China leapfrogs US in global market for ‘open’ AI models https://t.co/Vdh6BRSjho @Melissahei @ft

China leapfrogs US in global market for ‘open’ AI models https://t.co/Vdh6BRSjho @Melissahei @ft

AI ‘dreams’ up new realities. How does this impact the way we understand our own dreaming? https://t.co/z7iX2pvj8R @ConversationEDU

AI ‘dreams’ up new realities. How does this impact the way we understand our own dreaming? https://t.co/z7iX2pvj8R @ConversationEDU

Die erstaunliche Reise der Challenger-Bank Revolut https://t.co/5wxuykWnOm Die wirklich grossen Dinger kommen meist aus den USA, vielleicht noch aus China. Mit @Revolut kommt ein wirklich grosses Ding aus Europa. https://t.co/RY5npoyFXg

Die erstaunliche Reise der Challenger-Bank Revolut https://t.co/5wxuykWnOm Die wirklich grossen Dinger kommen meist aus den USA, vielleicht noch aus China. Mit @Revolut kommt ein wirklich grosses Ding aus Europa. https://t.co/RY5npoyFXg

MIT scientists debut a generative AI model that could create molecules addressing hard-to-treat diseases https://t.co/yK7HTB1iQZ @MIT

🧠Model-Based RL shows promises but has seen limited success in real-world robotics. 🌎Introducing Robotic World Model, a black-box end-to-end neural dynamics model that bridges this gap, where policies are trained purely in imagination. @NeurIPSConf 🎯https://t.co/6YYsiVWZic https://t.co/9BMNhhJvTw

The rise of machines by Yang-Hui He https://t.co/feu6KRbOZM

The rise of machines by Yang-Hui He https://t.co/feu6KRbOZM

something wild coming out of @heliumrobotics an ai powered pet lamp. it moves, it vibes, it just exists in your space like it’s alive https://t.co/UYlIsNHRKJ

RAG isn't dead, it evolved I compared the new semantic search (RAG) against default agentic search (also RAG 😄) for coding agents. Semantic search won Rui Huang ( @mixedbreadai ) will give an engineering talk on why, intuition, and setup Sign up 👇 https://t.co/I6bgJP9YoN

@llm_wizard @Nexuist RAG won so hard. we're doing tools for RAG over your other tools now https://t.co/5GyJ3GCHGV

@llm_wizard @Nexuist RAG won so hard. we're doing tools for RAG over your other tools now https://t.co/5GyJ3GCHGV

Next week @sh_reya is hosting a unique session on processing unstructured data at scale with LLMs. This session is the culmination of years of research. She'll cover how to combine database thinking with LLMs, plus a few new tricks. Link to signup: https://t.co/ODNUNGn2Wt https://t.co/GenvDI1Epc

If you aren't familiar with her work see this page. I've enjoyed every single one of these papers. Notes and recording sent to everyone who signs up: https://t.co/ODNUNGn2Wt https://t.co/tleKM9ATll

New meme template unlocked 🙌 https://t.co/mjnVxdFsx7

Opus 4.5 is our best model yet for design & vision. Here are some of my favorite UIs we made with Claude Code's frontend-design plugin. https://t.co/QKhVcwig0j

I used the design plugin + Opus 4.5 to upgrade my business page https://t.co/b6C5EA4QtU Absolutely blown away. Before vs. After https://t.co/UAcwwBb6eW

+1 more

Those who defend Leetcode for hiring are brainwashed servants of the matrix https://t.co/ujMdEbi45w

Opus 4.5 + Claude Code's front-end design plugin is a great combo for designing apps. Just one-shotted a few designs, and it feels like a huge improvement. Use plan mode to get much better results. https://t.co/QSi8SDYZ78

Physics simulator in one shot. Designs are pretty versatile. I am sure that with just a few more iterations, it's possible to significantly improve upon the designs. Prompts were pretty basic, so I didn't expect much. https://t.co/aY3Lxggflc

To try this yourself add our marketplace in Claude Code: /plugin marketplace add anthropics/claude-code and then install the plugin: /plugin install frontend-design@claude-code-plugins https://t.co/hYKyAAFUuH

AI agents forget everything between sessions. However, the problem isn't storage. It's how knowledge gets encoded. Current agents either retrieve surface-level information or build task-specific memories that don't transfer elsewhere. Real expertise works differently. Deep understanding enables flexible application across new situations. This new research introduces a framework where agents build memory through deep research, not shallow retrieval. The key idea: before encoding anything into memory, agents conduct thorough investigation. They explore relationships, synthesize findings, and create rich knowledge structures. This depth enables generalization. The framework operates across stages. Investigate: agents research topics comprehensively before storage. Structure: findings get organized into representations that capture nuance and context. Apply: these memories transfer across different tasks and domains. Evaluated on HotpotQA, NarrativeQA, and other knowledge-intensive benchmarks. Agents with research-driven memory outperform those using standard retrieval approaches. What makes this interesting: memory becomes an asset that compounds. Knowledge built for one task supports future tasks and agents develop genuine expertise rather than disposable context.

Paper: https://t.co/EZI800fl2P Code: https://t.co/l5iQ7zNUQS

YT version if you like: https://t.co/bWAe7II5TK

Thrilled to release new paper: “Scaling Latent Reasoning via Looped Language Models.” TLDR: We scale up loop language models to 2.6 billion parameters, and pretrained on > 7 trillion tokens. The resulting model is on par with SOTA language models of 2 to 3x size. https://t.co/6iauhVZ83g

@Teknium https://t.co/65afHL3rpb + 16x https://t.co/AMjSoAjrjf

@edward_milsom @jeremyphoward wrote up a piece about this recently as well https://t.co/mMRbkumUGe

https://t.co/NYiRyuBysI

testing out @cursor_ai designing my dropdown menu with opus 4.5 https://t.co/f4A2UnV0Vx

@cursor_ai its a good compontent https://t.co/3nzs2hrrYV