From LLMs to hallucinations, here’s a simple guide to common #AI terms
by @riptari @techcrunch Learn more: https://
bit.ly/4vukgg0 #GenerativeAI #ArtificialIntelligence #MachineLearning #ML
MACHINE LEARNING
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Guide to Common AI Terms: LLMs and Hallucinations Explained
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CodeX: Open Source 3D Asset Generation Framework
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Here the link : https://
github.com/anisayari/code
x-3d-asset
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Computer Vision Evolution: From Detection to Scene Comprehension
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Computer vision has moved beyond simple detection to understanding what is actually happening in a scene. Instead of just identifying objects, AI can now interpret behavior, context, and real world events. That shift from recognition to comprehension is what makes it truly… pic.twitter.com/06CX6H2Ldb
— Satya Mallick (@LearnOpenCV) 18 avril 2026Computer vision has moved beyond simple detection to understanding what is actually happening in a scene. Instead of just identifying objects, AI can now interpret behavior, context, and real world events. That shift from recognition to comprehension is what makes it truly
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Machine Learning Drives Dynamic Pricing Through Real-Time Algorithms
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Machine learning enables dynamic pricing through demand signals and competitive data in real time. As margins narrow and volatility grows, algorithmic updates align sales and finance around measurable targets and limit manual pricing decisions. Microblog by @antgrasso
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8 LLM Types Powering AI Agents and Agentic Systems
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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
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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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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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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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Adaptive Thinking Trade-off: Token Burn vs Performance Regression
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The adaptive thinking burns more tokens and the results drop. That's a regression no matter how the marketing reads. The real question is whether this is a calibration bug fixable in a point patch or a deeper reward-shaping choice that won't roll back… in any case, not so happy