Depth Anything 3: Recovering the Visual Space from Any Views ( Code , Model available). lot of examples on project page.

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Project page: https://depth-anything-3.github.io/ Paper: https://arxiv.org/pdf/2511.10647 Demo: https://huggingface.co/spaces/depth-anything/depth-anything-3 Github: https://github.com/ByteDance-Seed/depth-anything-3 Depth Anything 3, a single transformer model trained exclusively for joint any-view depth and pose estimation via a specially chosen ray representation. Depth Anything 3 reconstructs the visual space, producing consistent depth and ray maps that can be fused into accurate point clouds, resulting in high-fidelity …

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Build a biomedical research agent with Biomni tools and Amazon Bedrock AgentCore Gateway

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This post is co-authored with the Biomni group from Stanford. Biomedical researchers spend approximately 90% of their time manually processing massive volumes of scattered information. This is evidenced by Genentech’s challenge of processing 38 million biomedical publications in PubMed, public repositories like the Human Protein Atlas, and their internal repository of hundreds of millions of …

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A new top score: Advancing Text-to-SQL on the BIRD benchmark

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In the fast-evolving world of agentic development, natural language is becoming the standard for interaction. This shift is deeply connected to the power of operational databases, where a more accurate text-to-SQL capability is a major catalyst for building better, more capable agents. From empowering non-technical users to self-serve data, to accelerating analyst productivity, the ability …

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Google’s new AI training method helps small models tackle complex reasoning

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Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning tasks. Supervised Reinforcement Learning (SRL) reformulates problem-solving as a sequence of logical “actions,” providing rich learning signals during the training process. This approach enables smaller models to learn …

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New prediction breakthrough delivers results shockingly close to reality

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Researchers have created a prediction method that comes startlingly close to real-world results. It works by aiming for strong alignment with actual values rather than simply reducing mistakes. Tests on medical and health data showed it often outperforms classic approaches. The discovery could reshape how scientists make reliable forecasts.

I made a full music video with Wan2.2 featuring my AI artist

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Workflow is just regular Wan2.2 fp8 6 steps (2 steps high noise, 4 steps low), lighting lora on the high noise expert then interpolated with this wf (I believe it came from the wan2.2 Kijai folder). Initial images all coming from nanobanana. I want to like Qwen but there’s something about the finish that feels …

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