View Yoshua Bengio’s profile on LinkedIn, the world’s largest professional community. As part of our ongoing Deep Learning Q&A series, I caught up with Yoshua to hear his thoughts on media interest in the field, future developments and more, ahead of his presentation at the RE•WORK Deep Learning Summit in Boston this May. Yoshua Bengio [1] FRS OC FRSC (nacido en 1964 en París, Francia) es un informático canadiense, más conocido por su trabajo en redes neuronales artificiales y … BOOK YOUR PLACE HERE. For more information and to register, please visit the event website here. Ve el perfil de Daniel Bengio en LinkedIn, la mayor red profesional del mundo. The following year, he earned the prestigious Killam Prize in computer science from the Canada Council for the Arts and was co-winner of the A.M. Turing Prize, which he received jointly with Geoffrey Hinton and Yann LeCun. Ve el perfil completo en LinkedIn y descubre los contactos y empleos de Daniel en empresas similares. What does Yoshua think is the future of AI? di LinkedIn. This website uses cookies to improve service and provide tailored ads. How can we close that gap to human-level AI? Yoshua also commented on the two systems for cognitive processing, citing Daniel Kahneman’s book ‘Thinking Fast and Slow’ with the use of ‘System 1 and System 2’ with the former encompassing intuitive, fast and automatic perception and the latter harnessing rational but sequential, slow and logistical decision making formats. The Deep Learning Summit is taking place alongside the Connected Home Summit. Yoshua further simplified this by explaining that we can draw inspiration for AI from living intelligence, suggesting that curriculum learning, cultural evolution, lateral connections, attention, distributed representations and more are all methods which are commonly used, maybe without intention, in everyday life which can then be further applied to the development of future AI algorithms. Since 1993, he has been a professor in the Department of Computer Science and Operational Research at the Université de Montréal. Holder of the Canada Research Chair in Statistical Learning Algorithms, he is also the founder and scientific director of Mila, the Quebec Institute of Artificial Intelligence, which is the world’s largest university-based research group in deep learning. The Best Way Forward For AI. In 2019, he received the ACM A.M. Turing Award, “the Nobel Prize of Computing”, jointly with Geoffrey Hinton and Yann LeCun for conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing. Yoshua Chocrón Bendahan | Madrid, Comunidad de Madrid, España | Encargado de las devoluciones | 1 contacto | Ver la página de inicio, el perfil, la actividad y los artículos de Yoshua Hear from the likes of: Early Bird tickets end on Friday 13 December. The RE•WORK Deep Learning Summit & Responsible AI Summits were brought to a close on day one with an hour-long keynote from one of the world’s leading experts and pioneers in the Deep Learning Space, Yoshua Bengio. In 2018, Yoshua Bengio collected the largest number of new citations in the world for a computer scientist thanks to his many publications. DEBATE : Yoshua Bengio | Gary Marcus. There are good sides and bad sides. Following his studies in Montreal, culminating in a Ph.D. in computer science from McGill University, Professor Bengio did postdoctoral studies … Take a read and let us know what you think! Whilst it is true that brains are incredibly complex and somewhat stochastic machines, the idea of consciousness can be associated with various computational mechanisms. In 2018, Yoshua Bengio ranked as the computer scientist with the most new citations worldwide, thanks to his many high-impact contributions. Gated orthogonal recurrent units: On learning to forget. The discovery of said disentangled representations is easier said than done, with spatial and temporal scales alongside marginal independence, simple dependency between factors and more needed. Since 1993, he has been a professor in the Department of Computer Science and Operational Research at the Université de Montréal. In the latter part of his presentation, Yoshua discussed the facets of Machine Learning currently missing to be progressive, including the need for generalisation and understanding beyond mere training distribution. When summarising his talk, Professor Bengio gave three key points to keep in mind when ‘looking forward’. Turing Award winners Yoshua Bengio and Yann LeCun spoke during a session at tthe International Conference on Learning Representations (ICLR) 2020. His titles include Full Professor of the Department of Computer Science & Operations Research at the Université de Montréal, head of the Machine Learning Laboratory (MILA), CIFAR Program Co-director of the CIFAR Neural Computation and Adaptive Perception program, and Canada Research Chair in Statistical Learning Algorithms, among many others. His current interests are centered around a quest for artificial intelligence, through machine learning, and include fundamental questions on deep learning and representation learning, the geometry of generalization in high-dimensional spaces, manifold learning, biologically inspired learning algorithms, and challenging applications of statistical machine learning. This interview originally appeared on the RE•WORK Blog. Yoshua Bengio is recognized as one of the world’s leading experts in artificial intelligence (AI) and a pioneer in deep learning. Yoshua has 4 jobs listed on their profile. RE•WORK Deep Learning Summit & Responsible AI Summits, Global Deep Learning Summit Series in San Francisco on 30-31 January, ‘Must-Read’ AI Papers Suggested by Experts -…, The ability to generalize faster from fewer examples, The ability to generalize out-of-distribution, better transfer learning, domain adaptation, reduce catastrophic forgetting in continual learning, Higher-level cognition: system 1 vs system 2, Additional compositionality from reasoning & consciousness, Discovery of causal structure and the potential to exploit it, Human-level exploitation of agents with perspective from RL, unsupervised exploration, We must build a world model which meta-learns causal effects in abstract space of causal variables. Brains tore their own side memory which we are not conscious of, but have the ability to play back. MONTREAL.AI. Yoshua Bengio is Professor of Computer Science at the Université de Montréal. What do you feel are the leading factors enabling recent advancements and uptake of deep learning?Research results have greatly improved, due also to improved hardware. Similar to the laws of physics, we should consider understanding the physical world, mostly by having figured out the laws of physics, not just by describing its consequences. Yoshua Bengio FRS OC FRSC (born 1964 in Paris, France) is a Canadian computer scientist, most noted for his work on artificial neural networks and deep learning. Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. In fact, it could be that we are over complicating that which we think machines should understand, this is sometimes seen as although we think about objects and high-level entities in the world and not necessarily about something's shape, colour or texture, more so how we interact with it, we expect machines to have a different level of affordances, which we ourselves do not. Yoshua further suggested that the talk of ‘what’s next’ is far-wide of the mark: Interestingly, Yoshua used, many times, the example of young children or babies as something which the next generation of AI can be modelled on. What are your thoughts on the recent surge of media interest surrounding deep learning? Bengio cited that this concept is going to unlock the ability to transform DL to high level human intelligence allowing for your consciousness to focus and highlight one thing at a time. Concerned about the social impact of AI, he actively contributed to the development of the Montreal Declaration for the Responsible Development of Artificial Intelligence. View the profiles of professionals named "Yoshua" on LinkedIn. In regard to the next steps for AI, it is simply not good enough to grow data sets, model sizes and computer speeds without applying this information. Select Accept cookies to consent to this use or Manage preferences to make your cookie choices. Following topics of note included Recurrent independent mechanisms, sample complexity, end-to-end adaptation, multivariate categorical MLP conditionals and more. Since 1993, he has been a professor in the Department of Computer Science and Operational Research at the Université de Montréal. View the profiles of professionals named "Bengio" on LinkedIn. In 2018, Professor BENGIO was the computer scientist who collected the largest number of new citations worldwide. Massachusetts Institute of Technology, Cambridge, MA 02139, U.S.A. [email protected] Caglar Gulcehre For more information, see our Cookie Policy. Ve los perfiles de profesionales con el nombre de «Bengio» en LinkedIn. See the complete profile on LinkedIn and discover Yoshua’s connections and jobs at similar companies. What developments can we expect to see in deep learning in the next 5 years?I don't have a crystal ball, but major challenges include improving unsupervised (or semi-supervised) learning, bringing in modelling of causal dependencies, natural language understanding, reasoning, etc. We were delighted to have Yoshua join us again this year in Canada to discuss his current work, referencing both the latest technological breakthroughs and business use application methods discovered in Deep Learning over the last twelve months. There are 10+ professionals named "Yoshua", who use LinkedIn to exchange information, ideas, and opportunities. Yoshua Bengio is recognized as one of the world’s leading experts in artificial intelligence and a pioneer in deep learning. View the profiles of professionals named "Yoshua Bengio" on LinkedIn. Yoshua Bengio will be speaking at the RE•WORK Deep Learning Summit in Boston, on 12-13 May 2016. What present or potential future applications of deep learning excite you most?Natural language understanding. See our, Department of Computer Science & Operations Research, The Intersection of Probabilistic Modeling &…, Special offer on ALL RE•WORK Deep Learning &…. There are 200+ professionals named "Bengio", who use LinkedIn to exchange information, ideas, and opportunities. LinkedIn adalah jaringan bisnis terbesar di dunia yang membantu para profesional seperti Yoshua . The ability for humans to generalise allows us to have a more powerful understanding of the world than machines currently do. Something which Yoshua credited as the future of unlocking Deep Learning was the concept of attention. Li Jing. He’s devoted much of his life to researching and advancing AI, which he is hopeful will help in the fight against COVID-19. Yoshua Bengio is Professor of Computer Science at the Université de Montréal. LinkedIn es la red profesional más grande del mundo que ayuda a profesionales como Alegría Malka Bengio a encontrar contactos internos para recomendar candidatos a un empleo, expertos de un sector y socios comerciales. Yoshua Bengio is recognized as one of the world’s leading experts in artificial intelligence (AI) and a pioneer in deep learning. Imagine if you will, that we can understand stories which are fictional, in fact, many are able to finish stories I start to tell purely because, even if it is nonsensical, humans have no problem with imagining impossible things. It is fuelled by the above progress and the impressive potential for transformative effects on society and business. That is, that we use training data, which to us is not training data. The good side is that it is helps to attract strong researchers (especially students) and funding. Daniel tiene 9 empleos en su perfil. Bengio is best-known for winning the 2018 Turing Award — nicknamed the Nobel Prize of computing — with Geoffrey Hinton and Yann LeCun, after the trio made a series of deep neural network breakthroughs. Yoshua suggested that the following are currently missing and would be necessary to make that next step: The answer for a majority of the above stated factors? His research contributions have been undeniable. This requires a necessity to quickly adapt to change and generalize out-of-distribution by sparsely recombining modules, The necessity to acquire knowledge and encourage exploratory behaviour, The need to bridge the gap between the aforementioned system 1 and system 2 ways of thinking, with old neural networks and consciousness reasoning taken into account, Ilya Sutskever, Co-Founder & Chief Scientist, OpenAI, Dawn Song, Professor of Computer Science, UC Berkeley, Jeff Clune, Sr Research Scientist & Founding Member, Uber AI Labs, Dumitru Erhan, Staff Research Scientist, Google Brain.
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