Almost all of Hadid’s buildings appear to melt, bend, and curve into a new architectural language that defies description. Her completed buildings span the globe and include the Jockey Club Innovation Tower on the north side of the Hong Kong Polytechnic University in Hong Kong, completed in 2013, that provides Hong Kong an entry into the world stage of cutting-edge architecture by revealing a design that dissolved traditional architecture, the so called modernist “glass box,” into a shattering of windows and melting of walls to form organic structures with halls and stairways that flow through the building, pooling open into rooms and foyers.”[69]

Hadid’s architectural language has been described by some as “famously extravagant” with many of her projects sponsored by “dictator states”. [emphasis mine] [70] Rowan Moore described Hadid’s Heydar Aliyev Center as “not so different from the colossal cultural palaces long beloved of Soviet and similar regimes”. Architect Sean Griffiths characterised Hadid’s work as “an empty vessel that sucks in whatever ideology might be in proximity to it”.[71] Art historian Maike Aden criticises in particular the foreclosure of Zaha Hadid’s architecture of the MAXXI in Rome towards the public and the urban life that undermines even the most impressive program to open the museum.[72]

If you think about it, most of the world’s great monuments were built by dictators or omnipotent rulers of one country or another. Getting the money and commitment can present an ethical/moral issue for any artist or architect who has a ‘grand design’.

Artificial intelligence and industrial applications

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This is take on artificial intelligence that I haven’t encountered before. Sean Captain’s Nov. 15, 2016 article for Fast Company profiles industry giant GE (General Electric) and its foray into that world (Note: Links have been removed),

When you hear the term “artificial intelligence,” you may think of tech giants Amazon, Google, IBM, Microsoft, or Facebook. Industrial powerhouse General Electric is now aiming to be included on that short list. It may not have a chipper digital assistant like Cortana or Alexa. It won’t sort through selfies, but it will look through X-rays. It won’t recommend movies, but it will suggest how to care for a diesel locomotive. Today, GE announced a pair of acquisitions and new services that will bring machine learning AI to the kinds of products it’s known for, including planes, trains, X-ray machines, and power plants.

The effort started in 2015 when GE announced Predix Cloud—an online platform to network and collect data from sensors on industrial machinery such as gas turbines or windmills. At the time, GE touted the benefits of using machine learning to find patterns in sensor data that could lead to energy savings or preventative maintenance before a breakdown. Predix Cloud opened up to customers in February [2016?], but GE is still building up the AI capabilities to fulfill the promise. “We were using machine learning, but I would call it in a custom way,” says Bill Ruh, GE’s chief digital officer and CEO of its GE Digital business (GE calls its division heads CEOs). “And we hadn’t gotten to a general-purpose framework in machine learning.”

Today [Nov. 15, 2016] GE revealed the purchase of two AI companies that Ruh says will get them there. Bit Stew Systems, founded in 2005, was already doing much of what Predix Cloud promises—collecting and analyzing sensor data from power utilities, oil and gas companies, aviation, and factories. (GE Ventures has funded the company.) Customers include BC Hydro, Pacific Gas & Electric, and Scottish & Southern Energy.

The second purchase, Wise.io is a less obvious purchase. Founded by astrophysics and AI experts using machine learning to study the heavens, the company reapplied the tech to streamlining a company’s customer support systems, picking up clients like Pinterest, Twilio, and TaskRabbit. GE believes the technology will transfer yet again, to managing industrial machines. “I think by the middle of next year we will have a full machine learning stack,” says Ruh.

…

Though young, Predix is growing fast, with 270 partner companies using the platform, according to GE, which expects revenue on software and services to grow over 25% this year, to more than $7 billion. Ruh calls Predix a “significant part” of that extra money. And he’s ready to brag, taking a jab at IBM Watson for being a “general-purpose” machine-learning provider without the deep knowledge of the industries it serves. “We have domain algorithms, on machine learning, that’ll know what a power plant is and all the depth of that, that a general-purpose machine learning will never really understand,” he says.

…

One especially dull-sounding new Predix service—Predictive Corrosion Management—touches on a very hot political issue: giant oil and gas pipeline projects. Over 400 people have been arrested in months of protests against the Dakota Access Pipeline, which would carry crude oil from North Dakota to Illinois. The issue is very complicated, but one concern of protestors is that a pipeline rupture would contaminate drinking water for the Standing Rock Sioux reservation.

