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OpenAI LP
We’ve created OpenAI LP, a new “capped-profit” company that allows us to rapidly increase our investments in compute and talent while including checks and balances to actualize our mission.
Most cited
Posts that commenters keep linking to, ranked by how many different people have cited them in Hacker News comments. 20 posts.
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OpenAI releases larger GPT-2 model
We’ve trained a large-scale unsupervised language model which generates coherent paragraphs of text, achieves state-of-the-art performance on many language modeling benchmarks, and performs rudimentary reading comprehension, machine translation, question answering, and summarization—all without task-specific training.
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Applying BERT models to Search
How new advances in the science of language understanding will help you find more useful information in Search.
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MuseNet
We’ve created MuseNet, a deep neural network that can generate 4-minute musical compositions with 10 different instruments, and can combine styles from country to Mozart to the Beatles. MuseNet was not explicitly programmed with our understanding of music, but instead discovered patterns of harmony, rhythm, and style…
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Better Language Models and Their Implications
Stay up to speed on the rapid advancement of AI technology and the benefits it offers to humanity.
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Autocompletion with Deep Learning
We've put together an index of testing terms and articles, covering many of the basics of testing and definitions for common searches.
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AlphaStar: Mastering the Real-Time Strategy Game StarCraft II
Games have been used for decades as an important way to test and evaluate the performance of artificial intelligence systems. As capabilities have increased, the research community has sought games with increasing complexity that capture different elements of intelligence required to solve scientific and real-world…
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Emergent Tool Use from Multi-Agent Interaction
We’ve observed agents discovering progressively more complex tool use while playing a simple game of hide-and-seek. Through training in our new simulated hide-and-seek environment, agents build a series of six distinct strategies and counterstrategies, some of which we did not know our environment supported. The…
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DiffEqFlux.jl – A Julia Library for Neural Differential Equations
DiffEqFlux.jl – A Julia Library for Neural Differential Equations...
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Grandmaster level in StarCraft II using multi-agent reinforcement learning
AlphaStar is the first AI to reach the top league of a widely popular esport without any game restrictions. This January, a preliminary version of AlphaStar challenged two of the world's top players in StarCraft II, one of the most enduring and popular real-time strategy video games of all time. Since then, we have…
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Solving the Rubik’s cube with a robot hand
We’ve trained a pair of neural networks to solve the Rubik’s Cube with a human-like robot hand. The neural networks are trained entirely in simulation, using the same reinforcement learning code as OpenAI Five paired with a new technique called Automatic Domain Randomization (ADR). The system can handle situations it…
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Microsoft is investing $1B in OpenAI
Microsoft is investing $1 billion in OpenAI to support us building artificial general intelligence (AGI) with widely distributed economic benefits. We’re partnering to develop a hardware and software platform within Microsoft Azure which will scale to AGI. We’ll jointly develop new Azure AI supercomputing…
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On-Device, Real-Time Hand Tracking with MediaPipe
Posted by Valentin Bazarevsky and Fan Zhang, Research Engineers, Google Research The ability to perceive the shape and motion of hands can be a v...
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OpenAI Releases Largest GPT-2 Text Generation Model
As the final model release of GPT-2’s staged release, we’re releasing the largest version (1.5B parameters) of GPT-2 along with code and model weights to facilitate detection of outputs of GPT-2 models. While there have been larger language models released since August, we’ve continued with our original staged release…
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Welcoming Semmle to GitHub
Today we’re announcing a big step in securing the open source supply chain: we’re welcoming Semmle to the GitHub family.
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Aroma: Using machine learning for code recommendation
Aroma is a code-to-code search and recommendation tool that uses ML to make the process of gaining insights from big codebases much easier.
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Continuing our work to improve recommendations on YouTube
That's why we update our recommendations system all the time—we want to make sure we’re suggesting videos that people actually want to watch.