AI-driven pattern matching tests demand adjustments against production schedules, even within frozen planning periods that traditionally couldn't be modified.
AUTOMATION
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Unified MES Platform Cuts Inventory 15% Improves Capacity
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15% inventory reduction and 12% better capacity utilization from unified MES platform. Eyelit Technologies combines demand planning, production scheduling, and shop-floor execution where competitors separate them. #coreflux_ai #adlib_iiot #tronics_ai #skkynet_ai #HM26 pic.twitter.com/8ZM4jJ1KjE
— Lucian Fogoros (@fogoros) 20 avril 202615% inventory reduction and 12% better capacity utilization from unified MES platform. Eyelit Technologies combines demand planning, production scheduling, and shop-floor execution where competitors separate them. #coreflux_ai #adlib_iiot #tronics_ai #skkynet_ai #HM26
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The Hidden Cost of Wasting 125,000 Hours
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I just wasted 125,000 hours of people’s time.
At least… that’s what I thought at first. A while ago, I gave a 1-hour workshop to ~100 people.
And I remember thinking: “If this is bad… that’s 100 human hours gone.” That idea stuck with me. So today, out of curiosity, I -
AI agent monitors news aggregation for latest updates
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I built an AI agent that monitors it for me: https://
alignednews.com/ai All the AI news in X. Soon I will have a much better news monitor -
Intuitive Task Assignment Interface Improves Over CLI Commands
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Makes task assignment way more intuitive than CLI commands
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AI Now Deriving Professional Roles in Companies
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Now AI will be deriving your Roles in companies 🙂
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Models as Components: The Infrastructure Behind AI Agents
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My biggest takeaway: Models are becoming components, not products. What matters now is the system around them: → runtimes
→ memory
→ tool access
→ orchestration
→ secure execution environments That is what turns a model into an agent, and an agent into something the -
Enterprise AI strategies behind: shift from models to reasoning systems
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Most enterprise AI strategies are already behind. Not because they picked the wrong model, but because they are still thinking at the model layer. The real shift is happening one level up, where AI becomes a system that can reason, use tools, retain context, and execute work
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Robot Dog Revolutionizes Spring Harvest Logistics Automation
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Meet the Cyber Tea Farmer: #Robot Dog Transforms Spring Harvest #Logistics
— Ronald van Loon (@Ronald_vanLoon) 20 avril 2026
by @DeepRobotics_CN#Robotics #Engineering #Innovation #Technology pic.twitter.com/wZ5oSJTr1KMeet the Cyber Tea Farmer: #Robot Dog Transforms Spring Harvest #Logistics
by @DeepRobotics_CN #Robotics #Engineering #Innovation #Technology