How Lightricks trains video diffusion models at scale with JAX on TPU
cloud.google.com·53m
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[News] SK hynix, Samsung, and SanDisk Bet on HBF — The Next Battleground in Memory Sector
trendforce.com·9h·
Discuss: r/hardware
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Real-World Applications of AI: How It Will Impact Industries in 2026
instandart.com·10h·
Discuss: DEV
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From Zero to LLMOps Hero: Your 101 Guide to Running LLMs in Production
analyticsvidhya.com·1d
🤖AI
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Bridging Accuracy and Explainability in EEG-based Graph Attention Network for Depression Detection
arxiv.org·12h
🤖AI
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Amortized Likelihood-Free Stochastic Model Updating via Conditional Diffusion Model for Structural Health Monitoring
sciencedirect.com·1d
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Next-Latent Prediction Transformers Learn Compact World Models
arxiv.org·12h
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Learnings from the Zurich AI Safety Day
lesswrong.com·53m
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RF-Behavior: A Multimodal Radio-Frequency Dataset for Human Behavior and Emotion Analysis
arxiv.org·12h
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A two-stage semi-supervised domain generalization network for fault diagnosis under unknown working conditions
sciencedirect.com·2d
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Deception Decoder: Proposing a Human-Focused Framework for Identifying AI-Generated Content on Social Media
arxiv.org·12h
🤖AI
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GRAVER: Generative Graph Vocabularies for Robust Graph Foundation Models Fine-tuning
arxiv.org·12h
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SoK: Systematizing a Decade of Architectural RowHammer Defenses Through the Lens of Streaming Algorithms
arxiv.org·12h
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Predicting Pedestrian Intent with Spatiotemporal Graph Neural Networks for Enhanced AEB Systems
dev.to·2d·
Discuss: DEV
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Structural sign herdability of linear time-invariant systems:theory and design for arbitrary network structures
arxiv.org·12h
🤖AI
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Book review: “Build a DeepSeek Model (From Scratch)”
dev.to·3d·
Discuss: DEV
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E2E-VGuard: Adversarial Prevention for Production LLM-based End-To-End Speech Synthesis
arxiv.org·12h
🤖AI
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TAI #178: Kimi K2 Thinking Steals the Open-Source Crown With a New Agentic Contender
pub.towardsai.net·2h
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VLA^2: Empowering Vision-Language-Action Models with an Agentic Framework forUnseen Concept Manipulation
paperium.net·4d·
Discuss: DEV
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LLM-Guided Reinforcement Learning with Representative Agents for Traffic Modeling
arxiv.org·12h
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