In 2017, Stanford University researchers presented a new device that mimics the brain’s efficient and low-energy neural learning process [see my March 8, 2017 posting for more]. It was an artificial version of a synapse — the gap across which neurotransmitters travel to communicate between neurons — made from organic materials. In 2019, the researchers assembled nine of their artificial synapses together in an array, showing that they could be simultaneously programmed to mimic the parallel operation of the brain [see my Sept. 17, 2019 posting].
Now, in a paper published June 15  in Nature Materials, they have tested the first biohybrid version of their artificial synapse and demonstrated that it can communicate with living cells. Future technologies stemming from this device could function by responding directly to chemical signals from the brain. The research was conducted in collaboration with researchers at Istituto Italiano di Tecnologia (Italian Institute of Technology — IIT) in Italy and at Eindhoven University of Technology (Netherlands).
“This paper really highlights the unique strength of the materials that we use in being able to interact with living matter,” said Alberto Salleo, professor of materials science and engineering at Stanford and co-senior author of the paper. “The cells are happy sitting on the soft polymer. But the compatibility goes deeper: These materials work with the same molecules neurons use naturally.”
While other brain-integrated devices require an electrical signal to detect and process the brain’s messages, the communications between this device and living cells occur through electrochemistry — as though the material were just another neuron receiving messages from its neighbor.
The biohybrid artificial synapse consists of two soft polymer electrodes, separated by a trench filled with electrolyte solution – which plays the part of the synaptic cleft that separates communicating neurons in the brain. When living cells are placed on top of one electrode, neurotransmitters that those cells release can react with that electrode to produce ions. Those ions travel across the trench to the second electrode and modulate the conductive state of this electrode. Some of that change is preserved, simulating the learning process occurring in nature.
“In a biological synapse, essentially everything is controlled by chemical interactions at the synaptic junction. Whenever the cells communicate with one another, they’re using chemistry,” said Scott Keene, a graduate student at Stanford and co-lead author of the paper. “Being able to interact with the brain’s natural chemistry gives the device added utility.”
This process mimics the same kind of learning seen in biological synapses, which is highly efficient in terms of energy because computing and memory storage happen in one action. In more traditional computer systems, the data is processed first and then later moved to storage.
To test their device, the researchers used rat neuroendocrine cells that release the neurotransmitter dopamine. Before they ran their experiment, they were unsure how the dopamine would interact with their material – but they saw a permanent change in the state of their device upon the first reaction.
“We knew the reaction is irreversible, so it makes sense that it would cause a permanent change in the device’s conductive state,” said Keene. “But, it was hard to know whether we’d achieve the outcome we predicted on paper until we saw it happen in the lab. That was when we realized the potential this has for emulating the long-term learning process of a synapse.”
A first step
This biohybrid design is in such early stages that the main focus of the current research was simply to make it work.
“It’s a demonstration that this communication melding chemistry and electricity is possible,” said Salleo. “You could say it’s a first step toward a brain-machine interface, but it’s a tiny, tiny very first step.”
Now that the researchers have successfully tested their design, they are figuring out the best paths for future research, which could include work on brain-inspired computers, brain-machine interfaces, medical devices or new research tools for neuroscience. Already, they are working on how to make the device function better in more complex biological settings that contain different kinds of cells and neurotransmitters.
Here’s a link to and a citation for the paper,
A biohybrid synapse with neurotransmitter-mediated plasticity by Scott T. Keene, Claudia Lubrano, Setareh Kazemzadeh, Armantas Melianas, Yaakov Tuchman, Giuseppina Polino, Paola Scognamiglio, Lucio Cinà, Alberto Salleo, Yoeri van de Burgt & Francesca Santoro. Nature Materials (2020) DOI: https://doi.org/10.1038/s41563-020-0703-y Published: 15 June 2020
The brain’s capacity for simultaneously learning and memorizing large amounts of information while requiring little energy has inspired an entire field to pursue brain-like — or neuromorphic — computers. Researchers at Stanford University and Sandia National Laboratories previously developed one portion of such a computer: a device that acts as an artificial synapse, mimicking the way neurons communicate in the brain.
In a paper published online by the journal Science on April 25 , the team reports that a prototype array of nine of these devices performed even better than expected in processing speed, energy efficiency, reproducibility and durability.
Looking forward, the team members want to combine their artificial synapse with traditional electronics, which they hope could be a step toward supporting artificially intelligent learning on small devices.
“If you have a memory system that can learn with the energy efficiency and speed that we’ve presented, then you can put that in a smartphone or laptop,” said Scott Keene, co-author of the paper and a graduate student in the lab of Alberto Salleo, professor of materials science and engineering at Stanford who is co-senior author. “That would open up access to the ability to train our own networks and solve problems locally on our own devices without relying on data transfer to do so.”
The team’s artificial synapse is similar to a battery, modified so that the researchers can dial up or down the flow of electricity between the two terminals. That flow of electricity emulates how learning is wired in the brain. This is an especially efficient design because data processing and memory storage happen in one action, rather than a more traditional computer system where the data is processed first and then later moved to storage.
Seeing how these devices perform in an array is a crucial step because it allows the researchers to program several artificial synapses simultaneously. This is far less time consuming than having to program each synapse one-by-one and is comparable to how the brain actually works.
In previous tests of an earlier version of this device, the researchers found their processing and memory action requires about one-tenth as much energy as a state-of-the-art computing system needs in order to carry out specific tasks. Still, the researchers worried that the sum of all these devices working together in larger arrays could risk drawing too much power. So, they retooled each device to conduct less electrical current – making them much worse batteries but making the array even more energy efficient.
