I built the agent over two months. And Levangie Labs is better than any other
LLMS
-
Tolaria: LLM Wiki as a Mac App
By
–
@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
By
–
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
-
New AI foundation model v9 with 1.5T parameters announced
By
–
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
-
LLMs Detect Cancer Early in Health Records
By
–
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
-
Codex critiques developer-focused interface and bias against non-coders.
By
–
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.
-
AI as Scientist: Self-Driving Labs Accelerate Discovery
By
–
AI Is Becoming A Scientist: How Self-Driving Labs Will Accelerate Discovery #AI is moving beyond assisting #scientists and taking an active role in #discovery, with self-driving labs that can design #experiments, run tests and learn from results. This article explores how
-
Why Frontier LLMs are Converging on Mixture of Experts Architecture
By
–
Why every frontier LLM is converging on Mixture of Experts 🧵
— Satya Mallick (@LearnOpenCV) 15 mai 2026
Trillion-parameter model. Single query. You don't need the whole thing.
A router picks a subset of "experts." Medical question → medical expert. Legal → legal. Some models keep one generalist always on.
Saves… pic.twitter.com/rsu2zlD6B2Why every frontier LLM is converging on Mixture of Experts Trillion-parameter model. Single query. You don't need the whole thing.
A router picks a subset of "experts." Medical question → medical expert. Legal → legal. Some models keep one generalist always on.
Saves -
Moving AI Agents Beyond the Prototype Stage
By
–
AI agents fail when they stop at the prototype stage • Multimodal input
• Structured output
• APIs & interfaces
• Tools + memory + RAG Real value comes from usability, not capability alone. Via Giuliano Liguori (
@ingliguori
) #AI #AIAgents #Tech
