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Wednesday

  1. Latent Space

    SF Compute CEO Evan Conrad on Programmable Data Centers and the Compute Market

    SF Compute CEO Evan Conrad said on the Latent Space podcast that the compute market must first achieve physical delivery—that is, actually delivering usable GPU compute—before discussing financialization; otherwise, market manipulation and basis risk are likely to arise. He said SF Compute has already put 5% of its capacity on the order book, and that customers who spend $100 to buy capacity can on average recover $25 by reselling it, with hundreds of millions of dollars in trading volume already completed. He also said the company does not hold hardware in order to remain neutral, and that it already supports customers in partitioning InfiniBand fabric online themselves.

    SF Compute CEO Evan Conrad said on the Latent Space podcast that the compute market must first achieve physical delivery—that is, actually delivering usable GPU compute—before discussing financialization; otherwise, market manipulation and basis risk are likely to arise. He said SF Compute has already put 5% of its capacity on the order book, and that customers who spend $100 to buy capacity can on average recover $25 by reselling it, with hundreds of millions of dollars in trading volume alread

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    #newsletter#Industry news#English text is being prepared.#English text is being prepared.

Tuesday

  8. Shao Meng

    Viggle Releases JST-2, a 3D-Native World Model

    Viggle has released JST-2, building its entire model stack in 3D space and representing the world with Physics-Native Tokens that carry xyz coordinates, attribute vectors, and dynamics vectors, rather than implicitly inferring physical laws from video pixels. The architecture consists of three parts: the JST encoder, JST generator, and JST decoder. A single forward inference generates a complete 3D scene in about 1 second, at a cost below $0.01 (B200), and supports up to 64 input views as a spatial context window. Blind human preference tests published by Viggle show that character generation wins 58.4% against Meshy 7.1 and 73.2% against Tripo H3.1, while video-generated motion wins 89.1% against DeepMotion. JST-3 plans to extend the learned dynamics to object interaction.

    Viggle has released JST-2, building its entire model stack in 3D space and representing the world with Physics-Native Tokens that carry xyz coordinates, attribute vectors, and dynamics vectors, rather than implicitly inferring physical laws from video pixels. The architecture consists of three parts: the JST encoder, JST generator, and JST decoder. A single forward inference generates a complete 3D scene in about 1 second, at a cost below $0.01 (B200), and supports up to 64 input views as a spat

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    #hot-signal#Model releases#Multimodal#Video
  14. Ant Group's inclusionAI: New GitHub repository

    Ant Group's inclusionAI publishes the sglang_ling_v3 repository on GitHub

    Ant Group's inclusionAI launches the sglang_ling_v3 repository on GitHub. Its contents are based on the open-source inference framework SGLang, which targets large language models, vision-language models, and diffusion models, and is optimized for agent workloads, large-scale serving, and RL rollout. The repository README shows that SGLang supports GPU, TPU, NPU, CPU, and Apple Silicon, and includes the built-in image and video generation engine SGLang Diffusion.

    PyPI version

    Ant Group's inclusionAI launches the sglang ling v3 repository on GitHub. Its contents are based on the open-source inference framework SGLang, which targets large language models, vision-language models, and diffusion models, and is optimized for agent workloads, large-scale serving, and RL rollout. The repository README shows that SGLang supports GPU, TPU, NPU, CPU, and Apple Silicon, and includes the built-in image and video generation engine SGLang Diffusion.

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    #engineering#English text is being prepared.#English text is being prepared.#Open-source ecosystem

Monday