The 3-by-3 array relied on a second type of device – developed by Joshua Yang at the University of Massachusetts, Amherst, who is co-author of the paper – that acts as a switch for programming synapses within the array.
“Wiring everything up took a lot of troubleshooting and a lot of wires. We had to ensure all of the array components were working in concert,” said Armantas Melianas, a postdoctoral scholar in the Salleo lab. “But when we saw everything light up, it was like a Christmas tree. That was the most exciting moment.”
During testing, the array outperformed the researchers’ expectations. It performed with such speed that the team predicts the next version of these devices will need to be tested with special high-speed electronics. After measuring high energy efficiency in the 3-by-3 array, the researchers ran computer simulations of a larger 1024-by-1024 synapse array and estimated that it could be powered by the same batteries currently used in smartphones or small drones. The researchers were also able to switch the devices over a billion times – another testament to its speed – without seeing any degradation in its behavior.
“It turns out that polymer devices, if you treat them well, can be as resilient as traditional counterparts made of silicon. That was maybe the most surprising aspect from my point of view,” Salleo said. “For me, it changes how I think about these polymer devices in terms of reliability and how we might be able to use them.”
Room for creativity
The researchers haven’t yet submitted their array to tests that determine how well it learns but that is something they plan to study. The team also wants to see how their device weathers different conditions – such as high temperatures – and to work on integrating it with electronics. There are also many fundamental questions left to answer that could help the researchers understand exactly why their device performs so well.
“We hope that more people will start working on this type of device because there are not many groups focusing on this particular architecture, but we think it’s very promising,” Melianas said. “There’s still a lot of room for improvement and creativity. We only barely touched the surface.”
While my main interest is the group’s temporary art gallery, I am providing a brief explanatory introduction and a couple of previews for SIGGRAPH 2018.
For anyone unfamiliar with the Special Interest Group on Computer GRAPHics and Interactive Techniques (SIGGRAPH) and its conferences, from the SIGGRAPH Wikipedia entry Note: Links have been removed),
Some highlights of the conference are its Animation Theater and Electronic Theater presentations, where recently created CG films are played. There is a large exhibition floor, where several hundred companies set up elaborate booths and compete for attention and recruits. Most of the companies are in the engineering, graphics, motion picture, or video game industries. There are also many booths for schools which specialize in computer graphics or interactivity.
Dozens of research papers are presented each year, and SIGGRAPH is widely considered the most prestigious forum for the publication of computer graphics research. The recent paper acceptance rate for SIGGRAPH has been less than 26%. The submitted papers are peer-reviewed in a single-blind process. There has been some criticism about the preference of SIGGRAPH paper reviewers for novel results rather than useful incremental progress. …
This is the third SIGGRAPH Vancouver has hosted; the others were in 2011 and 2014. The theme for the 2018 iteration is ‘Generations’; here’s more about it from an Aug. 2, 2018 article by Terry Flores for Variety,
While its focus is firmly forward thinking, SIGGRAPH 2018, the computer graphics, animation, virtual reality, games, digital art, mixed reality, and emerging technologies conference, is also tipping its hat to the past thanks to its theme this year: Generations. The conference runs Aug. 12-16 in Vancouver, B.C.
“In the literal people sense, pioneers in the computer graphics industry are standing shoulder to shoulder with researchers, practitioners and the future of the industry — young people — mentoring them, dabbling across multiple disciplines to innovate, relate, and grow,” says SIGGRAPH 2018 conference chair Roy C. Anthony, VP of creative development and operations at software and technology firm Ventuz. “This is really what SIGGRAPH has always been about. Generations really seemed like a very appropriate way of looking back and remembering where we all came from and how far we’ve come.”
SIGGRAPH 2018 has a number of treats in store for attendees, including the debut of Disney’s first VR film, the short “Cycles”; production sessions on the making of “Blade Runner 2049,” “Game of Thrones,” “Incredibles 2” and “Avengers: Infinity War”; as well as sneak peeks of Disney’s upcoming “Ralph Breaks the Internet: Wreck-It Ralph 2” and Laika’s “Missing Link.”
That list of ‘treats’ in the last paragraph makes the conference seem more like an iteration of a ‘comic-con’ than a technology conference.
CHICAGO–In the burgeoning world of virtual reality (VR) technology, it remains a challenge to provide users with a realistic perception of infinite space and natural walking capabilities in the virtual environment. A team of computer scientists has introduced a new approach to address this problem by leveraging a natural human phenomenon: eye blinks.
All humans are functionally blind for about 10 percent of the time under normal circumstances due to eye blinks and saccades, a rapid movement of the eye between two points or objects. Eye blinks are a common and natural cause of so-called “change blindness,” which indicates the inability for humans to notice changes to visual scenes. Zeroing in on eye blinks and change blindness, the team has devised a novel computational system that effectively redirects the user in the virtual environment during these natural instances, all with undetectable camera movements to deliver orientation redirection.
“Previous RDW [redirected walking] techniques apply rotations continuously while the user is walking. But the amount of unnoticeable rotations is limited,” notes Eike Langbehn, lead author of the research and doctoral candidate at the University of Hamburg. “That’s why an orthogonal approach is needed–we add some additional rotations when the user is not focused on the visuals. When we learned that humans are functionally blind for some time due to blinks, we thought, ‘Why don’t we do the redirection during eye blinks?'”
