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LLMs can clearly solve problems that computers up to now couldn't. They can't solve all problems and this should definitely be a cautionary note to anyone who w

LLMs can clearly solve problems that computers up to now couldn't. They can't solve all problems and this should definitely be a cautionary note to anyone who wants to use them as an artificial general intelligence, but this take seems no different to someone looking at a punchcard computer and going, it can't even recognize typos or categorize images, what good is this? We've already had human computers who can do everything these can do, and can recognize images and notice typos

evilduck 2y ago
Also humans would revert to explicitly using an algorithm and external storage like a sheet of paper with tally marks or a spreadsheet or even a computer program if you scale the question up to a full sheet of text or a whole book or a collection of books (we probably do it at a single word size too, but it's more intuitive than explicit behavior for most folks when the count sum is around 8 or less). LLMs can't effectively execute algorithms similarly in their context, nor can they memorize new data or facts it was given without providing it tools like function calling or embeddings. If you give LLMs tool calling and storage mechanisms then counting letters in words becomes pretty damn reliable.
jrflowers 2y ago
> going, it can't even recognize typos or categorize images, what good is this? No one said that LLMs aren’t good for anything. I pointed out — in response to another poster downplaying mention of a well-known and undisputed limitation that LLMs often have — that it is valid to consider these well-known and undisputed limitations if one is considering using them for anything other than a toy. It is downright silly to discourage discussion of well-known and undisputed limitations! The only reason for that can only be entirely emotional as there is genuinely nothing tangible to be gained by being steadfast in silence about a fact that isn’t up for debate.
- space_fountain 2y ago
  I think somehow there were a series of miscommunications. This kind of sub token manipulation task is hard for an LLM for somewhat predictable reasons. Knowing those limitations are important, but don't come up too often in practical circumstances. Outside of contrived examples counting the number of letters in a long word is pretty rare. I took your response to be arguing against a message I'd read to be saying something like the above. Especially when you basically seemed to be saying that limitations like this are important in everything but toy applications. It's uninteresting because it doesn't point towards larger problems with their use in the kind of application they're being used for and are intended for unlike prompts that point to weakness in logic or propensity to hallucinate.

evilduck 2y ago

Also humans would revert to explicitly using an algorithm and external storage like a sheet of paper with tally marks or a spreadsheet or even a computer program if you scale the question up to a full sheet of text or a whole book or a collection of books (we probably do it at a single word size too, but it's more intuitive than explicit behavior for most folks when the count sum is around 8 or less). LLMs can't effectively execute algorithms similarly in their context, nor can they memorize new data or facts it was given without providing it tools like function calling or embeddings. If you give LLMs tool calling and storage mechanisms then counting letters in words becomes pretty damn reliable.

jrflowers 2y ago

> going, it can't even recognize typos or categorize images, what good is this? No one said that LLMs aren’t good for anything. I pointed out — in response to another poster downplaying mention of a well-known and undisputed limitation that LLMs often have — that it is valid to consider these well-known and undisputed limitations if one is considering using them for anything other than a toy. It is downright silly to discourage discussion of well-known and undisputed limitations! The only reason for that can only be entirely emotional as there is genuinely nothing tangible to be gained by being steadfast in silence about a fact that isn’t up for debate.

space_fountain 2y ago
I think somehow there were a series of miscommunications. This kind of sub token manipulation task is hard for an LLM for somewhat predictable reasons. Knowing those limitations are important, but don't come up too often in practical circumstances. Outside of contrived examples counting the number of letters in a long word is pretty rare. I took your response to be arguing against a message I'd read to be saying something like the above. Especially when you basically seemed to be saying that limitations like this are important in everything but toy applications. It's uninteresting because it doesn't point towards larger problems with their use in the kind of application they're being used for and are intended for unlike prompts that point to weakness in logic or propensity to hallucinate.