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Articole: 6
  1. A “slowdown” might actually improve OpenAI and Anthropic products

    The frontier models have now reached a point where they can meaningfully contribute to scientific research.

  2. A connection between capability-based security and lambda calculus

    Motivation The security model commonly used in desktop operating systems nowadays is woefully inadequate: it was originally designed to protect user A from user B, but not user A from program A.

  3. METR’s time-horizon of software engineering tasks does not mean what you think it means

    Consider: METR: Measuring AI Ability to Complete Long Tasks METR’s “Measuring AI Ability to Complete Long Tasks” paper uses “a combination of RE-Bench, HCAST, and 66 novel shorter tasks” to measure “50%-task-completion time horizon”, which is defined as:…

  4. The future of LLMs: cognitive core + cartridges?

    Andrej Karpathy introduced a concept of a “cognitive core”: post #1: “a few billion param model that maximally sacrifices encyclopedic knowledge for capability” post #2: “the idea of stripping down LLMs, of making it harder for them to memorize, or active…

  5. Experiments with automated ML experiments

    How far is AI from being able to improve itself?

  6. Can LLMs actually represent meaning? / Getting over the impenetrable wall

    A discussion of AI and LLM often hits an impenetrable wall: “But it’s just a statistical model, and thus it cannot really …”.