Human eye blinks occur approximately 10 to 20 times per minute, about every 4 to 19 seconds. Leveraging this window of opportunity–where humans are unable to detect major motion changes while in a virtual environment–the researchers devised an approach to synchronize a computer graphics rendering system with this visual process, and introduce any useful motion changes in virtual scenes to enhance users’ overall VR experience.
The researchers’ experiments revealed that imperceptible camera rotations of 2 to 5 degrees and translations of 4 to 9 cm of the user’s viewpoint are possible during a blink without users even noticing. They tracked test participants’ eye blinks by an eye tracker in a VR head-mounted display. In a confirmatory study, the team validated that participants could not reliably detect in which of two eye blinks their viewpoint was manipulated while walking a VR curved path. The tests relied on unconscious natural eye blinking, but the researchers say redirection during blinking could be carried out consciously. Since users can consciously blink multiple times a day without much effort, eye blinks provide great potential to be used as an intentional trigger in their approach.
The team will present their work at SIGGRAPH 2018, held 12-16 August in Vancouver, British Columbia. The annual conference and exhibition showcases the world’s leading professionals, academics, and creative minds at the forefront of computer graphics and interactive techniques.
“RDW is a big challenge since current techniques still need too much space to enable unlimited walking in VR,” notes Langbehn. “Our work might contribute to a reduction of space since we found out that unnoticeable rotations of up to five degrees are possible during blinks. This means we can improve the performance of RDW by approximately 50 percent.”
The team’s results could be used in combination with other VR research, such as novel steering algorithms, improved path prediction, and rotations during saccades, to name a few. Down the road, such techniques could some day enable consumer VR users to virtually walk beyond their living room.
Langbehn collaborated on the work with Frank Steinicke of University of Hamburg, Markus Lappe of University of Muenster, Gregory F. Welch of University of Central Florida, and Gerd Bruder, also of University of Central Florida. For the full paper and video, visit the team’s project page.
About ACM, ACM SIGGRAPH, and SIGGRAPH 2018
ACM, the Association for Computing Machinery, is the world’s largest educational and scientific computing society, uniting educators, researchers, and professionals to inspire dialogue, share resources, and address the field’s challenges. ACM SIGGRAPH is a special interest group within ACM that serves as an interdisciplinary community for members in research, technology, and applications in computer graphics and interactive techniques. SIGGRAPH is the world’s leading annual interdisciplinary educational experience showcasing the latest in computer graphics and interactive techniques. SIGGRAPH 2018, marking the 45th annual conference hosted by ACM SIGGRAPH, will take place from 12-16 August at the Vancouver Convention Centre in Vancouver, B.C.
They have provided an image illustrating what they mean (I don’t find it especially informative),
Caption: The viewing behavior of a virtual reality user, including fixations (in green) and saccades (in red). A blink fully suppresses visual perception. Credit: Eike Langbehn
Walt Disney Animation Studios will debut its first ever virtual reality short film at SIGGRAPH 2018, and the hope is viewers will walk away feeling connected to the characters as equally as they will with the VR technology involved in making the film.
Cycles, an experimental film directed by Jeff Gipson, centers around the true meaning of creating a home and the life it holds inside its walls. The idea for the film is personal, inspired by Gipson’s childhood spending time with his grandparents and creating memories in their home, and later, having to move them to an assisted living residence.
“Every house has a story unique to the people, the characters who live there,” says Gipson. “We wanted to create a story in this single place and be able to have the viewer witness life happening around them. It is an emotionally driven film, expressing the real ups and downs, the happy and sad moments in life.”
For Cycles, Gipson also drew from his past life as an architect, having spent several years designing skate parks, and from his passion for action sports, including freestyle BMX. In Los Angeles, where Gipson lives, it is not unusual to find homes with an empty swimming pool reserved for skating or freestyle biking. Part of the pitch for Cycles came out of Gipson’s experience riding in these empty pools and being curious about the homes attached to them, the families who lived there, and the memories they made.
SIGGRAPH attendees will have the opportunity to experience Cycles at the Immersive Pavilion, a new space for this year’s conference. The Pavilion is devoted exclusively to virtual, augmented, and mixed reality and will contain: the VR Theater, a storytelling extravaganza that is part of the Computer Animation Festival; the Vrcade, a space for VR, AR, and MR games or experiences; and the well-known Village, for showcasing large-scale projects. SIGGRAPH 2018, held 12-16 August in Vancouver, British Columbia, is an annual gathering that showcases the world’s leading professionals, academics, and creative minds at the forefront of computer graphics and interactive techniques.
The production team completed Cycles in four months with about 50 collaborators as part of a professional development program at the studio. A key difference in VR filmmaking includes getting creative with how to translate a story to the VR “screen.” Pre-visualizing the narrative, for one, was a challenge. Rather than traditional storyboarding, Gipson and his team instead used a mix of Quill VR painting techniques and motion capture to “storyboard” Cycles, incorporating painters and artists to generate sculptures or 3D models of characters early on and draw scenes for the VR space. The creators also got innovative with the use of light and color saturation in scenes to help guide the user’s eyes during the film.
“What’s cool for VR is that we are really on the edge of trying to figure out what it is and how to tell stories in this new medium,” says Gipson. “In VR, you can look anywhere and really be transported to a different world, experience it from different angles, and see every detail. We want people watching to feel alive and feel emotion, and give them a true cinematic experience.”
