We’ve learned to make “machines that can mindlessly generate text. But we haven’t learned how to stop imagining the mind behind it.”
We’ve learned to make “machines that can mindlessly generate text. But we haven’t learned how to stop imagining the mind behind it.”
This is an incredibly complicated question. On a very basic level, the very physics of how decisions are made differ from a binary/coded system than how brains work (you don’t have 0/1 gates, you can have things encoded inbetween 0 and 1). On a slightly higher level, concepts like working memory don’t exist in LLMs (although they’ve started to include something akin to memory), LLMs hallucinate things because they don’t have a method to fact-check, so to speak, and there’s a variety of other mental concepts that aren’t employed by LLMs. On a much higher level there’s questions of what cognition is, and again many of these concepts just cannot be applied to LLMs in their current state.
Ultimately the question of “how our brains work” can be separated into many, many different areas. A good example of this is how two people can reach different conclusions given the same pieces of information based on their background, experiences, genetics, and so forth, and this is a reflection of diversity that affects everything from the architectural (what the physical structure of the brain looks like) to conceptual (how those might interact or what knowledge might inform differing outcomes).
Thank you for the answer.
Any suggestions on further reading?
I wish I had specific targeted reading, but I happen to have a degree in neurobiology and I’m a data scientist so I just happen to have accrued a lot of knowledge over the years in exactly the two fields being listed here