Ready for truly interactive, real-time AI video generation in live streams? Tianrui Feng et al. from UT Austin, UC Berkeley, Stanford, MIT, and others just dropped StreamDiffusionV2. This training-free pipeline uses clever scheduling and parallel processing to optimize video
RESEARCH
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Polsia Reveals AI Slop Problem in Reverse
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I recently learned that "Polsia" is "AI Slop" spelled in reverse.
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FAIR Teams Release Incredible New Research Findings
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incredible new research from our teams at FAIR https://t.co/SEUD9jaTiL
— Alexandr Wang (@alexandr_wang) 27 mars 2026incredible new research from our teams at FAIR
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Whose Mind Is It Anyway? AI and Machine Learning Discussion
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Whose Mind Is It Anyway?
by @JohnNosta @PsychToday Learn more: https://
bit.ly/4bpWhqu #AI #MachineLearning #ArtificialIntelligence #DL -
Jeff Dean discusses computer architecture and AI hardware with Bill Dally at GTC
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The video of my conversation with Bill Dally at GTC last week is up. I always enjoy talking to Bill, and we had a wide ranging discussion about computer architecture, model training, specialized inference hardware, custom interconnects, and more! piped.video/g8BuAtM3fp4?si=QMTb…
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ARC-AGI-3: a different test with different rules and measurements
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It helps to think of ARC-AGI-3 as a different test entirely than the previous ARC-AGIs. It measures different things (though, as in the previous tests, precisely what it measures isn’t clear) and has different rules. That doesn’t mean it isn’t good, but it is its own thing.
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MAGNet: Unified Autoregressive Diffusion Model for Multi-Agent Motion
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When people share a space, their movements become intertwined. Embodied agents need to understand these social dynamics to interact effectively.
— Vongani Maluleke (@vonekels) 27 mars 2026
Introducing MAGNet 🧲, a unified autoregressive diffusion forcing model for multi-agent motion generation that captures these… pic.twitter.com/Doc6fDLKJ9When people share a space, their movements become intertwined. Embodied agents need to understand these social dynamics to interact effectively. Introducing MAGNet 🧲, a unified autoregressive diffusion forcing model for multi-agent motion generation that captures these interactions. MAGNet is flexible: predict the future, fill in missing motion, or have people react to each other, all while naturally scaling to N>2 people and generating ultra-long motion sequences.
→ View original post on X — @berkeley_ai, 2026-03-27 02:07 UTC
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Survey on Agentic RAG Systems and Architectures
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A Survey on Agentic RAG! #BigData #Analytics #AI #MachineLearning #DataScience #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
geni.us/Agentic–RAG -
New AGI Eval Focuses Research Efforts on Critical Gaps
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If you care about the rate of AGI progress, you should be excited about a new eval that focuses research efforts by pointing out important gaps & providing a way to measure progress towards fixing them If instead you only care about having your preconceptions confirmed, too bad
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ARC-AGI-3 Environments Mirror Scientific Method for Breakthrough AI
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Many people expect that current AI is ready to cure cancer and do breakthrough new science. ARC-AGI-3 envs are like a microcosm of the scientific method: you must observe a tiny world, form a theory of how it works, test it, iterate until correct. Over the course of a few