| As many of you might be aware, the ARC-AGI-3 competition has just started ... (In case you're not familiar: it's a human/AI benchmark designed to see what AI still struggles with, that humans solve with ease - basically trying to push AI research to focus on new ideas that make AI think more human-like, assuming that that's what is required to solve such tasks, you could read more in their docs...) Seeing as the benchmark has so far only been solved at 0.68%, I was wondering what a real solution would look like: If a system has to explore and collect data, infer rules and patterns, decide which are useful, and then establish a set of rules and apply them, it seems that it such a system/algorithm would do essentially what a successful scientist would do. Apart from it being quite unrealistic in very near future, I do think that such a model (that achieves ~100% on arc-3), if open sourced (which is a condition to win the competition), would hold great potential for dangerous application, such as the military (engineering weapons), cybersecurity, manipulation, etc... Do you agree? [link] [comments] |
(How) could an ARC-3 solution be a threat? [D]
Reddit r/MachineLearning / 5/2/2026
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Key Points
- The ARC-AGI-3 (ARC-3) competition has recently started, and the post notes that so far only about 0.68% of the benchmark tasks have been solved.
- The author argues that a hypothetical ~100% ARC-3 solver would likely involve processes similar to a human scientist—exploring, inferring patterns/rules, selecting what’s useful, and then applying those rules.
- They suggest that if such a solution were open-sourced to win (as required by the competition), it could have significant potential for misuse in high-risk areas like military engineering, cybersecurity, and manipulation.
- The post poses a question to readers on whether they agree and how an ARC-3 level system could pose a threat even in an extreme “this year” hypothetical scenario.
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