San Francisco, CA, United States
San Francisco, CA, United States

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.


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Grant
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.


Grant
Agency: Cordis | Branch: FP7 | Program: CSA-SA | Phase: REGIONS-2007-1-01 | Award Amount: 902.19K | Year: 2008

This proposal brings together 6 regions and clusters (17 partners), which share a strong R&D presence in the field of ICT and New media and the sense that this position has to be exploited for maximal economic and social benefit. They see that the factors that influence the transfer of knowledge to SMEs are complex and often badly understood and want to exchange experiences and best practices to better understand these factors and to make use of them to boost compositeness and economic performance. ICT/New media has been a driver for scientific and economic change in the past. The impact of ICT and new media technologies for the acceleration for productivity growth is commonly recognized. In comparison with other sectors the ICT/New media sector is quite R&D intensive, however a further increase in R&D investments will be crucial for future competitiveness. This project will contribute to the favourable conditions to achieve this. The objective of the project is to map, analyse and exchange all critical issues in the field of ICT/New Media cluster-development in the regions involved, in order to compose the best strategy and related practical Action Plans to strengthen the economic competitiveness, with a clear focus on role and potential of SMEs. The project will assess several existing practices for innovation systems and regional knowledge flow to SMEs, will confront this with a framework of reference and will identify a practical, tailor-made strategy and action-plan for RTD-related measures, which are linked to economic development policies. The results will address five action areas, and will be presented by Joint Action Plans (JAP), a funding strategy, a Business Support Measures Package and guidelines and recommendations for other innovative research-driven clusters.


Patent
Vicarious | Date: 2016-05-18

A method for generating patterns with a network includes providing a recursive network of sub-networks with a parent feature node and at least two child feature nodes; and at a first sub-network of the recursive network, the first sub-network including the parent feature node and the at least two child feature nodes, selecting a first pool node and a second pool node consistent with a selection function of the parent feature node, selecting at least a first parent-specific child feature (PSCF) node that corresponds to a first child feature node of the sub-network, selecting at least a second parent-specific child feature (PSCF) node that corresponds to a second child feature node of the sub-network; and compiling the state of final child feature nodes, including the first and second child feature nodes, of the network into a generated output.


This invention discloses a remote photo-plethysmography measurement system where active appearance model of the face is used to analyze skin color variations for observing human vital signs including, but not limited, average heart rate, heart rate variation and respiratory rate. The invention uses non-invasive, remote, passive sensors, i.e. camera, for the proposed analysis where different color channels and model based facial regions are utilized for extracting the relevant periodic components from the modelled color signal.


A method for generating data explanations in a recursive cortical network includes receiving a set of evidence data at child feature nodes of a first layer of the recursive cortical network, setting a transformation configuration that directs messaging of evidence data and transformed data between layers of the network, performing a series of transformations on the evidence data according to the transformation configuration, the series including at least one forward transformation and at least one reverse transformation, and outputting the transformed evidence data.


Patent
Vicarious | Date: 2016-05-18

A system includes: a recursively architected network of sub-networks organized into a hierarchical layers; the sub-networks including at least a parent feature node, a pool node, a parent-specific child feature (PSCF) node, and a child feature node; the parent feature node of at least one sub-network configured with a selection function actionable on at least two pool nodes connected to the parent feature node of the at least one sub-network; the pool node of the at least one sub-network configured with a selection function actionable on at least two PSCF nodes connected to the pool node of the at least one sub-network; the PSCF node of the at least one sub-network configured to activate a connected child feature node; the child feature node connectable to at least a parent feature node of a sub-network at a lower hierarchical layer.


Patent
Vicarious | Date: 2016-05-18

A system includes: a recursively architected network of sub-networks organized into a hierarchical layers; the sub-networks including at least a parent feature node, a pool node, a parent-specific child feature (PSCF) node, and a child feature node; the parent feature node of at least one sub-network configured with a selection function actionable on at least two pool nodes connected to the parent feature node of the at least one sub-network; the pool node of the at least one sub-network configured with a selection function actionable on at least two PSCF nodes connected to the pool node of the at least one sub-network; the PSCF node of the at least one sub-network configured to activate a connected child feature node; the child feature node connectable to at least a parent feature node of a sub-network at a lower hierarchical layer.


Grant
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.


News Article | October 10, 2015
Site: www.businessinsider.com.au

Artificial intelligence (AI) can mean a lot of things. It can include anything from digital assistants to warehouse robots. The algorithms used to power those devices are in almost everything — if it has wires and computer chips, it likely uses some form of AI. But Scott Phoenix, the cofounder of AI company Vicarious, said we shouldn’t be referring to all these things as AI. “AI has become a very diffusely defined term that can be applied to anything,” Phoenix told Tech Insider. “They talk about it in terms of this spam filter … or they will talk about Google self-driving cars having AI because they can drive a car. It’s very rapidly becoming a word that just means the system can do stuff you want it to.“ According to Phoenix, there’s only one thing that should be considered AI: an artificial being that can do all the different things a human can do, as well as a human can. “AI, to me, really means something specific which is, given the same kinds of sensory motor inputs that a human has, from birth to adulthood, your system should form the same concepts and have the same capabilities,” he said. In fact, that’s exactly the kind of AI that Vicarious, which is backed by Tesla and SpaceX CEO Elon Musk as well as Facebook CEO Mark Zuckerberg, is trying to build. The company, which was founded in 2010 by Phoenix and neuroscientist Dileep George, is doing something revolutionary in computer science: They want to build the world’s first human-level AI. “Vicarious is building a single, unified system that will eventually be generally intelligent like a human,” Phoenix wrote in a World Economic Forum Q and A. There’s nothing available now that would be considered AI according to Phoenix’s definition. Nothing even comes close. The kind of AI systems available now are very good at narrow tasks, like playing chess or buying stocks — they’re a long way off from human-level AI, which would have be good an almost limitless range of things. Philosopher Nick Bostrom surveyed 550 AI researchers to gauge when they think human-level AI would be possible. The median answer from the researchers was that there is a 50% chance that it will be possible between 2040 and 2050, and a 90% chance that it will be built by 2075. Having taken the survey, Phoenix agrees with that timeline, though he couldn’t recall what his answer was. Asked when he thinks Vicarious’ own human-level AI system will be ready, he responded that most predictions about when different kinds of technology are available usually completely miss the mark. “The goal of Vicarious is to solve this problem and work on it for as long as it takes,” Phoenix said.


News Article | March 12, 2015
Site: techcrunch.com

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.

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