111–120 of 571 posts
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Nobody wants to work for an AI, and nobody would elect one, and there is no math answer to how to choose who is forced to reduce growth (ie emissions), so really, "kumbaya" politics are the ONLY solution.
Wouldn't candidates use AI, like they used social media ads, to win?
> The answer was simple in hindsight. It just kept looking until it found it—and that persistence might show up in many other areas. Sounds more like brute forcing than intelligence, this time.
That seems a like the result for a lot of AI solves. It solves it due to persistence, on a problem that hasn’t been important enough for a human to invest significant time into.
Definitely a much better target to show the power of an AI LLM imho (as opposed to stealing from starving mathematicians).
> Historically, many of these problems were bottlenecked by human attention. Someone had to care enough to spend hours or days reading obscure material, testing unpromising ideas, tracing references, and trying things that might go nowhere I wonder how many of the recent results are due to the fact that very few looked at the problem to start with. Still great results, but the general impression is that it's more abo…
Given the close relationship between compression and intelligence, I'm somewhat surprised at how poorly the cutting edge models do with being concise.
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Nobody wants to work for an AI, and nobody would elect one, and there is no math answer to how to choose who is forced to reduce growth (ie emissions), so really, "kumbaya" politics are the ONLY solution.
Speak for yourself. I would much rather work for and elect AI.
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Astra told me yesterday: > The run baseline was captured without a physical MAC; the current device is not durably bound to it. > Engineering mode confirmation is the ESPHome component read-back; the LD2410 UART acknowledgement is not observed, so this is not proof the radar itself applied the sensitivity change. No clue what the fuck any of it means.
Sometimes when I get frustrated reading Opus/Fable 5+ output I pause my rage out briefly to wonder if it's because I'm just too dumb for the model or if the model is just terrible at English. I'm not sure that telling it to "try explaining that again, simply and briefly" is helping my ego.
"If the crashes stop, the factory overclock is marginal; run a small negative offset."
This looks like it's saying: "If the crashes stop then we know the factory overclock is marginal." (This makes no sense.)
What it's trying to say is: "If the crashes stop then we can run a small negative offset, because the factory overlock is marginal."
What I would write: "If the crashes stop, we can avoid crashes by underclocking slightly. The speed difference between that and factory clock is marginal."
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"Caveats, stated plainly" You should have seen the discussion of this on the Schneier blog a few days ago. Someone had their agent check the solution, presumably it emailed a librarian to check that it was correct for the original edition. Then their comments read like "The BL/EEBO witness lacks it, so the discrepancy is copy-specific, not a disproof of the cipher." and "A complete 285-coordinate physical replication…
Astra told me yesterday: > The run baseline was captured without a physical MAC; the current device is not durably bound to it. > Engineering mode confirmation is the ESPHome component read-back; the LD2410 UART acknowledgement is not observed, so this is not proof the radar itself applied the sensitivity change. No clue what the fuck any of it means.
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That seems a like the result for a lot of AI solves. It solves it due to persistence, on a problem that hasn’t been important enough for a human to invest significant time into.
That's what Terence Tao said in one of his recent videos about it. That what the LLMs can provide is scale that humans can't. The example he provided is checking many possible solutions in a short amount of time because they can review all the previous literature and, for example, rule out ones with errors. He was realistic and practical about it and said that the tools working this way can be very helpful for a huma…
In the same way if you tell an LLM to go and find an unsolved cipher it can solve, of course it finds the one it can solve out of the set of all possible ciphers. Of course it finds one that uses a one time pad that is public and referenced nearby in the text.
It's the same trick used by those people who film themselves throwing a basketball backwards into the hoop. You do it enough times and don't show the misses. You pick the best one to show. It makes it look like you're a basketball genius when you aren't.
It is of course, still a cool trick. Those videos are fun to watch, and so is an LLM solving a cipher. It is absolutely incredible to live in the timeline where you can tell a computer in plain language to go and find a puzzle on the internet and solve it, and it does exactly that. It's truly a mind boggling miracle.
The first principle is that we must not fool ourself, and ourselves are the easiest people to fool. (Ht Feynman)