Wow are really great! Could definitely see these tools almost immediately being used for B Roll shots and adding extras to scenes. With some good post production, I think this will save studios millions. Or just imagine directories that want to check out how different shots look.

BREAKING: Stanford just surveyed 1,500 workers and AI experts about which jobs AI will actually replace and automate. Turns out, we've been building AI for all the WRONG jobs. Here's what they discovered: (hint: the "AI takeover" is happening backwards)

i'm going to say something that most of you won't understand but now, with the new crop of LLMs, coding is mostly solved, and its all systems engineering. and here is something i learned from being a distributed systems wagie for a long time: make your systems parametric

It’s true

Day 3 of replacing my Google Home with Claude Code Giving Claude a voice with an 11 Labs MCP server! Code walk through 👇

Our paper on autonomous scientific research is accepted to Findings of #EMNLP2025! 🎉 We introduce Agent Laboratory, a framework that accelerates scientific discovery by teaming human researchers with LLM agents.

I’ve been beta testing Google AI Co-Scientist for some time. It generates novel ideas, hypotheses & scientific proposals. It’s unbelievably good; together with the other AI models I discuss here, it fundamentally changes how science is done & will make the world a better place!❤️

Nice paper that is basically an empirical survey of all the recent RL algorithm improvements.

KV cache compression techniques ▪️KV caching (basic) – stores previously computed Keys and Values in memory and calculates attention only for new tokens. ▪️ Quantization – represents KV cache with fewer bits. ▪️ Low-rank decomposition – compresses the KV cache into smaller

🚨 Carnegie Mellon just dropped one of the most important AI agent papers of the year. It’s called “Training Proactive and Personalized LLM Agents.” Here’s the wild part... they didn’t train agents to just complete tasks. They trained them to talk better. Most AI agents are

Wild. By far the most complete Claude Skills repo yet 🤯 @Composio’s Awesome-Claude-Skills packs 100`s of ready-to-use workflows: ↳ PDF tools, changelog generation ↳ Playwright automation ↳ AWS/CDK tools, MCP builders ... and much more! Free and open-source. Repo in 🧵↓

This simple Claude Code hack has reduced token usage by ~90%. It adopts the "Code Execution with MCP" concept published by Anthropic. Remove preloaded MCP tools from context and use Python to execute tools via bash instead. BTW, this can be optimized much further. Insane!

(1/n) 🚨 BERTs that chat: turn any BERT into a chatbot with diffusion hi Andrej Karpathy, we just trained a few BERTs to chat with diffusion — we are releasing all the model checkpoints, training curves, and recipes! Hopefully this spares you the side quest into training nanochat with

First tools, then memory... ...and now there's another key layer for Agents. Karpathy talked about it in his recent podcast. Tools help Agents connect to the external world, and memory helps them remember, but they still can't learn from experience. He said that one key gap

Google released another whitepaper 🔥. it's a masterclass on building intelligent optimized sessions and long-term memories for agents that actually work. It covers: > context engineering best practices > comparing memory and RAG > memory-as-a-tool pattern > agent-to-agent (A2A)

Memory engine for AI Agents with a single line of code. Just call memori.enable() to give any LLM or agent persistent memory. Uses existing SQL database - no vector databases required. 100% open-source.

Anthropic is so, so over. Just completely defeated. Really sad, so many great people there. My advice: go to DeepMind before it's too late.

Massive update for AI Engineers! Training diffusion models just got a lot easier. dLLM is an open-source library that does for diffusion models what Hugging Face did for transformers. Here's why this matters: Traditional autoregressive models generate text left-to-right, one

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