What if LLM reinforcement learning could assign credit more accurately by thinking step by step? Researchers from Peking University and Microsoft Research Asia introduce GenAC: a generative critic that replaces one-shot value predictions with chain-of-thought reasoning before
GENERATIVE AI
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GPT-5.5 Pro applies research technique to generate funny word pairs
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GPT-5.5 Pro faces its hardest academic challenge: to apply the technique from a paper analyzing which word pairs were funny & why to come up with its own It came up with scrotum snorkel, tuba subpoena, waffle coffin, toad commode, diarrhea tiara, banana tribunal & muffin ruffian
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AI-powered transformation of RGB+D imagery into 3D assets
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Static scans provide context but the world is dynamic. Provide RGB+D imagery and get articulated simulation ready 3d assets back.
— Bilawal Sidhu (@bilawalsidhu) 17 mai 2026
Am very bullish on this approach reaching a quality threshold for production 3d use cases. https://t.co/iTCQWstSoBStatic scans provide context but the world is dynamic. Provide RGB+D imagery and get articulated simulation ready 3d assets back. Am very bullish on this approach reaching a quality threshold for production 3d use cases.
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Hermes Agent Self-Evolving Skills and Memory Architecture
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self-evolving skills in Hermes agent. i found this to be the most powerful feature in Hermes. the agent doesn't just solve problems, it remembers how it solved them. memory handles facts, and skills handle procedures. the difference matters because knowing that a Kubernetes
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Transformer Explainer: Visualizing How GPT Models Work
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This free interactive explainer just exposed how GPT actually works.
— AlphaSignal AI (@AlphaSignalAI) 17 mai 2026
Most people treat Transformers like magic. You type something in, words come out.
What happens inside stays a black box for almost everyone.
Transformer Explainer cracks that box wide open. It runs a live… pic.twitter.com/dkSxhjTFIgThis free interactive explainer just exposed how GPT actually works. Most people treat Transformers like magic. You type something in, words come out. What happens inside stays a black box for almost everyone. Transformer Explainer cracks that box wide open. It runs a live
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Debating the value of AI-generated content versus AI-powered tools
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For me that's what it comes down to: it's respecting another person's time If someone shows me a vibe-coded tool that works and solves a problem for me, they've saved me time If they ask me to read AI-generated slop that doesn't help me learn anything they're wasting my time
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Prompt to transform photo into plasticine claymation via GPT-Image
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Chose a photo: Use GPT-Image 2 or NBP Prompt: Transform this photo into meticulously hand-crafted plasticine puppets, combining exaggerated, caricatured features with a highly physical, weight-based, style absurdist claymation. Keep the EXACT composition. Grotesque
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Analysis of LLM failure modes in reasoning and token prediction
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The strawberry test. The "how many R's" test. The car wash riddle. Same failure mode every time. AI predicts the most probable answer, not the correct one. When probability matches reality, it looks like intelligence. When it doesn't, it looks like confidence without
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Understanding LLM Hallucinations and Pattern Matching
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This is what a hallucination actually looks like in practice. Not random nonsense. A confident, structured answer that happens to be wrong. The model pattern-matched to the most likely answer instead of the literal one. That's exactly what it does with your prompts too.
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ChatGPT fails a visual riddle about hidden horses
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The image shows 4 labeled horses. ChatGPT confidently identified a hidden 5th horse in the center where the bodies overlap. Detailed. Well-reasoned. Visually plausible. And wrong. The real 5th horse is the word "HORSE" in the title itself. Four drawn. One written. Five total.