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by therein7 hours ago |
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upvoteby root_axis6 hours ago|
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It would absolutely be a phase change in practical utility, but it still wouldn't be "super intelligence".
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upvoteby esperent6 hours ago|
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I think that just like there's tons of different kind of "superheroes" and nobody disputes whether they're genuinely deserving of the name or not, there could be many valid types of super intelligence.

If something is roughly as intelligent as a normal human expert in a given area, but 100 times faster, that would be a valid example of super intelligence.

I'm sure that by some definitions like this we've already discovered narrow super intelligence.

For example - breadth of knowledge. Is knowledge a kind of intelligence? If so then current agents absolutely have a breadth of knowledge which is superhuman.

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upvoteby lifeisloving3 hours ago|
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Or you'd just be making the same mistakes experts do but at a 100x clip.

Tortious really does win the race, and there is no such thing as a free lunch.

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upvoteby imtringued2 hours ago|
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It would be a super intelligence in terms of thinking speed, not necessarily be super intelligent, mind you.
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upvoteby lifeisloving3 hours ago|
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More like lighting a fire in your codebase at the speed of light.

Nobody needs this, and the quality of models they're deploying, or all llms for that matter, require heavy human review (if you care at all about maintainability).

One developer can barely keep up with the daily output of multiple llm sessions writing code at 50 tps.

Im convinced anyone confidently thinking 2k tps is a no brainer is probably not concerned about the quality of their work (many such cases).

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upvoteby Tade02 hours ago|
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Occasionally it takes me at most 10 minutes to figure out that a solution the LLM took an hour to churn out is not up to par and I need to throw it away entirely.

There are diminishing returns, but half of the rate you mentioned would already help me keep focus.

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upvoteby imtringued2 hours ago|
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At those token rates you could treat the LLM as a compiler and rebuild your software from scratch every week. That would mean the end for AI slop because people who spend the effort to build a process that creates high quality software from scratch can take full advantage of the one shot performance of an LLM without having to release the process itself.
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upvoteby lifeisloving11 minutes ago|
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Youre completely missing my argument. Speed is not the bottleneck, its the review burden.

You need human review when working on anything not table stakes. You cannot write shitty code for an avionics package on an airplane under the assumption that if we encounter bugs, its no big deal because we can rewrite it super fast..

It seems like all these bullish takes on AI are coming from people who think all software runs in a browser, and simply exists to take stripe payments or serve ads. Most software is actually very high stakes and lives depend on it and have high compliance burdens.

Just because it can "one shot" (which actually means 90 tools calls and a whole lot of brute forcing against tests/linter/compiler, and possibly reward hacking) to something that runs, does not mean it will continue to run well.

People treat llm made software like disposable code. You're the only one using it, typically on a single machine with no real world multi-user testing, but for some reason we derive from the fact it worked well the 3 times we used it, on a single machine with a single user that it is evidence of llm solving programming. Its bogus.

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upvoteby alchemist1e97 hours ago|
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This is why I think there will be selective pressure for fast tools. It’s like an evolutionary process and fast tools will be preferred and created. It’s already happening and also why I think computer use is a dead end.
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