Dancing with Qubits — From qubits to algorithms, embark on the Quantum Computing journey shaping our future: http://
amzn.to/4bJNwFj [2nd Edition] v/ @PacktDataML Covers Quantum Machine Learning and AI ——————
#ComputerScience #ComputationalScience
RESEARCH
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Exploring Quantum Machine Learning and AI Algorithms
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Computer Age Statistical Inference: Foundations for Data Science and AI
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Computer Age Statistical Inference — Algorithms, Evidence, and Data Science: http://
amzn.to/47zAhar -
RMS-MoE adds Co-Activation Memory to Mixture-of-Experts
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Why do Mixture-of-Experts models keep re-computing the same expert choices for similar inputs? Researchers from Mashang Consumer Finance, Nanjing University, and Alibaba Group introduce RMS-MoE: they add a Co-Activation Memory that remembers which expert teams worked best for
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AI takes control of your body to teach new skills
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#AI Temporarily Takes Control of Your Body to Teach New Skills
— Ronald van Loon (@Ronald_vanLoon) 16 mai 2026
by @BrianRoemmele#Innovation #ArtificialIntelligence #MachineLearning #ML pic.twitter.com/E4d1ix5zmz#AI Temporarily Takes Control of Your Body to Teach New Skills
by @BrianRoemmele #Innovation #ArtificialIntelligence #MachineLearning #ML -
SANA-WM Introduces Efficient Minute-Scale World Modeling
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"SANA-WM Efficient Minute-Scale World Modeling" Most world models can generate short controlled clips, but minute-long 720p rollouts usually need huge models, massive private data, and multi-GPU inference. This paper makes long-horizon world modeling much more practical by
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VGGT-Ω: Scaling 3D Reconstruction Models with Feed-Forward Neural Networks
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“VGGT-Ω” 3D reconstruction models is scaling like LLMs. Instead of relying on slow optimization pipelines, VGGT-Ω predicts cameras and depth in one feed-forward pass, even for dynamic video. This research makes that scaling practical with scene registers, lighter prediction
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Researchers convert autoregressive VLM into diffusion-based model
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What if you could get the smarts of an autoregressive AI model but with much faster generation? Researchers from Shanghai Academy of AI for Science and Fudan University present BARD. They convert a standard autoregressive VLM into a diffusion-based one using progressive block
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Moving beyond LLMs toward world models in AI research
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Truly an all-star cast, on one of the most important questions in AI. Thrilled to see some many people finally willing to confront the hard questions of how we can move beyond LLMs, and into what world models are really about.
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Causal Emergence Predicts Reward in RL Agents
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The Causally Emergent Alignment Hypothesis: Causal Emergence Aligns with and Predicts Final Reward in Reinforcement Learning Agents Federico Pigozzi, Michael Levin: https://
arxiv.org/abs/2605.06746 #AIAgents #ReinforcementLearning -
Causal Emergence Alignment Hypothesis in Reinforcement Learning Agents
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The Causally Emergent Alignment Hypothesis: Causal Emergence Aligns with and Predicts Final Reward in Reinforcement Learning Agents Federico Pigozzi, Michael Levin: https://
arxiv.org/abs/2605.06746 #AIAgents #ReinforcementLearning