“I think absolutely this is aimed at that problem. If you look at why pipelines spill, it’s corrosion,” says Ruh. “We believe that 10 years from now, we can detect a leak before it occurs and fix it before you see it happen.” Given how political battles over pipelines drag on, 10 years might not be so long to wait.

I recommend reading the article in its entirety if you have the time. And, for those of us in British Columbia, Canada, it was a surprise to see BC Hydro on the list of customers for one of GE’s new acquisitions. As well, that business about the pipelines hits home hard given the current debates (Enbridge Northern Gateway Pipelines) here. *ETA Dec. 27, 2016: This was originally edited just prior to publication to include information about the announcement by the Trudeau cabinet approving two pipelines for TransMountain  and Enbridge respectively while rejecting the Northern Gateway pipeline (Canadian Broadcasting Corporation [CBC] online news Nov. 29, 2016).  I trust this second edit will stick.*

It seems GE is splashing out in a big way. There’s a second piece on Fast Company, a Nov. 16, 2016 article by Sean Captain (again) this time featuring a chat between an engineer and a robotic power plant,

We are entering the era of talking machines—and it’s about more than just asking Amazon’s Alexa to turn down the music. General Electric has built a digital assistant into its cloud service for managing power plants, jet engines, locomotives, and the other heavy equipment it builds. Over the internet, an engineer can ask a machine—even one hundreds of miles away—how it’s doing and what it needs. …

Voice controls are built on top of GE’s Digital Twin program, which uses sensor readings from machinery to create virtual models in cyberspace. “That model is constantly getting a stream of data, both operational and environmental,” says Colin Parris, VP at GE Software Research. “So it’s adapting itself to that type of data.” The machines live virtual lives online, allowing engineers to see how efficiently each is running and if they are wearing down.

GE partnered with Microsoft on the interface, using the Bing Speech API (the same tech powering the Cortana digital assistant), with special training on key terms like “rotor.” The twin had little trouble understanding the Mandarin Chinese accent of Bo Yu, one of the researchers who built the system; nor did it stumble on Parris’s Trinidad accent. Digital Twin will also work with Microsoft’s HoloLens mixed reality goggles, allowing someone to step into a 3D image of the equipment.

…

I can’t help wondering if there are some jobs that were eliminated with this technology.

How might artificial intelligence affect urban life in 2030? A study

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Peering into the future is always a chancy business as anyone who’s seen those film shorts from the 1950’s and 60’s which speculate exuberantly as to what the future will bring knows.

A sober approach (appropriate to our times) has been taken in a study about the impact that artificial intelligence might have by 2030. From a Sept. 1, 2016 Stanford University news release (also on EurekAlert) by Tom Abate (Note: Links have been removed),

A panel of academic and industrial thinkers has looked ahead to 2030 to forecast how advances in artificial intelligence (AI) might affect life in a typical North American city – in areas as diverse as transportation, health care and education ­– and to spur discussion about how to ensure the safe, fair and beneficial development of these rapidly emerging technologies.

Titled “Artificial Intelligence and Life in 2030,” this year-long investigation is the first product of the One Hundred Year Study on Artificial Intelligence (AI100), an ongoing project hosted by Stanford to inform societal deliberation and provide guidance on the ethical development of smart software, sensors and machines.

“We believe specialized AI applications will become both increasingly common and more useful by 2030, improving our economy and quality of life,” said Peter Stone, a computer scientist at the University of Texas at Austin and chair of the 17-member panel of international experts. “But this technology will also create profound challenges, affecting jobs and incomes and other issues that we should begin addressing now to ensure that the benefits of AI are broadly shared.”

The new report traces its roots to a 2009 study that brought AI scientists together in a process of introspection that became ongoing in 2014, when Eric and Mary Horvitz created the AI100 endowment through Stanford. AI100 formed a standing committee of scientists and charged this body with commissioning periodic reports on different aspects of AI over the ensuing century.

“This process will be a marathon, not a sprint, but today we’ve made a good start,” said Russ Altman, a professor of bioengineering and the Stanford faculty director of AI100. “Stanford is excited to host this process of introspection. This work makes practical contribution to the public debate on the roles and implications of artificial intelligence.”

The AI100 standing committee first met in 2015, led by chairwoman and Harvard computer scientist Barbara Grosz. It sought to convene a panel of scientists with diverse professional and personal backgrounds and enlist their expertise to assess the technological, economic and policy implications of potential AI applications in a societally relevant setting.

“AI technologies can be reliable and broadly beneficial,” Grosz said. “Being transparent about their design and deployment challenges will build trust and avert unjustified fear and suspicion.”

