In case anyone wants to improve/change/use it:
MACHINE LEARNING
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Agentic layer enables autonomous fact-based optimization
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The agentic layer closes the loop entirely, pushing fact-based optimizations without waiting for human intervention.
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Four Layers of Industrial AI: From Prediction to Automation
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Industrial AI operates across four layers: predictive forecasts what's coming, prescriptive recommends actions, generative exposes insights in natural language, agentic pushes optimizations directly to control systems. #industrialai #manufacturing
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LogicFolding: 3D Chip Architecture for AI Inference Optimization
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One concept that makes this practical is LogicFolding. Traditional chips spread logic across a flat surface. LogicFolding brings related logic closer together by moving toward more 3D structures. Less distance means less delay. And in AI workloads, small delays compound fast.
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Tau Scaling Law: Beyond Chip Size in AI Systems
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This is the idea behind Tau Scaling Law, also known among peers as Her’s Law. Instead of asking only, “How small can the chip get?” We now have to ask: → Where is time being lost?
→ Where is data waiting?
→ Where are signals traveling too far?
→ Where is the system -
Proactive Agents: LLM Efficiency in Wake Triggers
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Do proactive agents really need an LLM to decide when to wake? The default proactive agent calls an LLM on every event just to decide whether to wake up. That is a lot of expensive inference spent on a yes or no. New research from Microsoft and Purdue asks whether the trigger
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Teaching Robots Complex Tasks Without Extensive Training
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Teaching #Robots to do complex tasks WITHOUT spending hours training them
— Ronald van Loon (@Ronald_vanLoon) 29 mai 2026
via @IlirAliu_
#Robotics #AI #ArtificialIntelligence #MachineLearning #MI #Tech pic.twitter.com/QsA3VhFyOITeaching #Robots to do complex tasks WITHOUT spending hours training them
via @IlirAliu_ #Robotics #AI #ArtificialIntelligence #MachineLearning #MI #Tech -
20-minute intro to Managed Deep Agents by Runkle and Moreira16
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.@sydneyrunkle + @VictorMoreira16 with a 20 minute intro to Managed Deep Agents.
— LangChain (@LangChain) 29 mai 2026
Watch the full Interrupt keynote: https://t.co/jDvoDG6wek pic.twitter.com/hcBAIcUHpL.
@sydneyrunkle + @VictorMoreira16 with a 20 minute intro to Managed Deep Agents. Watch the full Interrupt keynote: https://
youtu.be/LdQpoK2TzSo -
Shift from Opus to GPT 5.5 as best model for Clawdbot
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I was full on promoting Opus as best model for “Clawdbot”. Luckily that changed and GPT 5.5 is now the best model based on our internal benchmarks.
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Reconstructing Software Engineering for AI-Driven Coding
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Reconstructing software engineering around AI is going to take work (even as the ability of AI to code increases at a rapid rate). Organizations are ideally spending tokens for two things:
1) building stuff
2) experiments to figure out best practices (which involves failure)