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Oftentimes, plausible code is good enough, hence why people keep using AI to generate code. This is a distinction without a difference.
by satvikpendem 8mo ago
Oftentimes, plausible code is good enough, hence why people keep using AI to generate code. This is a distinction without a difference.
- andai 8mo agoThere appears to be a similar approach in UX... plausible user experience is close enough.
- satvikpendem 8mo agoYes, especially because in UX there is no "correct" approach to it, it's all relative.
- bluetomcat 8mo agoNo. Plausible code is syntactically-correct BS disguised as a solution, hiding a countless amount of weird semantic behaviours, invariants and edge cases. It doesn't reflect a natural and common-sense thought process that a human may follow. It's a jumble of badly-joined patterns with no integral sense of how they fit together in the larger conceptual picture.
- satvikpendem 8mo agoWhy do people keep insisting that LLMs don't follow a chain of reasoning process? Using the latest LLMs you can see exactly what they "think" and see the resultant output. Plausible code does not mean random code as you seem to imply, it means...code that could work for this particular situation.
- tovej 8mo agoBecause they don't. The chain-of-reasoning feature is really just a way to get the LLM to prompt more. The fact that it generates these "thinking" steps does not mean it is using them for reasoning. It's most useful effect is making it seem to a human that there is a reasoning process.
- satvikpendem 8mo agoHow would you determine humans have reasoning then, in a way that LLMs do not?
- andai 8mo agoOr — here's a fun one — subjective experience.
- satvikpendem 8mo agoThey haven't replied to my comment but have to yours, so I can only assume they actually cannot point out the difference, which makes sense as the philosophy of mind is a very old subject and there is no way a threaded conversation like this would produce any concrete answers.
- tovej 8mo agoThis one is even easier. LLMs record objective data about n-gram distribution, there is no room for any "subjective state" in their working set. Or another way: an LLM will respond the same way if you wait for one second or a decade between prompts. The only way it is interacted with is through a stream of tokens. There is exactly one stream at all times, and each time the stream is input again, it is barely different from the previous input. The LLM does not behave differently depending on the contents of the stream. It may produce the exact same token for two different streams. It may also encounter the same stream twice, and will act the same in both cases. If it were a "subject" "experiencing" say, a discussion, it would use its pasts "experience". But it does not.
- tovej 8mo agoEasy, humans can synthesize new facts using logic and context. And the conclusions can be checked against the real world to check that the reasoning was correct. Or another way: reasoning is a socially constructed concept, developed by humans. Humans therefore have defined reasoning, and must therefore know how to reason. Or a third way: I experience reasoning, you experience reasoning. I am currently reasoning. You are currently reasoning. I am human, as are you. Therefore humans reason.
- topaz0 8mo ago2 seconds to insert 100 rows in an empty database table is not "good enough" if you are doing anything that is worth doing.
- satvikpendem 8mo agoWho said anything about this? I never did.
- topaz0 8mo agoTfa did