the time is here – we're launching our 10th @raais summit speakers! first up, @jeffrey_hawke
, co-founder/cto at world simulator pioneers @odysseyml jeff's work intersects generative modelling, embodied intelligence, and large-scale learning he was prev vp tech @wayve_ai
AGENTS
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RAAIS Summit Announces Jeffrey Hawke as 10th Speaker
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Cognee Knowledge Graph Enhances AI Reasoning with OpenClaw Memory Layer
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I wrote about pairing Cognee with OpenClaw's memory layer. Native memory stores facts but can't reason over relationships. Cognee adds a knowledge graph that makes those connections explicit. Same Markdown files, but with structure underneath. Better retrieval = cleaner context
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OpenAI Launches GPT-5.4 with Native Computer Usage Capabilities
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OpenAI launched GPT-5.4 on March 5 — first model with native computer-use built in. One system that can reason, code, and operate your desktop. That's a meaningful consolidation. openai.com/index/introducing-gpt-5-4/ #AI [Translated from EN to English]
→ View original post on X — @svenphilipsen, 2026-03-10 08:00 UTC
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Reality of Agentic AI: Beyond Labels and Simple Workflows
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𝗧𝗵𝗲 𝗿𝗲𝗮𝗹𝗶𝘁𝘆 𝗼𝗳 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝗿𝗶𝗴𝗵𝘁 𝗻𝗼𝘄. → Many people are talking about AI agents. Only a few are actually building systems that generate real value. → Most “AI agents” today are still assistants or simple workflows with a new label. That gap is
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Microsoft Chooses Anthropic for Copilot Cowork in M365
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Microsoft just announced Copilot Cowork — built with Anthropic's Claude and shipping in M365. OpenAI signed the Pentagon contract. Anthropic refused it. Now Microsoft is betting on Anthropic for enterprise agents. Corporate AI choices are geopolitical now. #AIGovernance [Translated from EN to English]
→ View original post on X — @svenphilipsen, 2026-03-10 06:00 UTC
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LangChain San Jose Event Promises Major Enterprise AI Agents Week
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Can’t wait to see the @LangChain team in San Jose—it’s going to be a massive week for enterprise AI agents!
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Humanoid Robots Revolutionize Shopping Experience with AI
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Want to experience your shopping with Robots? 🛒 🤖 🛒pic.twitter.com/m2mJ18jJbT#humanoidtech #humanoid #robot #Robotics #AI #TechRevolution #TechInnovation #ArtificialInteligence #PhysicalAI@SpirosMargaris @PawlowskiMario @mvollmer1 @gvalan @ipfconline1 @LaurentAlaus…
— Amitav Bhattacharjee (@bamitav) 10 mars 2026Want to experience your shopping with Robots? #humanoidtech #humanoid #robot #Robotics #AI #TechRevolution #TechInnovation #ArtificialInteligence #PhysicalAI @SpirosMargaris @PawlowskiMario @mvollmer1 @gvalan @ipfconline1 @LaurentAlaus
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Anthropic Introduces Automated AI Agent Code Review for Claude Code
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🚨 Anthropic just dropped Code Review for Claude Code, and it just flipped the script on code reviews.
— Charly Wargnier (@DataChaz) 9 mars 2026
AI agents hunting bugs in parallel?
Yes please!
When a PR opens, Claude doesn't just scan the code.
It sends out multiple agents to find, cross-verify, and rank severities… pic.twitter.com/Yk2x4pCGS8Anthropic just dropped Code Review for Claude Code, and it just flipped the script on code reviews. AI agents hunting bugs in parallel? Yes please! When a PR opens, Claude doesn't just scan the code. It sends out multiple agents to find, cross-verify, and rank severities
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Test Time Compute and Subagents: Optimizing AI Results
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Roughly, the more tokens you throw at a coding problem, the better the result is. We call this test time compute. One way to make the result even better is to use separate context windows. This is what makes subagents work, and also why one agent can cause bugs and another
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SIPDO: AI that auto-discovers and fixes its own instruction errors
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What if your AI could automatically hunt for its own mistakes and fix its instructions in a continuous loop? Researchers from UIUC, HKUST, USF, and http://
Starc.Institute introduce SIPDO to do exactly that. Instead of relying on a fixed set of data, SIPDO uses a feedback loop