This is Gipson’s VR directorial debut. He joined Walt Disney Animation Studios in 2013, serving as a lighting artist on Disney favorites like Frozen, Zootopia, and Moana. Of getting to direct the studio’s first VR short, he says, “VR is an amazing technology and a lot of times the technology is what is really celebrated. We hope more and more people begin to see the emotional weight of VR films, and with Cycles in particular, we hope they will feel the emotions we aimed to convey with our story.”
Apparently this is a still from the ‘short’,
Caption: Disney Animation Studios will present ‘Cycles’ , its first virtual reality (VR) short, at ACM SIGGRAPH 2018. Credit: Disney Animation Studios
Google has unveiled a new virtual reality (VR) immersive experience based on a novel system that captures and renders high-quality, realistic images from the real world using light fields. Created by a team of leading researchers at Google, Welcome to Light Fields is the tech giant’s splash into the nascent arena of light fields VR experiences, an exciting corner of VR video technology gaining traction for its promise to deliver extremely high-quality imagery and experiences in the virtual world.
Google released Welcome to Light Fields earlier this year as a free app on Steam VR for HTC Vive, Oculus Rift, and Windows Mixed Reality headsets. The creators will demonstrate the VR experience at SIGGRAPH 2018, in the Immersive Pavilion, a new space for this year’s conference. The Pavilion is devoted exclusively to virtual, augmented, and mixed reality and will contain: the Vrcade, a space for VR, AR, and MR games or experiences; the VR Theater, a storytelling extravaganza that is part of the Computer Animation Festival; and the well-known Village, for showcasing large-scale projects. SIGGRAPH 2018, held 12-16 August in Vancouver, British Columbia, is an annual gathering that showcases the world’s leading professionals, academics, and creative minds at the forefront of computer graphics and interactive techniques.
Destinations in Welcome to Light Fields include NASA’s Space Shuttle Discovery, delivering to viewers an astronaut’s view inside the flight deck, which has never been open to the public; the pristine teak and mahogany interiors of the Gamble House, an architectural treasure in Pasadena, CA; and the glorious St. Stephen’s Church in Granada Hills, CA, home to a stunning wall of more than 14,000 pieces of glimmering stained glass.
“I love that light fields in VR can teleport you to exotic places in the real world, and truly make you believe you are there,” says Ryan Overbeck, software engineer at Google who co-led the project. “To me, this is magic.”
To bring this experience to life, Overbeck worked with a team that included Paul Debevec, senior staff engineer at Google, who managed the project and led the hardware piece with engineers Xueming Yu, Jay Busch, and Graham Fyffe. With Overbeck, Daniel Erickson and Daniel Evangelakos focused on the software end. The researchers designed a comprehensive system for capturing and rendering high-quality, spherical light field still images from footage captured in the real world. They developed two easy-to-use light field camera rigs, based on the GoPro Hero4action sports camera, that efficiently capture thousands of images on the surface of a sphere. Those images were then passed through a cloud-based light-field-processing pipeline.
Among other things, explains Overbeck, “The processing pipeline uses computer vision to place the images in 3D and generate depth maps, and we use a modified version of our vp9 video codec
to compress the light field data down to a manageable size.” To render a light field dataset, he notes, the team used a rendering algorithm that blends between the thousands of light field images in real-time.
The team relied on Google’s talented pool of engineers in computer vision, graphics, video compression, and machine learning to overcome the unique challenges posed in light fields technology. They also collaborated closely with the WebM team (who make the vp9 video codec) to develop the high-quality light field compression format incorporated into their system, and leaned heavily on the expertise of the Jump VR team to help pose the images and generate depth maps. (Jump is Google’s professional VR system for achieving 3D-360 video production at scale.)
Indeed, with Welcome to Light Fields, the Google team is demonstrating the potential and promise of light field VR technology, showcasing the technology’s ability to provide a truly immersive experience with a level of unmatched realism. Though light fields technology has been researched and explored in computer graphics for more than 30 years, practical systems for actually delivering high-quality light field experiences has not yet been possible.
Part of the team’s motivation behind creating this VR light field experience is to invigorate the nascent field.
“Welcome to Light Fields proves that it is now possible to make a compelling light field VR viewer that runs on consumer-grade hardware, and we hope that this knowledge will encourage others to get involved with building light field technology and media,” says Overbeck. “We understand that in order to eventually make compelling consumer products based on light fields, we need a thriving light field ecosystem. We need open light field codecs, we need artists creating beautiful light field imagery, and we need people using VR in order to engage with light fields.”
I don’t really understand why this image, which looks like something belongs on advertising material, would be chosen to accompany a news release on a science-based distribution outlet,
Caption: A team of leading researchers at Google, will unveil the new immersive virtual reality (VR) experience “Welcome to Lightfields” at ACM SIGGRAPH 2018. Credit: Image courtesy of Google/Overbeck
Advances in computer-generated imagery have brought vivid, realistic animations to life, but the sounds associated with what we see simulated on screen, such as two objects colliding, are often recordings. Now researchers at Stanford University have developed a system that automatically renders accurate sounds for a wide variety of animated phenomena.
“There’s been a Holy Grail in computing of being able to simulate reality for humans. We can animate scenes and render them visually with physics and computer graphics, but, as for sounds, they are usually made up,” said Doug James, professor of computer science at Stanford University. “Currently there exists no way to generate realistic synchronized sounds for complex animated content, such as splashing water or colliding objects, automatically. This fills that void.”
