343 | Tom Griffiths on The Laws of Thought
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Hello everyone and welcome to the Mindscape Podcast. I'm your host, Sean Carroll. I've always thought that one of the interesting aspects of modern approaches to AI, large language models, other connectionist things, is that very often, or at least in their natural state, an LLM is not good at arithmetic. It's not good at adding numbers together. You can
Augment the program so that they're very good. You can give basically an LLM access to a calculator. It's exactly like human beings. They're not very good at arithmetic in some sense, but if you have a calculator, they can do it. But in their natural state, LLMs make mistakes about simple problems adding medium-sized numbers together.
Other kinds of number-based problems they're not very good at. counting the number of Rs in the word strawberry. Random numbers. If you asked an LLM to generate a million random integers between zero and a hundred and then made a plot of the frequencies, it would not look uniform. Of course, these are all things that human beings are also intrinsically not very good at, but part of you thinks
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