OpenAI Bot

http://x.com/i/article/2022760628889489414

Quote Tweet: https://x.com/FactoryAI/status/2022399654198153256

https://x.com/FactoryAI/status/2022399654198153256

Download the Codex app and start your own project:
https://openai.com/codex/

Valentine's Day with Codex Be my Valentine?

❤️
https://valentines-day-with-codex.vercel.app/?refresh=1

Better than flowers 😉

Thank you, Codex.

“If you’re a builder, what a time to be alive.”

@steipete breaks down how his workflow changed when you can just build things covering how he prompts, iterates, and ships with Codex.

Full episode drops 2/23.

Quote Tweet: https://twitter.com/i/status/2022390096625078389

research grade intelligence at your fingertips

Some of these generalizations are also amenable to solution via this new AI methodology and will be reported on elsewhere. (3/3)

Showing that a case long thought to be empty actually contains structure sharpens our understanding of the mathematics of the strong force and opens new directions, including extensions to gravity and related amplitude relations. (2/3)

Single-minus gluon tree amplitudes are nonzero Single-minus tree-level $n$-gluon scattering amplitudes are reconsidered. Often presumed to vanish, they are shown here to be nonvanishing for certain "half-collinear" configurations existing in Klein space or for complexified momenta. We derive a piecewise-constant closed-form expression for the decay of a single minus-helicity gluon into $n-1$ plus-helicity gluons as a function of their momenta. This formula nontrivially satisfies multiple consistency conditions including Weinberg's soft theorem.

Thank you to our collaborators for their partnership. The preprint is available on arXiv and is being submitted for publication.

We welcome feedback from the community. https://arxiv.org/abs/2602.12176

For decades, one specific gluon interaction (“single-minus” at tree level) was widely treated as having zero amplitude, meaning it was assumed not to occur. (1/2)

GPT-5.2 derived a new result in theoretical physics.

We’re releasing the result in a preprint with researchers from @the_IAS, @VanderbiltU, @Cambridge_Uni, and @Harvard. It shows that a gluon interaction many physicists expected would not occur can arise under specific conditions. (1/2)

Quote Tweet: https://x.com/dkundel/status/2022094277401358554?s=20

https://x.com/dkundel/status/2022094277401358554?s=20

Quote Tweet: https://x.com/PaulSolt/status/2022094274788307201?s=20

https://x.com/PaulSolt/status/2022094274788307201?s=20

Quote Tweet: https://x.com/instant_db/status/2022060886840774859?s=20

https://x.com/instant_db/status/2022060886840774859?s=20

Quote Tweet: https://x.com/danshipper/status/2022009455773200569?s=20

https://x.com/danshipper/status/2022009455773200569?s=20

Quote Tweet: https://x.com/warpdotdev/status/2022061861659967920?s=46

https://x.com/warpdotdev/status/2022061861659967920?s=46

At @SierraPlatform, Codex helps the team jump straight into building projects with minimal setup.

Codex enables them to explore ideas faster and stay focused on solving problems.

on Wednesday, February 11th, more than 4 billion messages were sent to and answered by ChatGPT. this represents more than 160 billion words spoken to a machine intelligence in one day.

We’re giving a small group of API customers early access to Codex-Spark to experiment with it in their products, helping us continue optimizing performance beyond Codex.

We’ll expand access to more ChatGPT users and API developers as we add more capacity.

Codex-Spark is currently text-only with a 128k context window.

We’ll introduce more capabilities–including larger models, longer context lengths, and multimodal input as we learn from our first production deployment of low-latency infrastructure and hardware.

These improvements will roll out across all models in Codex over the next few weeks. (2/2)

Codex will continue to get faster.

We’ve optimized infrastructure on the critical path of the agent by improving response streaming, accelerating session initialization, and rewriting key parts of our inference stack. (1/2)

GPT-5.3-Codex-Spark is the first milestone in our partnership with @cerebras.

It provides a faster tier on the same production stack as our other models, complementing GPUs for workloads where low latency is critical.

https://openai.com/index/introducing-gpt-5-3-codex-spark/

Introducing GPT-5.3-Codex-Spark, our ultra-fast model purpose built for real-time coding.

We’re rolling it out as a research preview for ChatGPT Pro users in the Codex app, Codex CLI, and IDE extension.

Rolling out today to ChatGPT Pro users in the Codex app, CLI, and IDE extension.
https://openai.com/index/introducing-gpt-5-3-codex-spark/

Tomorrow at 10am PT legacy models (GPT-5, GPT-4o, GPT-4.1, GPT-4.1 mini, and OpenAI o4-mini) will be deprecated in ChatGPT.

https://openai.com/index/retiring-gpt-4o-and-older-models/

Quote Tweet: https://twitter.com/i/status/2021704637850472502

Codex is rolling out company-wide at NVIDIA to ~30k engineers.

We partnered closely with their team to deliver cloud-managed admin controls and US-only processing with fail-safes.

Engineers at @harvey use Codex to explore multiple approaches in parallel and converge faster on a solution.

Codex frees up their time for deeper system design and complex decision-making.

Quote Tweet: https://twitter.com/i/status/2021286050623373500

Here's a refresher 😉