How can robots master new, complex tasks and generalize effortlessly without endless, costly data collection? Toyota Research Institute and Tsinghua University just published a massive study on this! They explored co-training strategies for Large Behavior Models, teaching
LLMS
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CoWork: Multi-Model AI Assistant for Optimal Task Performance
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What if CoWork could – use Claude for coding – GPT 5.4 for excel – cheap open source for simple tasks – Kling for video generation Does all the work on your laptop using the best models all the time Coming Very Soon
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Anthropic Introduces Claude Code Integration for Telegram and Discord
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Anthropic released Claude Code channels in research preview, a new feature that would allow users to send messages to Claude Code directly from Telegram and Discord. https://t.co/33pWCIDsDr pic.twitter.com/8GG6t8vWhP
— 🚨 AI News | TestingCatalog (@testingcatalog) 19 mars 2026Anthropic released Claude Code channels in research preview, a new feature that would allow users to send messages to Claude Code directly from Telegram and Discord.
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OpenAI Reportedly Developing Unified ‘Super App’ for AI Models
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BREAKING : OpenAI is planing to launch a Super App that would unify ChatGPT, Codex and Atlas into one, as reported by WSJ. OneAI
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APL Right-to-Left Precedence Challenges for Language Models
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One thing I wonder about APL is whether the right-to-left precedence would cause problems for an LLM. In practice folks tend to write APL using a number of steps of creating small blocks then building them up. Perhaps LLMs need some tooling to help them…
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Discussion on AI model benchmarks and performance metrics
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ah bon où ca ? ca c'est les deux autres graphiques, il y a un benchmark qui ne mesure pas de capacité de code, et un graphique de comparaison speed / price.
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Criticism of cherry-picked AI benchmarks and internal metrics
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Wait a minute… Franchement, ça devient indécent les communications autour des graphiques et des benchmarks. Tout le monde fait du cherry-pick. Ça devient ridicule, à un moment. Maintenant on invente même ces propres benchmarks "interne" pour avoir un joli grpahique où on
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MiniMax-M2.7 Self-Evolving Model Launches for Software Engineering
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MiniMax-M2.7 is live on Poe! A next‑gen self‑evolving model built for autonomous software engineering and agent workflows. M2.7 can iteratively improve its own agent scaffolds, optimize task performance over repeated runs, and deliver major gains on real-world coding benchmarks
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Jensen Huang and AI Leaders Discuss Open Models
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The future of AI isn't being built in a vacuum. 🤝 NVIDIA Founder and CEO Jensen Huang sat down with the builders from AMP PBC, @bfl_ml, @Cursor_ai, @LangChain, @MistralAI, @EvidenceOpen, @Perplexity_ai, @Reflection_AI, @Thinkymachines & @Allen_ai to discuss the rapid rise of open frontier models. 🔗 Learn more: blogs.nvidia.com/blog/gtc-2026-news/#open-models-panel [Translated from EN to English]
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Introducing GLM 5 Turbo for Research Paper Analysis
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Introducing GLM 5 Turbo for understanding research papers 🚀
— alphaXiv (@askalphaxiv) 19 mars 2026
Highlight any section of a paper to ask questions and “@” other papers for quick context, comparisons, and benchmark references pic.twitter.com/WKPGQP3ExMIntroducing GLM 5 Turbo for understanding research papers Highlight any section of a paper to ask questions and “@” other papers for quick context, comparisons, and benchmark references