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OpenAI Residency

As part of our effort to support and develop AI talent, we’re excited to announce the OpenAI Residency.

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Solving math word problems

We’ve trainedΒ a system that solves grade school math problems with nearly twice the accuracy of a fine-tuned GPT-3 model. It solves about 90% as many problems as real kids: a small sample of 9-12 year olds scored 60% on a test from our dataset, while our system scored 55% on those same problems.

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OpenAI Codex

We’ve created an improved version of OpenAI Codex, our AI system that translates natural language to code, and we are releasing it through our API in private beta starting today.

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Introducing Triton: Open-source GPU programming for neural networks

We’re releasing Triton 1.0, an open-source Python-like programming language which enables researchers with no CUDA experience to write highly efficient GPU codeβ€”most of the time on par with what an expert would be able to produce.

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OpenAI Scholars 2021: Final projects

We’re proud to announce that the 2021 class ofΒ OpenAI ScholarsΒ has completed our six-month mentorship program and have produced an open-source research project with stipends and support fromΒ OpenAI.

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Will Hurd joins OpenAI’s board of directors

OpenAI is committed to developing general-purpose artificial intelligence that benefits all humanity, and we believe that achieving our goal requires expertise in public policy as well as technology. So, we’re delighted to announce that CongressmanΒ Will HurdΒ has joined our board of directors.

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GPT-3 powers the next generation of apps

Over 300 applications are delivering GPT-3–powered search, conversation, text completion, and other advanced AI features through ourΒ API.

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Multimodal neurons in artificial neural networks

We’ve discovered neurons in CLIP that respond to the same concept whether presented literally, symbolically, or conceptually. This may explain CLIP’s accuracy in classifying surprising visual renditions of concepts, and is also an important step toward understanding the associations and biases that...

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Scaling Kubernetes to 7,500 nodes

We’ve scaled Kubernetes clusters to 7,500 nodes, producing a scalable infrastructure for large models likeΒ GPT-3,Β CLIP, andΒ DALLΒ·E, but also for rapid small-scale iterative research such asΒ Scaling Laws for Neural Language Models.

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DALLΒ·E: Creating images from text

We’ve trained a neural network called DALLΒ·E that creates images from text captions for a wide range of concepts expressible in naturalΒ language.

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CLIP: Connecting text and images

We’re introducing a neural network called CLIP which efficiently learns visual concepts from natural language supervision. CLIP can be applied to any visual classification benchmark by simply providing the names of the visual categories to be recognized, similar to the β€œzero-shot” capabilities of GP...

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Learning to summarize with human feedback

We’ve applied reinforcement learning from human feedback to train language models that are better at summarization.

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OpenAI Scholars 2020: Final projects

Our third class of OpenAI Scholars presented their final projects at virtual Demo Day, showcasing their research results from over the past five months.

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Procgen and MineRL Competitions

We’re excited to announce that OpenAI is co-organizing two NeurIPS 2020 competitions with AIcrowd, Carnegie Mellon University, and DeepMind, using Procgen Benchmark and MineRL.

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Image GPT

We find that, just as a large transformer model trained on language can generate coherent text, the same exact model trained on pixel sequences can generate coherent imageΒ completionsΒ andΒ samples. By establishing a correlation between sample quality and image classification accuracy, we show that ou...

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OpenAI API

We’re releasing an API for accessing new AI models developed by OpenAI.

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