Gary Marcus

Rank 19 of 47

Score 64

@emollick the problem is we need R into approaches that aren’t LLMs, because LLMs have many intrinsic problems.

it’s those problems that mean there will be an eventual bust.

3/31/2024, 4:42:50 PM

In reply to:

Ethan Mollick

@emollick

469d

R typically comes before D.

We have better insight in LLM timing than in most industries. It is over a year to go from startup to GPT-4 class model even with infinite money (Musk, Google).

I don’t think that this tells us anything about whether we are in a bubble or a boom.

/MachineLearning

@slashML

469d

WSJ: The AI industry spent 17x more on Nvidia chips than it brought in in revenue https://www.reddit.com/r/Machine…

The statement is part of a conversation about the AI industry's investment in technology and its potential overvaluation, which is a topic of public interest. The tone is cautionary, the intent is to express concern over the current focus on a specific AI technology, and the content suggests a need for diversification in research to avoid a market bust.

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