// Beyond Individual Intelligence // One of the more useful multi-agent surveys I've read this year. 200+ papers mapped along three axes: collaboration mechanisms, failure attribution, and self-evolution. The self-evolution chapter is the cleanest field map of where memory,
LLMS
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Comparison of Agentic Search vs. Vector Search
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Great paper discussing agentic search vs. vector search.
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Researchers Introduce Laser: A More Efficient Visual Reasoning AI Model
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What if visual reasoning could be 97% more efficient while outperforming top models? Researchers from MBZUAI, Fudan, Renmin, and Harvard introduce Laser. Instead of forcing step-by-step text, it uses “forest-before-trees” reasoning—maintaining a big-picture understanding
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AI Agent Development Over Two Months
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I built the agent over two months. And Levangie Labs is better than any other
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Tolaria: LLM Wiki as a Mac App
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@Karpathy
's LLM wiki concept just became a real Mac app. It is called Tolaria, a free desktop app for Mac and Linux. The goal is simple: give humans and AI agents a shared, native environment to build knowledge. It writes like a modern block editor, but saves everything as -
Claude Cowork’s Federated MCP Performance Benchmark
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Claude Cowork just got 10x more powerful!
— Sumanth (@Sumanth_077) 15 mai 2026
Glean benchmarked centralized vs federated MCP in Claude Cowork. Same harness, same model, same queries, different context layer.
The federated approach: Each data source (Gmail, Slack, Drive, Salesforce) has its own MCP server. Claude… pic.twitter.com/0lSWyHsKriClaude Cowork just got 10x more powerful! Glean benchmarked centralized vs federated MCP in Claude Cowork. Same harness, same model, same queries, different context layer. The federated approach: Each data source (Gmail, Slack, Drive, Salesforce) has its own MCP server. Claude
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New AI foundation model v9 with 1.5T parameters announced
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The version numbers are a little confusing and deserve some explanation. Internally, we are working on version 9 of our new foundation model, which is 1.5T params. This is substantially better in every way than v8: data curation, training recipe, size, etc. It is also optimized
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LLMs Detect Cancer Early in Health Records
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We could pick up risk of cancer and detect it much earlier if we applied LLMs to electronic health records, as shown in this @AllofUsResearch study
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Codex critiques developer-focused interface and bias against non-coders.
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Codex is very good, but it is still a very "developer coded" interface for an everything app. And it continues the somewhat annoying AI perspective that non-coders are just not as competent and need stuff hidden from them, as opposed to requiring a different form of complexity.
