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Sunday4 items

Saturday4 items

  1. HuxiuOpinion
    AI score53

    After Nvidia chips became hard to buy, what keeps China's large models running?

    A Huxiu analysis points out that domestic computing power can now cover large model operation: Zhipu's domestic-chip inference cluster has reached a scale of 100,000 cards, and Meituan's LongCat-2.0 has also completed training on domestic computing power. However, Ascend 910C achieves an MFU of about 30%-35% in trillion-parameter post-training, lower than H100's 40%-50%. The article breaks computing efficiency into three variables—chips, software, and models—and compares the four paths of Zhipu, MiniMax, DeepSeek, and Kimi, concluding that Zhipu has the highest short-term certainty, while DeepSeek has the greatest medium-term elasticity. The author proposes three tracking indicators—capacity, efficiency, and cost—and argues that only when all three improve simultaneously can domestic computing power shift from a backup option to a cost advantage.

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

Friday5 items

  5. PlatformerFirst-partyOpinion
    AI score57

    Can Muse make people forget the metaverse?

    At its developer conference, Meta pushed Muse, its personal agent that is less than a month old, to the center of its strategy; Zuckerberg said it will grow into a personal superintelligence used by billions of people, and the company plans to launch voice conversation capabilities, integration with the VR operating system, and companion hardware called Muse Charm. The author, Casey Newton, noted that Muse has about 500,000 weekly users, far short of Threads surpassing 100 million in five days, and argued that Meta's move is more about generating momentum amid capital expenditures reaching as high as $145 billion this year. He also tested the Meta VR Glasses, which weigh 100 grams and claim 5K displays, and concluded that they significantly reduce the bulk and price of the Vision Pro, though the question of what VR is for remains unresolved.

    #Industry news#Agents#OpenAI

Thursday4 items

  2. philschmidOpinion
    AI score65

    English translation is being prepared.

    Quoted postSpencer Schiff · @SpencerKSchiff

    I drew this today. None of the frontier models come anywhere close to matching the correct name to each person. I feel like this is a pretty good visual test so I’m looking forward to trying it with future models. https://t.co/68lJuVCImb

    #Industry news#Multimodal#Google

Wednesday2 items

Tuesday4 items

  2. Latent SpaceOpinion
    AI score62

    TypeSafe CEO Diogo Almeida on Jev: Building a System One Model for Production, Not for God

    InstructGPT paper author and TypeSafe CEO Diogo Almeida detailed his new model Jev on the Latent Space podcast, describing it as a System One large programmatic model oriented toward code consumption, with its core innovation being an unpublished RLCD (reinforcement learning for calibrated decision-making), optimized for "intelligence per dollar" rather than human preference feedback. He criticized RLHF for causing mode collapse, sycophancy, and hallucinations, arguing that safety alignment suits products like ChatGPT but fragments intelligence at the API layer, and said TypeSafe would rather be seen as a data lab, refusing to publish benchmark tests. He revealed that Jev's daily token consumption has exceeded one trillion since launch, and previewed follow-up models such as ReasoningJev.

    #Industry news#Agents#Reasoning