2021年7月28日 · 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 code—most of the time on par with what an expert would be able to produce.

For example, we develop Triton, a language and compiler for writing custom GPU kernels. The aim of Triton is to provide an open-source environment to write fast code at higher productivity than CUDA. We frequently collaborate with other teams to speed up the development of new state-of-the-art capabilities.

For example, we develop Triton, a language and compiler for writing custom GPU kernels. The aim of Triton is to provide an open-source environment to write fast code at higher productivity than CUDA. We frequently collaborate with other teams to speed up the development of new state-of-the-art capabilities.

2023年12月1日 · Writing all kernels in OpenAI’s Triton language; Reduce data movements via inplace operations; And doing other maths and coding trickery!

We believe our research will eventually lead to artificial general intelligence, a system that can solve human-level problems. Building safe and beneficial AGI is our mission.

2021年9月12日 · Two NLP transformer AI are trained on a curated dataset of programming language theory etc. An artificial environment is set up with the initial condition that they are experts in the field of Python. They are engaged with each other in a collaborative discussion on creating a new programming language for training and running NLP AI algorithms. They …

OpenAI o1 is trained to spend more time thinking before responding and reasons through complex questions across fields like math, science, and coding.

OpenAI

Introducing OpenAI o1 We've developed a new series of AI models designed to spend more time thinking before they respond. Here is the latest news on o1 research, product and other updates.

2022年6月9日 · At OpenAI, we are training and improving large models from the underlying infrastructure all the way to deploying them for real-world problems. If you’d like to put the ideas from this post into practice—especially relevant for our Scaling and Applied Research teams—we’re hiring ⁠!