A Wave of Unexplained Bot Traffic Is Sweeping the Web 5 months ago
That or unhinged, state sponsored Claude armies.
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cmccand1
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Response to “How much U.S. taxpayer money was spent on this?” - now flagged: $1.2B Source: https://defensescoop.com/2024/04/25/iron-beam-procurement-us...
Response to “How much U.S. taxpayer money was spent on this?” - now flagged:
$1.2B
Source: https://defensescoop.com/2024/04/25/iron-beam-procurement-us...
Training LLMs for honesty via confessions 7 months ago
I think the problem with your line of reasoning is a category error, not a mistake about arithmetic.
I agree that every step of an LLM’s operation reduces to Boolean logic and arithmetic. That description is correct. Where I disagree is the inference that, because the implementation is purely arithmetic, higher-level concepts like representation, semantics, knowledge, or even lying are therefore meaningless or false.
That inference collapses levels of explanation. Semantics and knowledge are not properties of logic gates, so it is a category error to deny them because they are absent at that level. They are higher-level, functional properties implemented by the arithmetic, not competitors to it. Saying “it’s just numbers” no more eliminates semantics than saying something like “it’s just molecules” eliminates biology.
So I don’t think the reduction itself is wrong. I think the mistake is treating a complete implementation-level account as if it exhausts all legitimate descriptions. That is the category error.
Training LLMs for honesty via confessions 7 months ago
Well, then you didn't look very hard. Where do you think we got the idea for artificial neurons from?
Training LLMs for honesty via confessions 7 months ago
Human brains depend on neurons and "neuronal arithmetic". In fact, their statements are merely "neuronal arithmetic" that gets converted to speech or writing that get imbued with semantic meaning when interpreted by another brain. And yet, we have no problem attributing dishonesty or knowledge to other humans.
That’s why the model runs locally.
Here’s some that were failing:
Amazing concept! The app is having a hard time finding the transcripts for YouTube videos. It wasn’t able to find a single one that I tried, even older videos. However, I’ve used custom GPT‘s that are able to, for example, provide summaries of YouTube videos successfully so something’s not working for this service. Maybe they’re using speech-to-text when no transcript is available?