The report investigates eight domains of human activity in which AI technologies are beginning to affect urban life in ways that will become increasingly pervasive and profound by 2030.

The 28,000-word report includes a glossary to help nontechnical readers understand how AI applications such as computer vision might help screen tissue samples for cancers or how natural language processing will allow computerized systems to grasp not simply the literal definitions, but the connotations and intent, behind words.

The report is broken into eight sections focusing on applications of AI. Five examine application arenas such as transportation where there is already buzz about self-driving cars. Three other sections treat technological impacts, like the section on employment and workplace trends which touches on the likelihood of rapid changes in jobs and incomes.

“It is not too soon for social debate on how the fruits of an AI-dominated economy should be shared,” the researchers write in the report, noting also the need for public discourse.

“Currently in the United States, at least sixteen separate agencies govern sectors of the economy related to AI technologies,” the researchers write, highlighting issues raised by AI applications: “Who is responsible when a self-driven car crashes or an intelligent medical device fails? How can AI applications be prevented from [being used for] racial discrimination or financial cheating?”

The eight sections discuss:

Transportation: Autonomous cars, trucks and, possibly, aerial delivery vehicles may alter how we commute, work and shop and create new patterns of life and leisure in cities.

Home/service robots: Like the robotic vacuum cleaners already in some homes, specialized robots will clean and provide security in live/work spaces that will be equipped with sensors and remote controls.

Health care: Devices to monitor personal health and robot-assisted surgery are hints of things to come if AI is developed in ways that gain the trust of doctors, nurses, patients and regulators.

Education: Interactive tutoring systems already help students learn languages, math and other skills. More is possible if technologies like natural language processing platforms develop to augment instruction by humans.

Entertainment: The conjunction of content creation tools, social networks and AI will lead to new ways to gather, organize and deliver media in engaging, personalized and interactive ways.

Low-resource communities: Investments in uplifting technologies like predictive models to prevent lead poisoning or improve food distributions could spread AI benefits to the underserved.

Public safety and security: Cameras, drones and software to analyze crime patterns should use AI in ways that reduce human bias and enhance safety without loss of liberty or dignity.

Employment and workplace: Work should start now on how to help people adapt as the economy undergoes rapid changes as many existing jobs are lost and new ones are created.

“Until now, most of what is known about AI comes from science fiction books and movies,” Stone said. “This study provides a realistic foundation to discuss how AI technologies are likely to affect society.”

Grosz said she hopes the AI 100 report “initiates a century-long conversation about ways AI-enhanced technologies might be shaped to improve life and societies.”

You can find the A100 website here, and the group’s first paper: “Artificial Intelligence and Life in 2030” here. Unfortunately, I don’t have time to read the report but I hope to do so soon.

The AI100 website’s About page offered a surprise,

This effort, called the One Hundred Year Study on Artificial Intelligence, or AI100, is the brainchild of computer scientist and Stanford alumnus Eric Horvitz who, among other credits, is a former president of the Association for the Advancement of Artificial Intelligence.

In that capacity Horvitz convened a conference in 2009 at which top researchers considered advances in artificial intelligence and its influences on people and society, a discussion that illuminated the need for continuing study of AI’s long-term implications.

Now, together with Russ Altman, a professor of bioengineering and computer science at Stanford, Horvitz has formed a committee that will select a panel to begin a series of periodic studies on how AI will affect automation, national security, psychology, ethics, law, privacy, democracy and other issues.

“Artificial intelligence is one of the most profound undertakings in science, and one that will affect every aspect of human life,” said Stanford President John Hennessy, who helped initiate the project. “Given’s Stanford’s pioneering role in AI and our interdisciplinary mindset, we feel obliged and qualified to host a conversation about how artificial intelligence will affect our children and our children’s children.”

Five leading academicians with diverse interests will join Horvitz and Altman in launching this effort. They are:

  • Barbara Grosz, the Higgins Professor of Natural Sciences at HarvardUniversity and an expert on multi-agent collaborative systems;
  • Deirdre K. Mulligan, a lawyer and a professor in the School of Information at the University of California, Berkeley, who collaborates with technologists to advance privacy and other democratic values through technical design and policy;

    This effort, called the One Hundred Year Study on Artificial Intelligence, or AI100, is the brainchild of computer scientist and Stanford alumnus Eric Horvitz who, among other credits, is a former president of the Association for the Advancement of Artificial Intelligence.

