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Nov 11Wed
  1. ChinaTalk

    US data company sells data worth about $500 million to Chinese AI labs, including reinforcement learning environments to help improve model performance in specific fields.

    US data company sold about $500 million data to Chinese AI labs, including reinforcement learning environments to help improve model performance in fields such as coding, networking, finance, law, and biology. These environments simulate the world to allow models to train repeatedly and use scoring standards to optimize output. Chinese labs can save over 70% of inference computing costs annually by purchasing the same RL environments as US companies like Anthropic and OpenAI.

Nov 1Sun
  1. Latent Space42

    How Arca uses Claude to support long-term financial work

    Arca stated at the AI Engineers' New York Summit that its agents primarily handle background work, but human advisors retain final decision-making authority. Agents only analyze and propose solutions, with transactions executed by humans. Agent tasks can last up to ten days, and the company has developed an internal memory system to track task progress and responsibility allocation. They use models from Anthropic and OpenAI, automatically selecting models based on internal benchmarks via a custom harness. In terms of security, agent operations are strictly limited, involving no client risk, and they use sandbox computing and additional measures to handle sensitive data.

Oct 29Thu
  1. QbitAI72

    Tenstorrent releases Tianhe 300 and Tongyang TY1200, on-site actual test targets NVIDIA H200 and Thor T5000.

    Tenstorrent releases cloud-based general-purpose GPU Tianhe 300 and edge product Tongyang TY1200 based on the Tianshu architecture, and compares them with NVIDIA H200, Jetson Thor T5000 on-site with random questions.

    Why it matters: On-site random tests, dual-track comparison of cloud and edge against NVIDIA, and providing reproducible test numbers and software stack implementation methods.

Oct 27Tue
  1. Latent Space42

    Supabase's AI App Backend Plan

    Supabase plans to run long-running workloads alongside its database using Supabase Compute, simplify schemas to make them easier for AI agents to understand, and design infrastructure that supports more applications. Its acquired Turso product supports scaling, and the company is using AI internally to improve efficiency while maintaining a parallel approach of open-source and commercial sales.