The researchers will present their work on this sound synthesis system as part of ACM SIGGRAPH 2018, the leading conference on computer graphics and interactive techniques. In addition to enlivening movies and virtual reality worlds, this system could also help engineering companies prototype how products would sound before being physically produced, and hopefully encourage designs that are quieter and less irritating, the researchers said.
“I’ve spent years trying to solve partial differential equations – which govern how sound propagates – by hand,” said Jui-Hsien Wang, a graduate student in James’ lab and in the Institute for Computational and Mathematical Engineering (ICME), and lead author of the paper. “This is actually a place where you don’t just solve the equation but you can actually hear it once you’ve done it. That’s really exciting to me and it’s fun.”
Informed by geometry and physical motion, the system figures out the vibrations of each object and how, like a loudspeaker, those vibrations excite sound waves. It computes the pressure waves cast off by rapidly moving and vibrating surfaces but does not replicate room acoustics. So, although it does not recreate the echoes in a grand cathedral, it can resolve detailed sounds from scenarios like a crashing cymbal, an upside-down bowl spinning to a stop, a glass filling up with water or a virtual character talking into a megaphone.
Most sounds associated with animations rely on pre-recorded clips, which require vast manual effort to synchronize with the action on-screen. These clips are also restricted to noises that exist – they can’t predict anything new. Other systems that produce and predict sounds as accurate as those of James and his team work only in special cases, or assume the geometry doesn’t deform very much. They also require a long pre-computation phase for each separate object.
“Ours is essentially just a render button with minimal pre-processing that treats all objects together in one acoustic wave simulation,” said Ante Qu, a graduate student in James’ lab and co-author of the paper.
The simulated sound that results from this method is highly detailed. It takes into account the sound waves produced by each object in an animation but also predicts how those waves bend, bounce or deaden based on their interactions with other objects and sound waves in the scene.
In its current form, the group’s process takes a while to create the finished product. But, now that they have proven this technique’s potential, they can focus on performance optimizations, such as implementing their method on parallel GPU hardware, that should make it drastically faster.
And, even in its current state, the results are worth the wait.
“The first water sounds we generated with the system were among the best ones we had simulated – and water is a huge challenge in computer-generated sound,” said James. “We thought we might get a little improvement, but it is dramatically better than previous approaches even right out of the box. It was really striking.”
Although the group’s work has faithfully rendered sounds of various objects spinning, falling and banging into each other, more complex objects and interactions – like the reverberating tones of a Stradivarius violin – remain difficult to model realistically. That, the group said, will have to wait for a future solution.
Timothy Langlois of Adobe Research is a co-author of this paper. This research was funded by the National Science Foundation and Adobe Research. James is also a professor, by courtesy, of music and a member of Stanford Bio-X.
Researchers Timothy Langlois, Doug L. James, Ante Qu and Jui-Hsien Wang have created a video featuring highlights of animations with sounds synthesized using the Stanford researchers’ new system.,
The researchers have also provided this image,
By computing pressure waves cast off by rapidly moving and vibrating surfaces – such as a cymbal – a new sound synthesis system developed by Stanford researchers can automatically render realistic sound for computer animations. (Image credit: Timothy Langlois, Doug L. James, Ante Qu and Jui-Hsien Wang)
It does seem like we’re synthesizing the world around us, eh?
SIGGRAPH 2018, the world’s leading showcase of digital art created using computer graphics and interactive techniques, will present a special Art Gallery, entitled “Origins,” and historic Art Papers in Vancouver, B.C. The 45th SIGGRAPH conference will take place 12–16 August at the Vancouver Convention Centre. The programs will also honor the generations of creators that have come before through a special, 50th anniversary edition of the Leonard journal. To register for the conference, visit S2018.SIGGRAPH.ORG.
The SIGGRAPH 2018 ART GALLERY is a curated exhibition, conceived as a dialogical space that enables the viewer to reflect on man’s diverse cultural values and rituals through contemporary creative practices. Building upon an exciting and eclectic selection of creative practices mediated through technologies that represent the sophistication of our times, the SIGGRAPH 2018 Art Gallery will embrace the narratives of the indigenous communities based near Vancouver and throughout Canada as a source of inspiration. The exhibition will feature contemporary media artworks, art pieces by indigenous communities, and other traces of technologically mediated Ludic practices.
Andrés Burbano, SIGGRAPH 2018 Art Gallery chair and professor at Universidad de los Andes, said, “The Art Gallery aims to articulate myth and technology, science and art, the deep past and the computational present, and will coalesce around a theme of ‘Origins.’ Media and technological creative expressions will explore principles such as the origins of the cosmos, the origins of life, the origins of human presence, the origins of the occupation of territories in the Americas, and the origins of people living in the vast territories of the Arctic.”
He continued, “The venue [in Vancouver] hopes to rekindle the original spark that ignited the collaborative spirit of the SIGGRAPH community of engineers, scientists, and artists, who came together to create the very first conference in the early 1970s.”
Highlights from the 2018 Art Gallery include:
Transformation Mask (Canada) [Technology Based]
Shawn Hunt, independent; and Microsoft Garage: Andy Klein, Robert Butterworth, Jonathan Cobb, Jeremy Kersey, Stacey Mulcahy, Brendan O’Rourke, Brent Silk, and Julia Taylor-Hell, Microsoft Vancouver
TRANSFORMATION MASK is an interactive installation that features the Microsoft HoloLens. It utilizes electronics and mechanical engineering to express a physical and digital transformation. Participants are immersed in spatial sounds and holographic visuals.
