Vicarious Visions is an American video game developer. Vicarious Visions' games accounted for over 2.5 billion dollars in retail sales and over 40 million units of its software have been sold worldwide. The headquarters of Vicarious Visions is located in Menands, New York. Wikipedia.
Agency: Cordis | Branch: FP7 | Program: MC-ITN | Phase: FP7-PEOPLE-2011-ITN | Award Amount: 3.76M | Year: 2011
Consumer science is touching the lives of 493 million EU Consumers with their consumption representing 58% of the EU GDP, yet the insights of consumer research typically fail to have a substantial impact on consumer welfare. The EC acknowledges the problem and places it high on its policy priorities. Consumer research is scattered across several disciplines in the social sciences with little communication occurring between research and practice. The CONsumer COmpetence Research Training (CONCORT) tackles these issues. We abandon the marketing perspective of the persuasive agent trying to affect consumer decisions, and aim to pioneer research from the consumer perspective. We study consumer competence, a broad set of abilities, intuitions, knowledge and skills consumers need in order to make decisions that help them navigate successfully in the economic environment. CONCORT will train 14 ESRs in this new perspective, in 8 high level partners: Three business schools, 2 broad universities, and 3 corporate partners, 2 of which are SMEs. The academic partners are top quality departments from 3 disciplines, namely consumer behaviour, behavioural economics, and health psychology. The corporate partners are innovators in advanced behavioural measurement tools. CONCORT adds an optimal blend between traditional training methods (frequent conventions, high quality in-house doctoral courses), innovative learning instruments (blended learning, skills portfolio), and thorough practice training through industrial secondments. We will train ESRs to see the link between their theoretical training and thematic areas of real life consumer interest (environment, overspending, food choice, etc.). Relying on a strong infrastructure (second life, behavioural labs), and guided by a flexible but demanding modern management structure, CONCORT sets out to create 14 success stories of collaboration, excellence and professional accomplishment in consumer science. Those of our ESRs.
Agency: Cordis | Branch: H2020 | Program: MSCA-ITN-ETN | Phase: MSCA-ITN-2014-ETN | Award Amount: 3.89M | Year: 2015
Early onset neurodevelopmental disorders such as autism spectrum disorders (ASD) and attention-deficit hyperactivity disorder (ADHD) are rather common, and affect more than 30 million children in Europe. The disorders carry a huge burden to the patients and their families and to society in general. This burden is linked to their chronic course and the absence of curative treatments. These neurodevelopmental disorders are thought to result from the disruption of normal brain development and related neurobiological mechanisms during the prenatal and early postnatal period. Recent advances in technology, infrastructure and analytic tools allow us now to identify these disruptions in brain development in the prenatal and early postnatal period, examine how this compromises the development of key social, attentional, motor and cognitive skills, and help understanding of the mechanisms that lead to neurodevelopmental disorders. This will facilitate developing new approaches to early detection, diagnosis and treatment. BRAINVIEW ETN provides a multidisciplinary and intersectoral (academia, companies, patient organizations) network environment in which cutting-edge science is combined with training young researchers in such an approach.
News Article | March 12, 2015
Editor’s note: Dr. Nathan Wilson is co-founder and CTO of Nara Logics, a big data intelligence company creating a brain-based AI platform. There’s a pragmatic approach to the great artificial intelligence debate, one that responsibly answers both the trepidations and aspirations of top scientists and technologists in this field. I agree that anyone concerned with technology should be jolted awake by the warning that Stephen Hawking, Elon Musk Bill Gates and many scientists have now delivered. The early days of “let’s see what happens” with AI should justifiably be over. There is simply too much at stake in the coming decades with new technology that is already fundamentally challenging our privacy and autonomy as individuals and our attention and consciousness as human beings. However, the new path raised by Musk and colleagues is equally risky. By drawing neon-sign outlines around what we fear most, we risk manifesting these exact fears into reality. By demonizing a crucial discipline, we make it less likely to be the chosen destination for many moral contributors and pursuits. A “third way” exists to navigate the exploration of AI. When the Internet started, despite its military DNA, key contributors infused and amplified a “spirit” of openness, wonder and exploration that remain responsible for its positive outcomes around the globe today. It is possible this very spirit, rather than a culture of fear, will be crucial to incubating a nascent AI that resonates with our ideals. Just as Carl Sagan urged us to approach extraterrestrial intelligence with an instinct of trust rather than a “guns drawn” suspicion, there is wisdom in employing the same logic with artificial intelligence – in such encounters, to quote William James, the belief will create the fact, and our creations take on the character of our temper. Applying this spirit has three practical dimensions that are critical for defining this third approach and separating it from both rampant optimism and disabling fear. First, a mandate to focus on a closer time horizon. Pundits are often drawn to the most intellectually stimulating ideas that are decades or even centuries