The Top AI Papers of the Week (May 24 – May 31) – SkillOpt
– AutoScientists
– The Efficiency Frontier
– Language Models Need Sleep
– Adapting the Interface, Not the Model
– Forecasting Scientific Progress with AI
– Compiling Agentic Workflows into Weights Read on for more:
LLMS
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Principaux articles IA de la semaine (24-31 mai)
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Guild: unifies Claude Code, Cursor, and Codex on one machine
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Claude Code, Cursor, and Codex can now work as one team.
— AlphaSignal AI (@AlphaSignalAI) 31 mai 2026
Multi-agent coding setups keep losing context across tools and sessions.
Guild is a single Go binary that fixes this.
It runs a local MCP server backed by embedded SQLite.
Nothing leaves your machine, no cloud, no… pic.twitter.com/4JI1V4InrfClaude Code, Cursor, and Codex can now work as one team. Multi-agent coding setups keep losing context across tools and sessions. Guild is a single Go binary that fixes this. It runs a local MCP server backed by embedded SQLite. Nothing leaves your machine, no cloud, no
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Article written with Claude Opus 4.8 Max, best for writing now
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Btw, this article was written with a help of Claude Opus 4.8 Max. From my pov it is the best for writing at this moment.
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Token-level SSL vs Latent Prediction: Climbing Abstraction Hierarchies
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The key distinction: Token-level SSL asks the model to recover the hidden tree through the leaves. Latent prediction lets the model climb the tree. Once one abstraction level is learned, it becomes the substrate for learning the next.
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Chrome integrates Gemini, transforming into a powerful AI agent!
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🌐 Chrome turns into an AI agent with Gemini integration!#googlechrome #googlegemini #AI #google #artificialintelligence #AIagent @PawlowskiMario @chidambara09 @Ym78200 @CurieuxExplorer @efipm @bigfundu @sayedflah @Ronald_vanLoon @cyngn @belindabeibi @odisseiaalfa… pic.twitter.com/g1IM0xbPpV
— Amitav Bhattacharjee (@bamitav) 31 mai 2026Chrome turns into an AI agent with Gemini integration! #googlechrome #googlegemini #AI #google #artificialintelligence #AIagent @PawlowskiMario @chidambara09 @Ym78200 @CurieuxExplorer @efipm @bigfundu @sayedflah @Ronald_vanLoon @cyngn @belindabeibi @odisseiaalfa
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GPT-5.5 creative use cases underperformance examples
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what creativity usecases does gpt 5.5 not perform well for you at? if you have some prompts/ sessions I’d love to know more
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AI memory shifts from retrieval to compilation with LLM Wiki
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RAG is already becoming the “old way” The future of AI memory is not retrieval.
It’s compilation. Here’s the shift in one sentence: From searching information To structuring knowledge The new model? LLM Wiki Instead of: Chunking documents Running similarity -
Apple AI to run distilled Google Gemini on iPhone
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Interesting updates on Apple AI: As Apple's WWDC lands next month, and the long-delayed Siri and on-device AI upgrades are expected to be the centerpiece: a smaller, distilled version of Google's Gemini running locally on iPhone silicon, pitched on privacy and lower token costs.
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GEPA visualizer: LLM self-optimizing prompts beyond black-box scoring
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A new GEPA visualizer shows an LLM optimizing its own prompts in real time.
— AlphaSignal AI (@AlphaSignalAI) 31 mai 2026
Most prompt optimizers treat the LLM like a black box.
They reduce every run to a single score and call it learning.
GEPA takes a different path.
It reads the full execution trace, error logs, and… pic.twitter.com/ixJEsIMutdA new GEPA visualizer shows an LLM optimizing its own prompts in real time. Most prompt optimizers treat the LLM like a black box. They reduce every run to a single score and call it learning. GEPA takes a different path. It reads the full execution trace, error logs, and
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Autoreview keeps GPT honest and helps achieve real goals
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gotta use autoreview, that keeps gpt honest and usually helps achieve the real goal.