Somnium (U.S.) [Science Based]
Marko Peljhan, Danny Bazo, and Karl Yerkes, University of California, Santa Barbara
Somnium is a cybernetic installation that provides visitors with the ability to sensorily, cognitively, and emotionally contemplate and experience exoplanetary discoveries, their macro and micro dimensions, and the potential for life in our Galaxy. Some might call it “space telescope.”
Ernest Edmonds Retrospective – Art Systems 1968-2018 (United Kingdom) [History Based]
Ernest Edmonds, De Montfort University
Celebrating one of the pioneers of computer graphics-based art since the early 1970s, this Ernest Edmonds career retrospective will showcase snapshots of Edmonds’ work as it developed over the years. With one piece from each decade, the retrospective will also demonstrate how vital the Leonardo journal has been throughout the 50-year journey.
In addition to the works above, the Art Gallery will feature pieces from notable female artists Ozge Samanci, Ruth West, and Nicole L’Hullier. For more information about the Edmonds retrospective, read THIS POST ON THE ACM SIGGRAPH BLOG.
The SIGGRAPH 2018 ART PAPERS program is designed to feature research from artists, scientists, theorists, technologists, historians, and more in one of four categories: project description, theory/criticism, methods, or history. The chosen work was selected by an international jury of scholars, artists, and immersive technology developers.
To celebrate the 50th anniversary of LEONARDO (MIT Press), and 10 years of its annual SIGGRAPH issue, SIGGRAPH 2018 is pleased to announce a special anniversary edition of the journal, which will feature the 2018 art papers. For 50 years, Leonardo has been the definitive publication for artist-academics. To learn more about the relationship between SIGGRAPH and the journal, listen to THIS EPISODE OF THE SIGGRAPH SPOTLIGHT PODCAST.
“In order to encourage a wider range of topics, we introduced a new submission type, short papers. This enabled us to accept more content than in previous years. Additionally, for the first time, we will introduce sessions that integrate the Art Gallery artist talks with Art Papers talks, promoting richer connections between these two creative communities,” said Angus Forbes, SIGGRAPH 2018 Art Papers chair and professor at University of California, Santa Cruz.
Art Papers highlights include:
Alienating the Familiar with CGI: A Recipe for Making a Full CGI Art House Animated Feature [Long]
Alex Counsell and Paul Charisse, University of Portsmouth
This paper explores the process of making and funding an art house feature film using full CGI in a marketplace where this has never been attempted. It explores cutting-edge technology and production approaches, as well as routes to successful fundraising.
Augmented Fauna and Glass Mutations: A Dialogue Between Material and Technique in Glassblowing and 3D Printing [Long]
Tobias Klein, City University of Hong Kong
The two presented artworks, “Augmented Fauna” and “Glass Mutations,” were created during an artist residence at the PILCHUCK GLASS SCHOOL. They are examples of the qualities and methods established through a synthesis between digital workflows and traditional craft processes and thus formulate the notion of digital craftsmanship.
Inhabitat: An Imaginary Ecosystem in a Children’s Science Museum [Short]
Graham Wakefield, York University, and Haru Hyunkyung Ji, OCAD University
“Inhabitat” is a mixed reality artwork in which participants become part of an imaginary ecology through three simultaneous perspectives of scale and agency; three distinct ways to see with other eyes. This imaginary world was exhibited at a children’s science museum for five months, using an interactive projection-augmented sculpture, a large screen and speaker array, and a virtual reality head-mounted display.
What’s the what?
My father used to say that and I always assumed it meant summarize the high points, if you need to, and get to the point—fast. In that spirit, I am both fascinated and mildly appalled. The virtual, mixed, and augmented reality technologies, as well as, the others being featured at SIGGRAPH 2018 are wondrous in many ways but it seems we are coming ever closer to a world where we no longer interact with nature or other humans directly. (see my August 10, 2018 posting about the ‘extinction of experience’ for research that encourages more direct interaction with nature) I realize that SIGGRAPH is intended as a primarily technical experience but I think a little more content questioning these technologies and their applications (social implications) might be in order. That’s often the artist’s role but I can’t see anything in the art gallery descriptions that hint at any sort of fundamental critique.
This artificial synapse is apparently an improvement on the standard memristor-based artificial synapse but that doesn’t become clear until reading the abstract for the paper. First, there’s a Feb. 20, 2017 Stanford University news release by Taylor Kubota (dated Feb. 21, 2017 on EurekAlert), Note: Links have been removed,
For all the improvements in computer technology over the years, we still struggle to recreate the low-energy, elegant processing of the human brain. Now, researchers at Stanford University and Sandia National Laboratories have made an advance that could help computers mimic one piece of the brain’s efficient design – an artificial version of the space over which neurons communicate, called a synapse.
“It works like a real synapse but it’s an organic electronic device that can be engineered,” said Alberto Salleo, associate professor of materials science and engineering at Stanford and senior author of the paper. “It’s an entirely new family of devices because this type of architecture has not been shown before. For many key metrics, it also performs better than anything that’s been done before with inorganics.”
The new artificial synapse, reported in the Feb. 20 issue of Nature Materials, mimics the way synapses in the brain learn through the signals that cross them. This is a significant energy savings over traditional computing, which involves separately processing information and then storing it into memory. Here, the processing creates the memory.
