8 types of LLMs used in AI agents GPT • MoE • LRM • VLM • SLM • LAM • HRM • LCM Different models for reasoning, perception, planning, and action — not just chat. Agentic AI = model orchestration. #AI #LLMs #AgenticAI #GenAI #MachineLearning
INNOVATION
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AI and Law Integration Driving UAE 2031 Vision Forward
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شكرا على تكريمكم أولاً فاليوم نشهد التكامل القوي بين القانون والذكاء الاصطناعي مع الشكر لجمعية الإمارات للمحامين والقانونيين على هذه المبادرة المتقدمة 🙏. وفخور بالمساهمة في تحقيق رؤية الإمارات 2031 من خلال دمج التقنيات المتقدمة في المشهد القانوني. الابتكار ليس مجرد خيار، بل هو… pic.twitter.com/zZRfZqJxaI
— Shadi Dawi (@shadi_dawi) 18 avril 2026شكرا على تكريمكم أولاً فاليوم نشهد التكامل القوي بين القانون والذكاء الاصطناعي مع الشكر لجمعية الإمارات للمحامين والقانونيين على هذه المبادرة المتقدمة . وفخور بالمساهمة في تحقيق رؤية الإمارات 2031 من خلال دمج التقنيات المتقدمة في المشهد القانوني. الابتكار ليس مجرد خيار، بل هو
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Meta AI Proposes Neural Computer Where AI Becomes the Hardware
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The day AI replaces the computer wasn't supposed to come this fast.
— AlphaSignal AI (@AlphaSignalAI) 18 avril 2026
Right now, AI uses computers as tools.
This paper asks a different question: What if AI became the computer itself?
Neural Computer is a new paper from Meta AI.
It proposes a machine where computation,… pic.twitter.com/1AjqEC9LprThe day AI replaces the computer wasn't supposed to come this fast. Right now, AI uses computers as tools. This paper asks a different question: What if AI became the computer itself? Neural Computer is a new paper from Meta AI. It proposes a machine where computation,
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Intelligent Data Filtering Solves Manufacturing Efficiency Challenge
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2026 manufacturing efficiency barrier: abundance of data. Connected factories monitor tens of thousands of assets generating hundreds of thousands of data points. The solution is intelligent filtering, not more sensors.
— Lucian Fogoros (@fogoros) 18 avril 2026
Partner content with @AI4ProdOutcomes. #Infinite_iiot pic.twitter.com/z4MIfgFNBQ2026 manufacturing efficiency barrier: abundance of data. Connected factories monitor tens of thousands of assets generating hundreds of thousands of data points. The solution is intelligent filtering, not more sensors.
Partner content with @AI4ProdOutcomes
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Evaluation Rubrics Fail on Novel AI Research Paradigms
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Long-form eval breaks on novelty. A rubric written before the research exists can't score research that shifts the criteria. 2,500 rubrics is a real dataset, but the measurement question is whether the set handles reports that break the rubric assumptions. That's where deep
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AI Agent Progress: Real Gains Beyond Hype Metrics
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The stagnation take holds up until you ask it to compete with actual evals. Coherent 30-minute agent runs, tool-call reliability on complex schemas, long-context retrieval that finally works. The progress is there, it just isn't a dunk thread.
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Agentic RAG: Planning Over Agent Labels in Retrieval Systems
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The real contrast isn't static retrieval vs. adaptive. It's whether the retrieval layer can decide to stop, re-plan, and try a different tool. Agentic RAG is just RAG with a planner in front of it. The name is new, the accuracy gain is from the planning, not the "agent" label.
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Voice-to-Prototype Democratizes Design for Non-Designers
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Voice-to-prototype is the part of the stack that was always going to eat the "I can't design" excuse. Speaking a single-page doc into existence is where non-designers actually ship something that looks ok. The UX framing is what matters here, not the raw capability, since voice
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Long-run model consistency becomes key performance benchmark
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Long uninterrupted runs are the new benchmark. A model that doesn't stop and start on a 50k-token refactor is shipping a different product than one that does, even if they score similar on short tasks. 4.6 stopping was masking how sensitive the previous loop was to noise.
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AI Economy: From Value Extraction to Creation Shift
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At some point over the past century or so modern economy, especially in America, started tilting from value creation to value extraction. AI is only making it more explicit now. And the real economic impact of AI will only start happening once value creation becomes dominant