Samy Bengio | |
---|---|
Born | 1965 (age 58–59) |
Nationality | Canadian |
Alma mater | Université de Montréal |
Scientific career | |
Fields | Computer science |
Institutions | Google, IDIAP Research Institute, Microcell Labs |
Thesis | Optimisation d'une règle d'apprentissage pour réseaux de neurones artificiels (Optimization of a learning rule for artificial neural networks) (1993) |
Website | bengio |
Samy Bengio is a Canadian computer scientist, Senior Director of AI and Machine Learning Research at Apple, [1] and a former long-time scientist at Google [2] known for leading a large group of researchers working in machine learning including adversarial settings. Bengio left Google shortly after the company fired his report, Timnit Gebru, without first notifying him. [3] [4] At the time, Bengio said that he had been "stunned" by what happened to Gebru. [5] He is also among the three authors who developed Torch in 2002, [6] the ancestor of PyTorch, [7] one of today's two largest machine learning frameworks. [8]
Bengio obtained his Ph.D. in Computer Science in 1993 with a thesis titled Optimization of a Parametric Learning Rule for Neural Networks from the Université de Montréal. Before that, Bengio got an M.Sc. in Computer Science in 1989 with a thesis on Integration of Traditional and Intelligence Tutoring Systems from the same university, together with a B.Sc. in Computer Science in 1986.
According to DBLP, Samy Bengio has authored around 250 scientific papers on neural networks, machine learning, deep learning, statistics, computer vision and natural language processing. [9] The most cited [10] of these include some of the early works sparking the 2010s deep learning revolution by showing how to explore the many learned representations obtained through deep learning, [11] one of the first deep learning approaches to image captioning, [12] efforts to understand why deep learning works [13] leading to many follow-up works. [14] He also worked on the first evidence that adversarial examples can exist in the real world, i.e. one can really change a physical object such that a machine learning system would be fooled [15] and one of the first works on zero-shot recognition, i.e., recognizing classes never seen during training. [16]
Bengio worked at the IDIAP Research Institute and the École Polytechnique Fédérale de Lausanne in Switzerland, from 1999 to 2007. [17]
He was General Chair of the Conference on Neural Information Processing Systems (NeurIPS) in 2018 [18] served as program chair of NeurIPS in 2017 [19] and is currently a board member. [20] He was also program chair of ICLR (2015-2016) [21] and sits on its board (2018-2020). [22]
Bengio is also an editor of the Journal of Machine Learning Research . [23]
Samy Bengio was born to two Moroccan Jews who emigrated to France and Canada. He is the brother of Turing Award winner Yoshua Bengio. [24] Both of them lived in Morocco for a year during their father's military service there. [24] His father, Carlo Bengio, was a pharmacist who wrote theatre pieces and ran a Sephardic theatrical troupe in Montreal that played Judeo-Arabic pieces. [25] [26] His mother, Célia Moreno, is also an artist who played in one of the major theatre scenes of Morocco that was run by Tayeb Seddiki in the 1970s. [27]
Jürgen Schmidhuber is a German computer scientist noted for his work in the field of artificial intelligence, specifically artificial neural networks. He is a scientific director of the Dalle Molle Institute for Artificial Intelligence Research in Switzerland. He is also director of the Artificial Intelligence Initiative and professor of the Computer Science program in the Computer, Electrical, and Mathematical Sciences and Engineering (CEMSE) division at the King Abdullah University of Science and Technology (KAUST) in Saudi Arabia.
Geoffrey Everest Hinton is a British-Canadian computer scientist and cognitive psychologist, most noted for his work on artificial neural networks. From 2013 to 2023, he divided his time working for Google and the University of Toronto, before publicly announcing his departure from Google in May 2023, citing concerns about the risks of artificial intelligence (AI) technology. In 2017, he co-founded and became the chief scientific advisor of the Vector Institute in Toronto.
The Conference and Workshop on Neural Information Processing Systems is a machine learning and computational neuroscience conference held every December. The conference is currently a double-track meeting that includes invited talks as well as oral and poster presentations of refereed papers, followed by parallel-track workshops that up to 2013 were held at ski resorts.
Yann André LeCun is a Turing Award winning French computer scientist working primarily in the fields of machine learning, computer vision, mobile robotics and computational neuroscience. He is the Silver Professor of the Courant Institute of Mathematical Sciences at New York University and Vice-President, Chief AI Scientist at Meta.
The AAAI Conference on Artificial Intelligence (AAAI) is one of the leading international academic conference in artificial intelligence held annually. Along with ICML, NeurIPS and ICLR, it is one of the primary conferences of high impact in machine learning and artificial intelligence research. It is supported by the Association for the Advancement of Artificial Intelligence. Precise dates vary from year to year, but paper submissions are generally due at the end of August to beginning of September, and the conference is generally held during the following February. The first AAAI was held in 1980 at Stanford University, Stanford California.