This synapse may one day be part of a more brain-like computer, which could be especially beneficial for computing that works with visual and auditory signals. Examples of this are seen in voice-controlled interfaces and driverless cars. Past efforts in this field have produced high-performance neural networks supported by artificially intelligent algorithms but these are still distant imitators of the brain that depend on energy-consuming traditional computer hardware.
Building a brain
When we learn, electrical signals are sent between neurons in our brain. The most energy is needed the first time a synapse is traversed. Every time afterward, the connection requires less energy. This is how synapses efficiently facilitate both learning something new and remembering what we’ve learned. The artificial synapse, unlike most other versions of brain-like computing, also fulfills these two tasks simultaneously, and does so with substantial energy savings.
“Deep learning algorithms are very powerful but they rely on processors to calculate and simulate the electrical states and store them somewhere else, which is inefficient in terms of energy and time,” said Yoeri van de Burgt, former postdoctoral scholar in the Salleo lab and lead author of the paper. “Instead of simulating a neural network, our work is trying to make a neural network.”
The artificial synapse is based off a battery design. It consists of two thin, flexible films with three terminals, connected by an electrolyte of salty water. The device works as a transistor, with one of the terminals controlling the flow of electricity between the other two.
Like a neural path in a brain being reinforced through learning, the researchers program the artificial synapse by discharging and recharging it repeatedly. Through this training, they have been able to predict within 1 percent of uncertainly what voltage will be required to get the synapse to a specific electrical state and, once there, it remains at that state. In other words, unlike a common computer, where you save your work to the hard drive before you turn it off, the artificial synapse can recall its programming without any additional actions or parts.
Testing a network of artificial synapses
Only one artificial synapse has been produced but researchers at Sandia used 15,000 measurements from experiments on that synapse to simulate how an array of them would work in a neural network. They tested the simulated network’s ability to recognize handwriting of digits 0 through 9. Tested on three datasets, the simulated array was able to identify the handwritten digits with an accuracy between 93 to 97 percent.
Although this task would be relatively simple for a person, traditional computers have a difficult time interpreting visual and auditory signals.
“More and more, the kinds of tasks that we expect our computing devices to do require computing that mimics the brain because using traditional computing to perform these tasks is becoming really power hungry,” said A. Alec Talin, distinguished member of technical staff at Sandia National Laboratories in Livermore, California, and senior author of the paper. “We’ve demonstrated a device that’s ideal for running these type of algorithms and that consumes a lot less power.”
This device is extremely well suited for the kind of signal identification and classification that traditional computers struggle to perform. Whereas digital transistors can be in only two states, such as 0 and 1, the researchers successfully programmed 500 states in the artificial synapse, which is useful for neuron-type computation models. In switching from one state to another they used about one-tenth as much energy as a state-of-the-art computing system needs in order to move data from the processing unit to the memory.
This, however, means they are still using about 10,000 times as much energy as the minimum a biological synapse needs in order to fire. The researchers are hopeful that they can attain neuron-level energy efficiency once they test the artificial synapse in smaller devices.
Every part of the device is made of inexpensive organic materials. These aren’t found in nature but they are largely composed of hydrogen and carbon and are compatible with the brain’s chemistry. Cells have been grown on these materials and they have even been used to make artificial pumps for neural transmitters. The voltages applied to train the artificial synapse are also the same as those that move through human neurons.
All this means it’s possible that the artificial synapse could communicate with live neurons, leading to improved brain-machine interfaces. The softness and flexibility of the device also lends itself to being used in biological environments. Before any applications to biology, however, the team plans to build an actual array of artificial synapses for further research and testing.
Additional Stanford co-authors of this work include co-lead author Ewout Lubberman, also of the University of Groningen in the Netherlands, Scott T. Keene and Grégorio C. Faria, also of Universidade de São Paulo, in Brazil. Sandia National Laboratories co-authors include Elliot J. Fuller and Sapan Agarwal in Livermore and Matthew J. Marinella in Albuquerque, New Mexico. Salleo is an affiliate of the Stanford Precourt Institute for Energy and the Stanford Neurosciences Institute. Van de Burgt is now an assistant professor in microsystems and an affiliate of the Institute for Complex Molecular Studies (ICMS) at Eindhoven University of Technology in the Netherlands.
This research was funded by the National Science Foundation, the Keck Faculty Scholar Funds, the Neurofab at Stanford, the Stanford Graduate Fellowship, Sandia’s Laboratory-Directed Research and Development Program, the U.S. Department of Energy, the Holland Scholarship, the University of Groningen Scholarship for Excellent Students, the Hendrik Muller National Fund, the Schuurman Schimmel-van Outeren Foundation, the Foundation of Renswoude (The Hague and Delft), the Marco Polo Fund, the Instituto Nacional de Ciência e Tecnologia/Instituto Nacional de Eletrônica Orgânica in Brazil, the Fundação de Amparo à Pesquisa do Estado de São Paulo and the Brazilian National Council.
Here’s an abstract for the researchers’ paper (link to paper provided after abstract) and it’s where you’ll find the memristor connection explained,
The brain is capable of massively parallel information processing while consuming only ~1–100fJ per synaptic event1, 2. Inspired by the efficiency of the brain, CMOS-based neural architectures3 and memristors4, 5 are being developed for pattern recognition and machine learning. However, the volatility, design complexity and high supply voltages for CMOS architectures, and the stochastic and energy-costly switching of memristors complicate the path to achieve the interconnectivity, information density, and energy efficiency of the brain using either approach. Here we describe an electrochemical neuromorphic organic device (ENODe) operating with a fundamentally different mechanism from existing memristors. ENODe switches at low voltage and energy (<10pJ for 103μm2 devices), displays >500 distinct, non-volatile conductance states within a ~1V range, and achieves high classification accuracy when implemented in neural network simulations. Plastic ENODes are also fabricated on flexible substrates enabling the integration of neuromorphic functionality in stretchable electronic systems6, 7. Mechanical flexibility makes ENODes compatible with three-dimensional architectures, opening a path towards extreme interconnectivity comparable to the human brain.
