Message from @rheimann … “I put together a short benchmark based on Sutskever’s List that tries to test actual understanding. Thought you might find it interesting”:
AI
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AI spending triggers market inflection for DevOps and observability sector
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We’ve seen waves in which different parts of tech light up as they are favored with a portion of the enormous spending on artificial intelligence. This morning’s report feels like something of an inflection for “DevOps” and “observability.” Datadog soars as AI-driven outlook the
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Chromex: Codex intégré directement dans Chrome
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Chromex is live I built a Chrome extension that brings Codex directly into the browser. Instead of copying page text into another tab,
Chromex lets you ask, summarize, draft, inspect, and act from the page you’re already viewing. What Chromex can do: → chat with the -
Common LLM RAG Retrieval Accuracy Drops Explained
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A tricky LLM interview question: Your RAG system scores 90% retrieval accuracy on 5k company docs. But scaling to 500k docs drops the accuracy to just 50%, with the same embedding model and retriever. Why did this happen? The simplest answer is that more documents mean more
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Robot demo raises generalization questions
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This is a cool demo but a key question to ask is "can the robot do any of this with unfamiliar objects or in different conditions?". It looks to me like it is closely mirroring specific human actions. The range and complexity is certainly impressive, but that is not the same as… https://t.co/QSFcN9phLh
— Will Knight (@willknight) 7 mai 2026This is a cool demo but a key question to ask is "can the robot do any of this with unfamiliar objects or in different conditions?". It looks to me like it is closely mirroring specific human actions. The range and complexity is certainly impressive, but that is not the same as
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AI tools for autonomous workflow integration
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🚨 Anyone building autonomous workflows knows the real headache is integration.
— Charly Wargnier (@DataChaz) 7 mai 2026
ChatGPT and Claude Code are brilliant reasoning engines, but connecting them to external apps can still be rough!
I recently test-drove @CreaoAI to fix this exact bottleneck.
To test it, I built an… pic.twitter.com/0uCqu3LV8cAnyone building autonomous workflows knows the real headache is integration. ChatGPT and Claude Code are brilliant reasoning engines, but connecting them to external apps can still be rough! I recently test-drove @CreaoAI to fix this exact bottleneck. To test it, I built an
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YAAP: Harness Engineering and Why Agents Fail in Production
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New #YAAP episode out now @yuvalinthedeep sits down with @mikegchambers from @awsdevelopers to unpack harness engineering and why it's the reason most agents never make it to production. Listen/Watch it now: https://
ai21.com/yaap/everythin
g-but-the-model-harness-engineering/?utm_source=org-twitter
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AI memory future: from retrieval to LLM Wiki compilation
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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 -
AI geniuses by 2028 require hired forward-deployed engineers
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Labs; “we will have a nation of geniuses in a data center by 2028, capable of beating humans at every task, but you will need to hire our newly trained forward-deployed engineers for a six month engagement to deploy them to a single project”
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Underinvestment in enterprise pivot: Labs build consultancies, lack of trust
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Seems like a massively underinvested area in the “pivot to enterprise.” The fact that the Labs are building their own deployment consultancies (which will take a long time) suggests a failure of imagination or a lack of trust that models will be up to that task in coming years.