    In that capacity Horvitz convened a conference in 2009 at which top researchers considered advances in artificial intelligence and its influences on people and society, a discussion that illuminated the need for continuing study of AI’s long-term implications.

    Now, together with Russ Altman, a professor of bioengineering and computer science at Stanford, Horvitz has formed a committee that will select a panel to begin a series of periodic studies on how AI will affect automation, national security, psychology, ethics, law, privacy, democracy and other issues.

    “Artificial intelligence is one of the most profound undertakings in science, and one that will affect every aspect of human life,” said Stanford President John Hennessy, who helped initiate the project. “Given’s Stanford’s pioneering role in AI and our interdisciplinary mindset, we feel obliged and qualified to host a conversation about how artificial intelligence will affect our children and our children’s children.”

    Five leading academicians with diverse interests will join Horvitz and Altman in launching this effort. They are:

    • Barbara Grosz, the Higgins Professor of Natural Sciences at HarvardUniversity and an expert on multi-agent collaborative systems;
    • Deirdre K. Mulligan, a lawyer and a professor in the School of Information at the University of California, Berkeley, who collaborates with technologists to advance privacy and other democratic values through technical design and policy;
    • Yoav Shoham, a professor of computer science at Stanford, who seeks to incorporate common sense into AI;
    • Tom Mitchell, the E. Fredkin University Professor and chair of the machine learning department at Carnegie Mellon University, whose studies include how computers might learn to read the Web;
    • and Alan Mackworth, a professor of computer science at the University of British Columbia [emphases mine] and the Canada Research Chair in Artificial Intelligence, who built the world’s first soccer-playing robot.

    I wasn’t expecting to see a Canadian listed as a member of the AI100 standing committee and then I got another surprise (from the AI100 People webpage),

    Study Panels

    Study Panels are planned to convene every 5 years to examine some aspect of AI and its influences on society and the world. The first study panel was convened in late 2015 to study the likely impacts of AI on urban life by the year 2030, with a focus on typical North American cities.

    2015 Study Panel Members

    • Peter Stone, UT Austin, Chair
    • Rodney Brooks, Rethink Robotics
    • Erik Brynjolfsson, MIT
    • Ryan Calo, University of Washington
    • Oren Etzioni, Allen Institute for AI
    • Greg Hager, Johns Hopkins University
    • Julia Hirschberg, Columbia University
    • Shivaram Kalyanakrishnan, IIT Bombay
    • Ece Kamar, Microsoft
    • Sarit Kraus, Bar Ilan University
    • Kevin Leyton-Brown, [emphasis mine] UBC [University of British Columbia]
    • David Parkes, Harvard
    • Bill Press, UT Austin
    • AnnaLee (Anno) Saxenian, Berkeley
    • Julie Shah, MIT
    • Milind Tambe, USC
    • Astro Teller, Google[X]
  • [emphases mine] and the Canada Research Chair in Artificial Intelligence, who built the world’s first soccer-playing robot.

I wasn’t expecting to see a Canadian listed as a member of the AI100 standing committee and then I got another surprise (from the AI100 People webpage),

Study Panels

Study Panels are planned to convene every 5 years to examine some aspect of AI and its influences on society and the world. The first study panel was convened in late 2015 to study the likely impacts of AI on urban life by the year 2030, with a focus on typical North American cities.

2015 Study Panel Members

  • Peter Stone, UT Austin, Chair
  • Rodney Brooks, Rethink Robotics
  • Erik Brynjolfsson, MIT
  • Ryan Calo, University of Washington
  • Oren Etzioni, Allen Institute for AI
  • Greg Hager, Johns Hopkins University
  • Julia Hirschberg, Columbia University
  • Shivaram Kalyanakrishnan, IIT Bombay
  • Ece Kamar, Microsoft
  • Sarit Kraus, Bar Ilan University
  • Kevin Leyton-Brown, [emphasis mine] UBC [University of British Columbia]
  • David Parkes, Harvard
  • Bill Press, UT Austin
  • AnnaLee (Anno) Saxenian, Berkeley
  • Julie Shah, MIT
  • Milind Tambe, USC
  • Astro Teller, Google[X]

I see they have representation from Israel, India, and the private sector as well. Refreshingly, there’s more than one woman on the standing committee and in this first study group. It’s good to see these efforts at inclusiveness and I’m particularly delighted with the inclusion of an organization from Asia. All too often inclusiveness means Europe, especially the UK. So, it’s good (and I think important) to see a different range of representation.

As for the content of report, should anyone have opinions about it, please do let me know your thoughts in the blog comments.