A Jan. 16, 2017 news item on ScienceDaily describes what lengths researchers at Stanford University (US) will go to in pursuit of their goals,
In a lab 18 feet below the Engineering Quad of Stanford University, researchers in the Dionne lab camped out with one of the most advanced microscopes in the world to capture an unimaginably small reaction.
The lab members conducted arduous experiments — sometimes requiring a continuous 30 hours of work — to capture real-time, dynamic visualizations of atoms that could someday help our phone batteries last longer and our electric vehicles go farther on a single charge.
Toiling underground in the tunneled labs, they recorded atoms moving in and out of nanoparticles less than 100 nanometers in size, with a resolution approaching 1 nanometer.
“The ability to directly visualize reactions in real time with such high resolution will allow us to explore many unanswered questions in the chemical and physical sciences,” said Jen Dionne, associate professor of materials science and engineering at Stanford and senior author of the paper detailing this work, published Jan. 16  in Nature Communications. “While the experiments are not easy, they would not be possible without the remarkable advances in electron microscopy from the past decade.”
Their experiments focused on hydrogen moving into palladium, a class of reactions known as an intercalation-driven phase transition. This reaction is physically analogous to how ions flow through a battery or fuel cell during charging and discharging. Observing this process in real time provides insight into why nanoparticles make better electrodes than bulk materials and fits into Dionne’s larger interest in energy storage devices that can charge faster, hold more energy and stave off permanent failure.
Technical complexity and ghosts
For these experiments, the Dionne lab created palladium nanocubes, a form of nanoparticle, that ranged in size from about 15 to 80 nanometers, and then placed them in a hydrogen gas environment within an electron microscope. The researchers knew that hydrogen would change both the dimensions of the lattice and the electronic properties of the nanoparticle. They thought that, with the appropriate microscope lens and aperture configuration, techniques called scanning transmission electron microscopy and electron energy loss spectroscopy might show hydrogen uptake in real time.
After months of trial and error, the results were extremely detailed, real-time videos of the changes in the particle as hydrogen was introduced. The entire process was so complicated and novel that the first time it worked, the lab didn’t even have the video software running, leading them to capture their first movie success on a smartphone.
Following these videos, they examined the nanocubes during intermediate stages of hydrogenation using a second technique in the microscope, called dark-field imaging, which relies on scattered electrons. In order to pause the hydrogenation process, the researchers plunged the nanocubes into an ice bath of liquid nitrogen mid-reaction, dropping their temperature to 100 degrees Kelvin (-280 F). These dark-field images served as a way to check that the application of the electron beam hadn’t influenced the previous observations and allowed the researchers to see detailed structural changes during the reaction.
“With the average experiment spanning about 24 hours at this low temperature, we faced many instrument problems and called Ai Leen Koh [co-author and research scientist at Stanford’s Nano Shared Facilities] at the weirdest hours of the night,” recalled Fariah Hayee, co-lead author of the study and graduate student in the Dionne lab. “We even encountered a ‘ghost-of-the-joystick problem,’ where the joystick seemed to move the sample uncontrollably for some time.”
While most electron microscopes operate with the specimen held in a vacuum, the microscope used for this research has the advanced ability to allow the researchers to introduce liquids or gases to their specimen.
“We benefit tremendously from having access to one of the best microscope facilities in the world,” said Tarun Narayan, co-lead author of this study and recent doctoral graduate from the Dionne lab. “Without these specific tools, we wouldn’t be able to introduce hydrogen gas or cool down our samples enough to see these processes take place.”
Pushing out imperfections
Aside from being a widely applicable proof of concept for this suite of visualization techniques, watching the atoms move provides greater validation for the high hopes many scientists have for nanoparticle energy storage technologies.
The researchers saw the atoms move in through the corners of the nanocube and observed the formation of various imperfections within the particle as hydrogen moved within it. This sounds like an argument against the promise of nanoparticles but that’s because it’s not the whole story.
“The nanoparticle has the ability to self-heal,” said Dionne. “When you first introduce hydrogen, the particle deforms and loses its perfect crystallinity. But once the particle has absorbed as much hydrogen as it can, it transforms itself back to a perfect crystal again.”
The researchers describe this as imperfections being “pushed out” of the nanoparticle. This ability of the nanocube to self-heal makes it more durable, a key property needed for energy storage materials that can sustain many charge and discharge cycles.
Looking toward the future
As the efficiency of renewable energy generation increases, the need for higher quality energy storage is more pressing than ever. It’s likely that the future of storage will rely on new chemistries and the findings of this research, including the microscopy techniques the researchers refined along the way, will apply to nearly any solution in those categories.
For its part, the Dionne lab has many directions it can go from here. The team could look at a variety of material compositions, or compare how the sizes and shapes of nanoparticles affect the way they work, and, soon, take advantage of new upgrades to their microscope to study light-driven reactions. At present, Hayee has moved on to experimenting with nanorods, which have more surface area for the ions to move through, promising potentially even faster kinetics.