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Ian J. Goodfellow (born 1987 [1]) is an American computer scientist, engineer, and executive, most noted for his work on artificial neural networks and deep learning.He is a research scientist at Google DeepMind, [2] was previously employed as a research scientist at Google Brain and director of machine learning at Apple as well as one of the first employees at OpenAI, and has made several ...
"End-to-End Training of Deep Visuomotor Policies". Journal of Machine Learning Research. 17 (39): 1– 40. arXiv: 1504.00702. ISSN 1533-7928. Wikidata Q90313375. Chelsea Finn; Ian Goodfellow; Sergey Levine (2016). "Unsupervised Learning for Physical Interaction through Video Prediction" (PDF). Advances in Neural Information Processing Systems ...
His machine learning course CS229 at Stanford is the most popular course offered on campus with over 1,000 students enrolling some years. [23] [24] As of 2020, three of most popular courses on Coursera are Ng's: Machine Learning (#1), AI for Everyone (#5), Neural Networks and Deep Learning (#6). [25]
It was developed by a team at the MIT-IBM Watson AI Lab in IBM Research and first presented at the 2018 International Conference on Learning Representations. [2] It was mentioned and reviewed by Ian Goodfellow [3] as well. It was adopted into an educational game Fool The Bank [4] by Narendra Nath Joshi, [5] Abhishek Bhandwaldar and Casey Dugan
A generative adversarial network (GAN) is a class of machine learning frameworks and a prominent framework for approaching generative artificial intelligence.The concept was initially developed by Ian Goodfellow and his colleagues in June 2014. [1]
MuZero (MZ) is a combination of the high-performance planning of the AlphaZero (AZ) algorithm with approaches to model-free reinforcement learning. The combination allows for more efficient training in classical planning regimes, such as Go, while also handling domains with much more complex inputs at each stage, such as visual video games.
AlphaFold is a deep learning based system developed by DeepMind for prediction of protein structure. [76] Otter.ai is a speech-to-text synthesis and summary platform, which allows users to record online meetings as text. It additionally creates live captions during meetings. [77]
It is named "chinchilla" because it is a further development over a previous model family named Gopher.Both model families were trained in order to investigate the scaling laws of large language models.