Interactive chat with Amy Krouse Rosenthal’s memoir

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It’s nice to see writers using technology in their literary work to create new forms although I do admit to a pang at the thought that this might have a deleterious effect on book clubs as the headline (Ditch Your Book Club: This AI-Powered Memoir Wants To Chat With You) for Claire Zulkey’s Sept. 1, 2016 article for Fast Company suggests,

Instead of attempting to write a book that would defeat the distractions of a smartphone, author Amy Krouse Rosenthal decided to make the two kiss and make up with her new memoir.

“I have this habit of doing interactive stuff,” says the Chicago writer and filmmaker, whose previous projects have enticed readers to communicate via email, website, or in person, and before all that, a P.O. box. As she pondered a logical follow-up to her 2005 memoir Encyclopedia of an Ordinary Life (which, among other prompts, offered readers a sample of her favorite perfume if they got in touch via her website), Rosenthal hit upon the concept of a textbook. The idea appealed to her, for its bibliographical elements and as a new way of conversing with her readers. And also, of course, because of the double meaning of the title. Textbook, which went on sale August 9 [2016], is a book readers can send texts to, and the book will text them back. “When I realized the wordplay opportunity, and that nobody had done that before, I loved it,” Rosenthal says. “Most people would probably be reading with a phone in their hands anyway.”

Rosenthal may be best known for the dozens of children’s books she’s published, but Encyclopedia was listed in Amazon’s top 10 memoirs of the decade for its alphabetized musings gathered together under the premise, “I have not survived against all odds. I have not lived to tell. I have not witnessed the extraordinary. This is my story.” Her writing often celebrates the serendipitous moment, the smallness of our world, the misheard sentence that was better than the real one—always in praise of the flashes of magic in our mundane lives. Textbook, Rosenthal says, is not a prequel or a sequel but “an equal” to Encyclopedia. It is organized by subject, and Rosenthal shares her favorite anagrams, admits a bias against people who sign emails with just their initials, and exhorts readers, next time they are at a party, to attempt to write a “group biography.” …

… when she sent the book out to publishers, Rosenthal explains, “Pretty much everybody got it. Nobody said, ‘We want to do this book but we don’t want to do that texting thing.’”

Zulkey also covers some of the nitty gritty elements of getting this book published and developed,

After she signed with Dutton, Rosenthal’s editors got in touch with OneReach, a Denver company that specializes in providing multichannel, conversational bot experiences, “This book is a great illustration of what we’re going to see a lot more of in the future,” says OneReach cofounder Robb Wilson. “It’s conversational and has some basic AI components in it.”

…

Textbook has nearly 20 interactive elements to it, some of which involve email or going to the book’s website, but many are purely text-message-based. One example is a prompt to send in good thoughts, which Rosenthal will then print and send out in a bottle to sea. Another asks readers to text photos of a rainbow they are witnessing in real time. The rainbow and its location are then posted on the book’s website in a live rainbow feed. And yet another puts out a call for suggestions for matching tattoos that at least one reader and Rosenthal will eventually get. Three weeks after its publication date, the book has received texts from over 600 readers.

Nearly anyone who has received a text from Walgreens saying a prescription is ready, gotten an appointment confirmation from a dentist, or even voted on American Idol has interacted with the type of technology OneReach handles. But behind the scenes of that technology were artistic quandaries that Rosenthal and the team had to solve or work around.

For instance, the reader has the option to pick and choose which prompts to engage with and in what order, which is not typically how text chains work. “Normally, with an automated text message you’re in kind of a lineal format,” says Justin Biel, who built Textbook’s system and made sure that if you skipped the best-wishes text, for instance, and go right to the rainbow, you wouldn’t get an error message. At one point Rosenthal and her assistant manually tried every possible permutation of text to confirm that there were no hitches jumping from one prompt to another.

Engineers also made lots of revisions so that the system felt like readers were having a realistic text conversation with a person, rather than a bot or someone who had obviously written out the messages ahead of time. “It’s a fine line between robotic and poetic,” Rosenthal says.

…

Unlike your Instacart shopper whom you hope doesn’t need to text to ask you about substitutions, Textbook readers will never receive a message alerting them to a new Rosenthal signing or a discount at Amazon. No promo or marketing messages, ever. “In a way, that’s a betrayal,” Wilson says. Texting, to him, is “a personal channel, and to try to use that channel for blatant reasons, I think, hurts you more than it helps you.

Zulkey’s piece is a good read and includes images and an embedded video.