away. But fundamental issues in the technosphere that will impact our “AI nature” are being decided right now. Battles for how we approach privacy, how we avoid digital overload and cyborgization, and how we interact in a machine-assisted world are being won and lost now. This will reverberate in user interfaces and compute-power direction for decades to come, when AI starts to really get going. Simply put, as with children, we must hurl ourselves in to shaping AI in its early years, not by injecting it with post-hoc rules once it gets to college, which is essentially the approach of the open letter. Second, for nascent AI to grow up well-adjusted with a moral and logical compass, it must be exposed to many voices and not just raised by cold logic. It’s encouraging to see social scientists, entrepreneurs and even philosophers like Nick Bostrom contributing foundationally to this discussion. This is another reason why we need more women and minorities in tech to add diverse and stabilizing perspectives. We need contributions from neuroscientists and psychologists that study cognition. Finally, we need to change the emphasis of our tech development from brunch apps in Silicon Valley to problems of the world at large – this will determine the goals and evolution of our AI decades from now more than any theoretical seat belts and crash helmets we might try to put in place later. Finally, to nurture the moral, humanity-supporting applications of AI, we should not be afraid to go deep with basic research, because this will teach us more about who we are and thus help erode the real challenge of AI, that it is not “people vs. nature” but “people vs. themselves.” Toward this end, a growing number of academic researchers and a new breed of companies and technologies like Google’s DeepMind, Vicarious, IBM Watson and our team at Nara Logics are developing a primitive new class of “brain AI.” This sort of boundary-pushing is a natural area of concern, but such explorations should not be shunted — this brain-like AI is application-neutral and brings us closer to understanding our own minds, morals and decision-making processes, thus uncovering the definitions for human-supportive applications. It is only with this deeper exploration and self-knowledge of our own mechanics that we can arbitrate and reconcile the concerns that will increasingly arise. As Bill Gates said, “I… don’t understand why some people are not concerned.” Accepting that wisdom, we propose a “selective optimism” to excite, rather than a blanket concern to inhibit, as a more dexterous way to sculpt our outcome. In that spirit, if AI can be made into an ally in our own self-discovery and development, our society will experience the same degree of wonder and positivity as we did at the dawn of the space age, as well as the remarkable progress and openness brought by the Internet age.
News Article | October 28, 2013
Vicarious - Turing Test 1: Captcha from Vicarious Inc on Vimeo. What’s this I hear about a breakthrough in artificial intelligence? A software company called Vicarious claims to have created a computer algorithm that can solve CAPTCHA with greater than 90% accuracy. What is CAPTCHA and why should I care? You’ve already encountered CAPTCHAs if you’ve ever created an email account with Google, set up a PayPal account, or commented on some WordPress blogs. CAPTCHAs are those wavy, distorted letters that you have to type into a box. The purpose is to prove that you are human rather than a computer-controlled “bot” making mischief on the Internet. You should care for at least two reasons. First, CAPTCHA is the security system used across the entire Internet to help prevent unlawful use of websites. So if that has been broken, the entire Internet should probably start transitioning to a new security system. But more exciting, this might be a major breakthrough in computer science. Creating machines that can see the world and make sense of images as humans do is one of the “hard problems” in artificial intelligence. Breaking CAPTCHA is a milestone on that road—if Vicarious has pulled it off. So is it a breakthrough or not? That depends on how they broke CAPTCHA. Previous attempts have used brittle solutions that relied on quirks of how different CAPTCHAs are implemented. For example, a CAPTCHA that just slants the letters and peppers them with dots can be solved by removing dots and then looking for recognizable letters when the image is bent in various directions. But those attacks have been easily squelched by tweaking the way that CAPTCHAs are generated. If Vicarious has merely created a new set of brittle solutions, then it is not a breakthrough. If the new algorithm does indeed solve a deeper problem in machine vision, and is indeed as good as human vision at solving any CAPTCHA-like problem, then this is breakthrough territory. That is exactly what is being claimed. In fact, Vicarious’s researchers go on to claim that their algorithm works in an analogous way to the human brain. Do they offer any proof? Ah, there’s the rub. Vicarious has credibility, given the scientists working there, but its current offer of proof is little more than a press release sent out to journalists and a video (above). The company has released no software code and no technical explanation, and as Vicarious co-founder Dileep George said in an email, “There are no current plans to write a paper, but things could change in the future.” To be fair, you wouldn’t want Vicarious to share the code. Unleashing a CAPTCHA hack before the world has time to adopt a new security system would be disastrous. Still, the science-by-press-release has annoyed many computer scientists with whom Science talked. As one bluntly put it, “the material provided is not sufficient to back up their claims.” And CAPTCHA creator Luis van Ahn, a computer scientist at Carnegie Mellon University in Pittsburgh, Pennsylvania, is not