Deep learning is the subset of machine learning methods based on artificial neural networks with representation learning. The adjective "deep" refers to the use of multiple layers in the network. Methods used can be either supervised, semi-supervised or unsupervised.
Google Brain was a deep learning artificial intelligence research team under the umbrella of Google AI, a research division at Google dedicated to artificial intelligence. Formed in 2011, Google Brain combined open-ended machine learning research with information systems and large-scale computing resources. The team has created tools such as TensorFlow, which allow for neural networks to be used by the public, with multiple internal AI research projects. The team aims to create research opportunities in machine learning and natural language processing. The team was merged into former Google sister company DeepMind to form Google DeepMind in April 2023.
Yoshua Bengio is a Canadian computer scientist, most noted for his work on artificial neural networks and deep learning. He is a professor at the Department of Computer Science and Operations Research at the Université de Montréal and scientific director of the Montreal Institute for Learning Algorithms (MILA).
Ian J. Goodfellow is an American computer scientist, engineer, and executive, most noted for his work on artificial neural networks and deep learning. He was previously employed as a research scientist at Google Brain and director of machine learning at Apple and has made several important contributions to the field of deep learning including the invention of the generative adversarial network (GAN). Goodfellow co-wrote, as the first author, the textbook Deep Learning (2016) and wrote the chapter on deep learning in the authoritative textbook of the field of artificial intelligence, Artificial Intelligence: A Modern Approach.
Raquel Urtasun is a professor at the University of Toronto. Urtasun uses artificial intelligence, particularly deep learning, to make vehicles and other machines perceive the world more accurately and efficiently.
Yee-Whye Teh is a professor of statistical machine learning in the Department of Statistics, University of Oxford. Prior to 2012 he was a reader at the Gatsby Charitable Foundation computational neuroscience unit at University College London. His work is primarily in machine learning, artificial intelligence, statistics and computer science.
Mila - Quebec AI Institute is a research institute in Montreal, Quebec, focusing mainly on machine learning research. Approximately 1000 students and researchers and 100 faculty members, were part of Mila in 2022. Along with Alberta's Amii and Toronto's Vector Institute, Mila is part of the Pan-Canadian Artificial Intelligence Strategy.
Artificial neural networks (ANNs) are models created using machine learning to perform a number of tasks. Their creation was inspired by neural circuitry. While some of the computational implementations ANNs relate to earlier discoveries in mathematics, the first implementation of ANNs was by psychologist Frank Rosenblatt, who developed the perceptron. Little research was conducted on ANNs in the 1970s and 1980s, with the AAAI calling that period an "AI winter".
Joseph (Yossi) Keshet is an Israeli professor in the Electrical and Computer Engineering Faculty of the Technion.
Black in AI, formally called the Black in AI Workshop, is a technology research organization and affinity group, founded by computer scientists Timnit Gebru and Rediet Abebe in 2017. It started as a conference workshop, later pivoting into an organization. Black in AI increases the presence and inclusion of Black people in the field of artificial intelligence (AI) by creating space for sharing ideas, fostering collaborations, mentorship, and advocacy.
François Chollet is a French software engineer and artificial intelligence researcher currently working at Google. Chollet is the creator of the Keras deep-learning library, released in 2015, and a main contributor to the TensorFlow machine learning framework. His research focuses on computer vision, the application of machine learning to formal reasoning, abstraction, and how to achieve greater generality in artificial intelligence.
Oriol Vinyals is a Spanish machine learning researcher at DeepMind, where he is the principal research scientist. His research in DeepMind is regularly featured in the mainstream media especially after being acquired by Google.
Mi Zhang is a computer scientist at Ohio State University, where he is an Associate Professor of Computer Science and Engineering and the director of AIoT and Machine Learning Systems Lab. He is best known for his work in Edge AI, Artificial Intelligence of Things (AIoT), machine learning systems, and mobile health.
Sébastien Bubeck is a French-American computer scientist and mathematician. He is currently a Senior Principal Research Manager at Microsoft Research in the Machine Learning Foundations group and was formerly professor at Princeton University. He is known for his contributions to online learning, optimization and more recently studying deep neural networks, and in particular transformer models.
AI safety is an interdisciplinary field concerned with preventing accidents, misuse, or other harmful consequences that could result from artificial intelligence (AI) systems. It encompasses machine ethics and AI alignment, which aim to make AI systems moral and beneficial, and AI safety encompasses technical problems including monitoring systems for risks and making them highly reliable. Beyond AI research, it involves developing norms and policies that promote safety.
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