36 ms·

> I've had LLMs do that correctly up to far larger numbers than I've multiplied by hand. but given enough time you can multiply any numbers, while LLM has fund

> I've had LLMs do that correctly up to far larger numbers than I've multiplied by hand. but given enough time you can multiply any numbers, while LLM has fundamental inability to learn algorithm. > I've also had LLMs execute algorithms most people wouldn't even understand. E.g. converting between NFAs and DFAs this is a not good quality discussion, such claims should be expressed in the form of some research results: describing what you do exactly, how data has been obtained, verified for correctness, what is complexity of your NFAs etc, otherwise I personally have hard time to judge how indicative your claim.

speedgoose 3y ago
ChatGPT knows how to write Python code, run it, and use the results. It can also use WolframAlpha. It’s not a pure LLM solution but it’s good enough to multiply numbers. Have you tried it?
- vidarh 3y ago
  ChatGPT knows how to multiply step by step without either of those, but like a human, who'll be annoyed and usually sloppy if you ask them to do things step by step instead of taking shortcuts, you increasingly need to push it to get it to do so with care. The irony of these objections is that people speak out of a "but we learned to do that at school" way of thinking, often on the basis of above average skills, rather than considering that while most people maybe could (I'm not convinced), most people won't do it step by step unless you really goad them into it and pay attention that they don't skip or gloss over steps.
- riku_iki 3y ago
  The question is inability of ChatGPT to do logical reasoning. Multiplying numbers is a simple test to prove this. The same with coding: it can produce code for tasks where something similar was in training dataset, but if you ask to do completely unknown problem - it will fail.
vidarh 3y ago
> but given enough time you can multiply any numbers, while LLM has fundamental inability to learn algorithm. GPT4 at least knows the algorithms - many alternative version - and will follow them. What it won't do, just like most humans, is take the time to go over it and review each step for possible errors without further prompting and inducement. Yes, humans could. Most humans don't, without outside pressure. With pressure applied and LLM will too. Again, this is an example of how people overestimate how humans do in the same condition. I would suggest you look up some studies on numeracy - sure, most people can learn if put through enough pressure, and good humans would do well against currebt LLMs, but average adult human numeracy is shockingly poor. Consider if you would question people's ability to reason in general if you find a few examples of humans who do poorly at it. It is fascinating when people compare LLMs this way against some platonic ideal of a human without considering that many of the failures of LLMs to stick to the prompt occurs in humans too. E.g. when you argue a human could do something with enough time, you leave out the effort you'd need to expend to convince said human to do so, and follow your instructions carefully enough. Yes, there are still plenty of conditions where humans can beat LLMs given sufficient inducement, and even in many cases easily. But that is a very different subject. > this is a not good quality discussion, such claims should be expressed in the form of some research results: describing what you do exactly, how data has been obtained, verified for correctness, what is complexity of your NFAs etc, otherwise I personally have hard time to judge how indicative your claim I'll happily do that if you do the same for your unsubstantiated claims first. Otherwise you can simply actually try to ask ChatGPT about these things yourself, and then try to ask a random person about them.
- riku_iki 3y ago
  > With pressure applied and LLM will too. unless it is fundamentally incapable.

speedgoose 3y ago

ChatGPT knows how to write Python code, run it, and use the results. It can also use WolframAlpha. It’s not a pure LLM solution but it’s good enough to multiply numbers. Have you tried it?

vidarh 3y ago
ChatGPT knows how to multiply step by step without either of those, but like a human, who'll be annoyed and usually sloppy if you ask them to do things step by step instead of taking shortcuts, you increasingly need to push it to get it to do so with care. The irony of these objections is that people speak out of a "but we learned to do that at school" way of thinking, often on the basis of above average skills, rather than considering that while most people maybe could (I'm not convinced), most people won't do it step by step unless you really goad them into it and pay attention that they don't skip or gloss over steps.
riku_iki 3y ago
The question is inability of ChatGPT to do logical reasoning. Multiplying numbers is a simple test to prove this. The same with coding: it can produce code for tasks where something similar was in training dataset, but if you ask to do completely unknown problem - it will fail.

vidarh 3y ago

> but given enough time you can multiply any numbers, while LLM has fundamental inability to learn algorithm. GPT4 at least knows the algorithms - many alternative version - and will follow them. What it won't do, just like most humans, is take the time to go over it and review each step for possible errors without further prompting and inducement. Yes, humans could. Most humans don't, without outside pressure. With pressure applied and LLM will too. Again, this is an example of how people overestimate how humans do in the same condition. I would suggest you look up some studies on numeracy - sure, most people can learn if put through enough pressure, and good humans would do well against currebt LLMs, but average adult human numeracy is shockingly poor. Consider if you would question people's ability to reason in general if you find a few examples of humans who do poorly at it. It is fascinating when people compare LLMs this way against some platonic ideal of a human without considering that many of the failures of LLMs to stick to the prompt occurs in humans too. E.g. when you argue a human could do something with enough time, you leave out the effort you'd need to expend to convince said human to do so, and follow your instructions carefully enough. Yes, there are still plenty of conditions where humans can beat LLMs given sufficient inducement, and even in many cases easily. But that is a very different subject. > this is a not good quality discussion, such claims should be expressed in the form of some research results: describing what you do exactly, how data has been obtained, verified for correctness, what is complexity of your NFAs etc, otherwise I personally have hard time to judge how indicative your claim I'll happily do that if you do the same for your unsubstantiated claims first. Otherwise you can simply actually try to ask ChatGPT about these things yourself, and then try to ask a random person about them.

riku_iki 3y ago
> With pressure applied and LLM will too. unless it is fundamentally incapable.