convinced. He sent ScienceNOW this defiant message: In an emailed response, Vicarious cofounder Scott Phoenix defends his company’s algorithm: Our approach gives a general way to solve text-based captchas, because we solve the segmentation problem in a very general way. Our system is extremely distortion tolerant, the systems that you saw were trained on just a handful of images per character. He can add more distortions, but we can simply add a few more training data that captures that distortion, if it is not already captured by the existing training examples. Yes, there are problems in image recognition we haven’t solved yet, and there can be captchas based on that. All we are claiming is that our approach fundamentally breaks all text-based captchas. You cannot hope to patch up the text-based captchas by adding more distortions or clutter. Our approach is immune to all such transformations. What does all this have to do with the human brain? Vicarious calls its algorithm the Recursive Cortical Network™. The reference to the human brain is built right into the name, as well as the commercial nature of this research. Whether it really has anything to do with how cortical neurons process information remains to be seen. Breaking CAPTCHA wasn’t the goal, says Phoenix. “It was just a sanity check. We believe that higher level intelligences are all built on the somatosensory system. So that’s why we started with vision.” The company plans to hook up this visual system to robots. The benchmark then will be, for example, “Preparing a meal in an arbitrary kitchen.” So does it really work? Vicarious was concerned when I sent the company an email describing its claim as “unsubstantiated”, so Phoenix and George offered to do a demonstration over Skype. I sent them CAPTCHAs off the internet. They were able to solve the first one, from a Paypal website, immediately. But the algorithm was stumped by two others. One had Cyrillic characters. “We haven’t trained our system on other languages yet,” said Phoenix. And it also failed on a CAPTCHA that used alternating patches of black and white like a chess board. In a follow-up email, George gave this explanation: So why didn’t our demo work on the checkerboard pattern? Before the image is presented to our algorithm, it has to pass through a retina+LGN kind of processing (it is a basic, common-to-all-CAPTCHAS pre-processing). In the demo, we had a specialized retina which was faster and gave a few percentage points more accuracy on reCAPTCHA; the downside being it not working well on the checkerboard pattern. (Or any pattern where some portions of the letter are black and some portions of the letter are white). Its just like putting on sunglasses being specialization we add to our eyes for going out in the sun, which causes us to see some other patterns not as well. It is not a fundamental flaw and we have tested that our system works with the checkerboard pattern as well This story provided by ScienceNOW, the daily online news service of the journal Science.
News Article | March 21, 2014
Mark Zuckerberg, Elon Musk, and Ashton Kutcher want to build an artificial brain that thinks the way you think. As reported by Wall Street Journal, the Facebook CEO, the co-founder of Tesla, and the dude from That 70s Show were part of a $40 million investment in a new kind of artificial intelligence called Vicarious. The San Francisco-based startup aims to recreate your neocortex, the part of your brain that handles cognitive functions like language and math. That’s an ambitious goal, but the company’s efforts are part of a larger trend across the tech world, with company’s such as Google, IBM, and Microsoft as well as Zuckerberg’s Facebook all exploring ways of mimicking the brain with hardware and software. IBM has long explored the possibility of an artificial brain. Google recently hired AI pioneer Geoff Hinton, before acquiring another artificial intelligence startup known as DeepMind. And Facebook just hired Yann LeCun, who, along with Hinton, helped pioneer a new AI field called “deep learning.” The aim here is to vastly improve the ability of machines to recognize images or process natural language. In other words, they want to build things like Apple Siri that actually work like you expect them to. Vicarious sets itself apart from others in the field by focusing on a model of the neocortex, the part of the brain dedicated high-level cognitive functions like spatial reasoning and language processing. Vicarious co-founder Dileep George previously built a similar company called Numenta (now known as Grok) with Palm co-founder Jeff Hawkins and former Palm CEO Donna Dubinsky in 2005. To be sure, actually building a working copy of a the full neocortex — let alone the entire human brain — may never be possible. But by simulating just a tiny slice of the cortex, both Grok and Vicarious have already achieved some tangible results. Grok sells an IT infrastructure monitoring service, while Vicarious has been focused on creating a system that can recognize images. The company made headlines last year with a tool it claimed could solve CAPTCHAs — those strings of letters you have to enter into web applications to prove you’re human. Other than that, the company has been pretty tight lipped about its plans. This is the second big funding round for Vicarious, and it was lead by venture capital outfit Formation 8. The first $15 million round included investments by Facebook and Asana co-founder Dustin Moskovitz; former Facebook CTO and Quora founder Adam D’Angelo; PayPal and Palantir co-founder Peter Thiel; and Palantir co-founder Joe Lonsdale. Facebook didn’t take part in the latest round. Zuckerberg made the investment on his own, the company told Wall Street Journal, saying it doesn’t indicate an interest on Facebook’s behalf in using Vicarious software. But Facebook’s interest in AI is well documented. And it’s not alone.