alt Hacker News> This brings us to what seems like a contradiction. LLMs are bad at playing games. Yet at the same time, they’re improving rapidly at coding, a skill set that can be used to create a game. How do these facts fit together?
> Togelius: It’s super weird.
...No, it's really not.
They're language models. Code is a language. "Playing a game well" is not. One can, hypothetically, encode game inputs in such a way that it seems kinda-sorta like a language, but it has none of the same kinds of structures that languages—both human and programming—do.
The only way one can think this is strange is if one thinks of LLMs' ability to code rudimentary games as being due to a deeper understanding of games, rather than due to game code being well-represented in their training data.
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Yea it’s wild watching so many smart people convince themselves that LLMs are general purpose AIs. Don’t get me wrong they are incredibly powerful tools. However being surprised that text models cannot play video games particularly well is like being surprised weather models cannot.
Yet LLMs can play chess and have a "mental" representation of the chessboard.
If LLMs get better but do not progress at playing games when not specifically trained on it it seems to point to a generalisation failure, a limitation that would prevent LLMs to ever achieve AGI, I do not know if that is weird but it seems that for now nobody really knows if they can achieve AGI or not. Perhaps some emergent behavior will arise after more scaling.
To me it's only totally unsurprising if you are 100% certain that LLMs will never reach AGI (like LeCun thinks for example).