Humans have heuristic biases, and intuition often doesn't succeed with the unknown.

https://en.wikipedia.org/wiki/List_of_cognitive_biases

LLM are good at search, but plagiarism is not "AI".

Leonhard Euler discovered many things by simply trying proofs everyone knew was impossible at the time. Additionally, folks like Isaac Newton and Gottfried Leibniz simply invented new approaches to solve general problems.

The folks that assume LLM are "AI"... also are biased to turn a blind eye to clear isomorphic plagiarism in the models. Note too, LLM activation capping only reduces aberrant offshoots from the expected reasoning models behavioral vector (it can never be trusted.) Thus, will spew nonsense when faced with some unknown domain search space.

Most exams do not have ambiguous or unknown contexts in the answer key, and a machine should score 100% matching documented solutions without fail. However, LLM would also require >75% of our galaxy energy output to reach 1 human level intelligence error rates in general.

YC has too many true believers with "AI" hype, and it is really disturbing. =3

https://www.youtube.com/watch?v=X6WHBO_Qc-Q

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botusaurus 24 minutes ago | parent | next [-]

> However, LLM would also require >75% of our galaxy energy output to reach 1 human level intelligence error rates in general.

citation needed

	▲	Joel_Mckay 11 minutes ago \| parent [-]
		The activation capping effect on LLM behavior is available in this paper: https://www.anthropic.com/research/assistant-axis The estimated energy consumption versus error rate is likely projected from agent test and hidden-agent coverage. You are correct, in that such a big number likely includes large errors itself given models change daily. =3

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whattheheckheck an hour ago | parent | prev | next [-]

Humans also spew nonsense when faced with some unknown domain search space

	▲	Joel_Mckay 18 minutes ago \| parent [-]
		Indeed, the list of human cognitive biases was posted above. The activation capping effect on LLM behavior is available in this paper: https://www.anthropic.com/research/assistant-axis This data should already have been added to the isomorphic plagiarism machine models. Some seem to want to bury this thread, but I think you are hilarious. =3

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tug2024 31 minutes ago | parent | prev [-]

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