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DOGE Used a Meta AI Model to Review Emails From Federal Workers | WIRED https://archive.md/Joty1
Meta shuffles AI, AGI teams to compete with OpenAI, ByteDance, Google https://www.axios.com/2025/05/27/meta-ai-restructure-2025-agi-llama
I built an AI Agent that > takes all my competitors Meta Ads > transcribes them > repurposes them > add them to a slack channel > ready to generate in https://t.co/ArtDvdEBf2 comment “”ai agent”” to get access https://x.com/rom1trs/status/1925518833902633009
Finally completed and merged the SWE_RL environment that was described by Meta’s SWE RL paper into Atropos – A really difficult environment that can teach a model to be a much better coding agent! Check out the PR: https://x.com/Teknium1/status/1927089897833140647
DeepSeek’s R1 leaps over xAI, Meta and Anthropic to be tied as the world’s #2 AI Lab and the undisputed open-weights leader DeepSeek R1 0528 has jumped from 60 to 68 in the Artificial Analysis Intelligence Index, our index of 7 leading evaluations that we run independently https://x.com/i/web/status/1928071179115581671
So so so cool. Llama 1B batch one inference in one single CUDA kernel, deleting synchronization boundaries imposed by breaking the computation into a series of kernels called in sequence. The *optimal* orchestration of compute and memory is only achievable in this way.”” / X https://x.com/karpathy/status/1927506788527591853
Ollama can now think! 🤔🤔🤔 For thinking models, and especially useful for very thoughtful models like DeepSeek-R1-0528, Ollama can separate the thoughts and the response. Thinking can also be disabled! This is useful for getting a direct response. This works across https://x.com/ollama/status/1928543644090249565
Meta understood that copying DeepSeek piecemeal is not working, and decided to copy the org structure, creating an internal AGI division. a cruel rhyme from Russian school program comes to mind “”And you, my friends, no matter your positions, Will never be musicians!”” https://x.com/i/web/status/1927944123358581182
Just FYI all the reports from our RL experiments have not been on Qwen, they’ve been on Llama (DeepHermes 8B) – so hopefully that gives some additional assurance on the impact RL can have and that its not random god-mode qwen math improvements from randomness”” / X https://x.com/i/web/status/1928184393035559191
RAG is dead, long live agentic retrieval! At LlamaIndex we’ve been saying for a long time that naive RAG is not enough for a modern application. Following from that conviction, we’ve built agentic strategies directly into LlamaCloud that you can adopt with just a few lines of https://x.com/llama_index/status/1928142249935917385
