This isnt about more power but being functional as group
SYSTEMS
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Self-Growing Robot Rebuilds Itself Using Salvaged Machine Parts
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Self-Growing #Robot Rebuilds Itself Using Parts from Other Machines
— Ronald van Loon (@Ronald_vanLoon) 15 avril 2026
by @spaceandtech_#Robotics #Engineering #ArtificialIntelligence #Innovation #Technology pic.twitter.com/mG6fKAnI4SSelf-Growing #Robot Rebuilds Itself Using Parts from Other Machines
by @spaceandtech_ #Robotics #Engineering #ArtificialIntelligence #Innovation #Technology -
General AI Systems Lack Manufacturing Process Understanding
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General AI systems are advancing rapidly but lack understanding of manufacturing constraints and process tradeoffs.
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Training AI Models on Production Signals and Operational Patterns
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These models are trained on production signals, process behavior, operational patterns, and engineering context.
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Industrial Foundation Models Transform Manufacturing Production Environments
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Unlike general AI trained on public text, industrial foundation models encode how manufacturing actually works. Their value comes from relevance to production environments, not just generating text or predictions.
— Lucian Fogoros (@fogoros) 14 avril 2026
Partner content with Cybus. #cybus_iiot pic.twitter.com/VYO0qyXuQ9Unlike general AI trained on public text, industrial foundation models encode how manufacturing actually works. Their value comes from relevance to production environments, not just generating text or predictions.
Partner content with Cybus. #cybus_iiot -
Neurosymbolic Implementation for Deterministic AI Behavior
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This is great work but I hope we have neurosymbolic implementation under the hood to ensure deterministic behaviour where needed. @pierrepinna https://t.co/SIUjAtKeUP
— AI (@DeepLearn007) 14 avril 2026This is great work but I hope we have neurosymbolic implementation under the hood to ensure deterministic behaviour where needed. @pierrepinna
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Autonomous Energy Systems Decision Speed Requirements
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What's the fastest decision time your energy systems need to make autonomously? @IIoT_World @CRudinschi @agentic_factory @asokan_telecom @KADGLOBAL @Paul4innovating
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Multi-Agent System Optimizes CUDA Kernels for GPU Efficiency
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The multi-agent system delivered optimizations that typically take experienced kernel engineers months or years. CUDA kernels are the core software supporting model training and inference. Faster kernels mean better GPU utilization and cheaper token costs.
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Sub-second response times critical for safety-critical energy systems
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For safety-critical energy systems where consequences of bad decisions are physical, not computational, sub-second response time isn't optional.
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Edge Compute Software Infrastructure for Distributed AI Model Deployment
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Edge compute requires not just hardware, but software infrastructure that can support model deployment, monitoring, and updates across distributed sites.