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<antirez> AI cybersecurity is not proof of work antirez 13 days ago. The proof of work is the wrong analogy: finding hash collisions, while exponentially harder with N, is guaranteed to find, with enough work, some S so that H(S) satisfies N, so an asymmetry of resources used will see the side with more "work ability" eventually winning. But bugs are different: 1. Different LLMs executions take different branches, but eventually the possible branches based on the code possible states are saturated. 2. If we imagine sampling the model for a bug in a given code M times, with M large, eventually the cap becomes not "M" (because of saturated state of the code AND the LLM sampler meaningful paths), but "I", the model intelligence level. read the full post at http://antirez.com/news/163 GNU and the AI reimplementations antirez 52 days ago. Those who cannot remember the past are condemned to repeat it. A sentence that I never really liked, and what is happening with AI, about software pr

The real AI risk is inside the labs ▼antirez 47 days ago. Amodei in his latest blog post wrote a mix of agreeable things and things that I believe misrepresent where the real risk of AI is located. I want to focus my attention on why, among all the risks, open weight models constitute the mildest one. I write these words as a person who strongly believes AI may be very dangerous in the near future: 1. Exactly like what happened during the OpenAI / HF incident (which was a joke, but focus on the modalities, not the outcomes), the first serious AI incident is very likely to happen *inside*…

List of posts - <antirez>

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