Our API is now available through LangChain! Our team is shipping new things everyday! What are you going to build? 🐍 Python docs: python.langchain.com/docs/integrati… ☕️️ Javascript docs: js.langchain.com/docs/integrati… Happy coding! console.x.ai

Remember the llm.c repro of the GPT-2 (124M) training run? It took 45 min on 8xH100. Since then, Keller Jordan (and by now many others) have iterated on that extensively in the new modded-nanogpt repo that achieves the same result, now in only 5 min! Love this repo 👏 600 LOC

Do you remember when you joined X? I do! #MyXAnniversary

It is happening!

Since ChatGPT dropped in 2022, AI progress has been dramatic. But it's also been predictable—new models, bigger chip clusters, more chatbots. Not in 2025. Here are the three big changes to watch for over the next 12 months 🧵 1/8

New Anthropic research: How are people using AI systems in the real world? We present a new system, Clio, that automatically identifies trends in Claude usage across the world.

🚨Ilya Sutskever finally confirmed > scaling LLMs at the pre-training stage plateaued > the compute is scaling but data isn’t and new or synthetic data isn’t moving the needle What’s next > same as human brain, stopped growing in size but humanity kept advancing, the agents and

those who think RL use less compute don’t know RL at all 😅 SFT: human generates data and machine learns RL: machine generates data and machine learns

I don't have too too much to add on top of this earlier post on V3 and I think it applies to R1 too (which is the more recent, thinking equivalent). I will say that Deep Learning has a legendary ravenous appetite for compute, like no other algorithm that has ever been developed

TL;DR: we are excited to release a powerful new open-weight language model with reasoning in the coming months, and we want to talk to devs about how to make it maximally useful: openai.com/open-model-fee… we are excited to make this a very, very good model! __ we are planning to

OpenAI o3 and o4-mini openai.com/live/

OpenAI uses FastAPI to serve ChatGPT and you’re complaining about Python and how FastAPI cannot support your 10 user CRUD app

Introducing AlphaEvolve: a Gemini-powered coding agent for algorithm discovery. It’s able to: 🔘 Design faster matrix multiplication algorithms 🔘 Find new solutions to open math problems 🔘 Make data centers, chip design and AI training more efficient across Google. 🧵

Explore how Project Euphonia’s open-source tools empower developers to build personalized audio tools and fine-tune open-weight models for diverse speech patterns, advancing speech tech for everyone. #GAAD → g.co/euphonia

Codex is now available in the ChatGPT iOS app! Start new tasks, view diffs, ask for changes, and even push PRs—all on the go. And you can keep tabs on Codex with live activities on your lock screen, or pick things up again when you're back at your computer. 🏃🤳

Early tests of Gemini 2.5 Pro Deep Think are looking 🔥 By applying new research techniques in reasoning, Deep Think is outperforming leading general foundation models on complex reasoning benchmarks, including the challenging USA Math Olympiad benchmark & MMMU.

A rare non-technical post from me. Shoutout to Chewy for the thoughtful painting of one of my dogs for National Pet Month. Pets are family, and Chewy truly made it personal.

A Survey of Context Engineering 160+ pages covering the most important research around context engineering for LLMs. This is a must-read! Here are my notes:

🚀 MassGen 0.0.3 is here! Major architecture upgrade for multi-agent scaling: 📷 GPT-OSS Support #GPToss 📷Anthropic , Cerebras, Google AI, Grok, OpenAI

Traditional RAG vs. Agentic RAG, clearly explained (with visuals):