Equation 2 · The Hardest Unsolved Problems in Open-Weight AI
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Put the two facts together and the shape of the unsolved problem is precise. It is not “open weights are dangerous” — that is a separate, contested claim examined below. It is that the field has no method, proposed or implemented, for making a release reversible , and every mitigation on offer — better licences, use-restriction clauses, staged access — governs the decision to release, not anything that happens afterward. A simple way to see why after-the-fact governance cannot rescue the situation is to notice how quickly the number of independent copies dominates any per-copy probability of control. If N copies exist and each copyholder independently retains theirs with probability q close…
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Put the two facts together and the shape of the unsolved problem is precise. It is not “open weights are dangerous” — that is a separate, contested claim examined below. It is that the field has no method, proposed or implemented, for making a release reversible , and every mitigation on offer — better licences, use-restriction clauses, staged access — governs the decision to release, not anything that happens afterward. A simple way to see why after-the-fact governance cannot rescue the situation is to notice how quickly the number of independent copies dominates any per-copy probability of control. If N copies exist and each copyholder independently retains theirs with probability q close to one, the probability that every single copy is eventually deleted or brought back under control is , so the probability that at least one copy survives indefinitely is
Sources cited in the article section
- [15] Runaway LLaMA: How Meta's LLaMA NLP Model Leaked ↗
- [3] Securing AI Model Weights: Preventing Theft and Misuse of Frontier Models ↗
- [1] Our Position on Open-Weights Models ↗
- [5] LoRA Fine-tuning Efficiently Undoes Safety Training in Llama 2-Chat 70B ↗
These citations give research context. Read each source to check which claims it supports.