Team update
We’ve hired more great people to help us achieve our goals. Welcome, everyone!
We’ve hired more great people to help us achieve our goals. Welcome, everyone!
We’ve hired more great people to help us achieve our goals. Welcome, everyone!
- Dario Amodei. Dario(opens in a new window) was one of the lead authors of Deep Speech 2(opens in a new window), a speech system which achieved near-human performance on many speech tasks. He is also a main co-author of “Concrete Problems in AI Safety(opens in a new window)”, which highlights issues related to accidents in machine learning systems. Prior to OpenAI, he worked at Google Brain.
- Filip Wolski. Filip’s(opens in a new window) recent background is in “practical” modeling, having spent the last few years working in the high-frequency trading space. In the past he enjoyed problem-solving in programming competitions, and won the IOI(opens in a new window) and ACM ICPC(opens in a new window).
- Jack Clark. Jack(opens in a new window) has spent the past few years writing about artificial intelligence and distributed systems, most recently at Bloomberg and BusinessWeek. His articles have covered technologies like memory networks(opens in a new window), image generation(opens in a new window), and reinforcement learning for robots(opens in a new window), and issues like diversity within AI(opens in a new window). As our Strategy and Communications Director, he will help with community outreach, policy, communications, and strategy.
- Scott Gray. Scott(opens in a new window) was previously an engineer at Nervana Systems(opens in a new window) where he focused on optimizing the performance of deep networks on GPUs. His assembly-level optimizations(opens in a new window) for dense linear algebra and convolution remain the fastest available. When not writing software(opens in a new window) he’s usually spending his time reading up on the latest research in neuroscience and related fields.
- Zain Shah. Zain(opens in a new window) previously led deep learning efforts to build a collaborative human-machine intelligence system at Clara Labs(opens in a new window). He’s also worked on speech synthesis(opens in a new window) and computational neuroscience(opens in a new window), built Mosaic(opens in a new window), and founded a mobile behavioral analytics company(opens in a new window). He most recently built a GIF search engine(opens in a new window) using deep multimodal embeddings.
We’re also pumped to be working with the following people for a more limited period of time:
- Catherine Olsson. Catherine(opens in a new window) built OpenAI Gym’s REST API(opens in a new window), which has already attracted users in Lua(opens in a new window), C++(opens in a new window), Java(opens in a new window), and Rust(opens in a new window). She graduated with a perfect GPA in CS and Brain & Cognitive Science from MIT, and has extensive research experience in computational neuroscience(opens in a new window) and psychology(opens in a new window). Catherine has taught programming and applied math(opens in a new window) for six years, including outreach to women and underrepresented minorities.
- Harri Edwards. Harri(opens in a new window) is a PhD student at the University of Edinburgh, where he is researching models that can quickly adapt to new situations by learning to represent datasets(opens in a new window).
- Igor Mordatch. Igor(opens in a new window) is interested in optimal control, machine learning, and their applications to robotics, biomechanics, and neuroscience. His PhD was in automated discovery and learning of complex movement behaviors(opens in a new window). He will join the faculty at CMU(opens in a new window) in September 2017.
- Taco Cohen. Taco(opens in a new window) is a PhD student working on applied and theoretical problems in representation learning. Most recently he invented group equivariant convolutional neural networks (G-CNNs(opens in a new window)), a generalization of CNNs that improves the statistical efficiency of these models by exploiting symmetries.
- Tambet Matiisen. Tambet(opens in a new window) is a PhD student from University of Tartu, Estonia. He previously worked as a software engineer and founded his own startup(opens in a new window). His recent projects range from making deep reinforcement learning agents cooperate(opens in a new window) to predicting a rat’s location from its brain activity. He also wrote an accessible introduction to deep Q-learning(opens in a new window).