What if a model could catch and correct its own mistakes while learning? Researchers from Peking University present a new AI method for visual grounding. Instead of just matching words to image regions, their system uses a "confidence score" to flag its unreliable guesses. It
MACHINE LEARNING
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DeepSeek v4 Pro Added to Playable Gallery
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Here's DeepSeek v4 Pro. Added to the playable gallery as well. https://t.co/foIqZakU9p pic.twitter.com/wpQ8kj9AAT
— Ethan Mollick (@emollick) 24 avril 2026Here's DeepSeek v4 Pro. Added to the playable gallery as well.
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First TiKZ Sparks unicorns from DeepSeek v4
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My first two TiKZ Sparks unicorns from DeepSeek v4. (Expert mode, from the DeepSeek site, which is supposed to be v4 Pro according to the release)
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DeepSeek v4 Sets New SOTA Open Source Record
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Deepseek v4 is a huge step upwards compared to DeepSeek 3, outperforms on SWE verified opus 4.6 and GPT-5.4 and sets a new record on Codeforces. Needs to be tested against opus 4.7 and GPT-5.5 tho and see if real world usage holds its promises. Big release! Sota open source
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Study: Overreliance on AI may undermine work confidence
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Overreliance on #AI programs may undermine confidence at work, study finds
by American Psychological Association @TechXplore_com Learn more: https://
bit.ly/4dSpwE1 #ArtificialIntelligence #MachineLearning #ML -
Seeing Fast and Slow: Learning Video Temporal Flow
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Seeing Fast and Slow
— AK (@_akhaliq) 24 avril 2026
Learning the Flow of Time in Videos
paper: https://t.co/LrIsGh3NLI pic.twitter.com/p8Hb1LjU95Seeing Fast and Slow Learning the Flow of Time in Videos paper: https://
huggingface.co/papers/2604.21
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KMLP: Hybrid AI Model for Web-Scale Tabular Data
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What if a single AI model could automatically learn from billions of messy data rows, eliminating the need for manual feature engineering? Researchers from Zhejiang University and Ant Group present KMLP, a new hybrid architecture for web-scale tabular data. It uses a clever
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8 Types of LLMs used in AI Agents by @ingliguori
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8 Types of #LLMs used in #AIAgents by @ingliguori #GenerativeAI #ArtificialIntelligence #MachineLearning #MI
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Sakana AI Fugu Launches Beta API with Recursive Test-Time Scaling
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One of my favorite things about Sakana Fugu is the recursive test-time scaling. When allowed to call itself recursively, it reads its own prior output and spins up corrective workflows on the fly. We are opening up the API for beta testers to try it out: https://
sakana.ai/fugu-beta/ -
Recursive Self-Improvement Loop: From AutoResearch to AGI
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Recursive self-improvement is not AGI hype. And it’s not just prompt tuning either. Karpathy’s autoresearch ran 700 experiments on a single GPU, improved its own training code, and kept what worked. This loop is already here. I break down how it works, where it fails, and how