I have my AI read 40,000 posts a day from the AI community here on X and it builds this site with the biggest news: https://
alignednews.com/ai But if you want the firehose, I built the most complete lists of the AI industry (50,000 people, 8,700 companies) that exists here on X:
RESEARCH
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AI aggregator site with curated industry lists
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Mixture of Experts (MoE) Training Explained: Compounding Loops and Expert Specialization
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MoE Training, Part 2 — in one tweet:
— Satya Mallick (@LearnOpenCV) 22 mai 2026
You start with random weights. By chance, one expert is slightly better at legal questions. Router notices, sends more its way. It gets better. Snowballs.
Same compounding loop that turns a slightly-talented 7-year-old into an IMO medalist.
—… pic.twitter.com/gXIjIRHlGZMoE Training, Part 2 — in one tweet:
You start with random weights. By chance, one expert is slightly better at legal questions. Router notices, sends more its way. It gets better. Snowballs.
Same compounding loop that turns a slightly-talented 7-year-old into an IMO medalist.
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AutoResearchClaw: AI Tool Automates Full Research Pipeline
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Karpathy automated experiments. AutoResearchClaw automated the whole lab. Most AI research tools handle one step. This one is a GitHub repo that handles all of them. AutoResearchClaw takes one idea as input. It outputs a full conference paper with real experiments, verified
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Kuaishou OneSearch-V2: Generative Search That Understands Intent
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What if your search engine could understand not just what you type, but what you really mean? Kuaishou Technology presents OneSearch-V2: a generative search framework that reasons like a human before returning results. It uses three clever tricks: (1) a “thought” step to deeply
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Gated DeltaNet-2: Decoupling Erase and Write in Linear Attention
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Gated DeltaNet-2: Decoupling Erase and Write in Linear Attention Paper: https://
github.com/NVlabs/GatedDe
ltaNet-2/blob/main/paper/GDN2_paper.pdf
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Code: https://
github.com/NVlabs/GatedDe
ltaNet-2
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Confusion over GPT model naming conventions
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Though I will continue to insist that the path we were on would have been much clearer if o3 had been called GPT-5 and GPT-5 had been called GPT-5.5 and GPT-5.2 had been called GPT-6.
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Models progressing from basic math to solving hard problems
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Its funny how much the whole "strawberry" thing, which turned out to be o1-preview, was dismissed as overhyped at launch when it is clear in retrospect that it was way underhyped. A direct line from models unable to do basic math to solving unresolved math problems in 18 months.
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Gemini 3.5 Flash Shows Major Progress and Competitiveness
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Gemini 3.5 Flash has made huge progress from 3.1 Pro on GDPval, Flash is competing at the frontier, post training going strong 🙂
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Models as the prime mover behind AI products
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I would push back a little: because the models are so good & improving, they don't have to be the product. But it is the model that is the prime mover. If they weren't so generally capable, the harnesses & apps the labs build around them would be hard to build and wouldn't work.
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Hermes and OpenClaw agents share a single brain
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This is HOW my Hermes and OpenClaw Agents share a single brain. Hermes Agent is the orchestrator with OpenClaw agents as the squad.