garymarcus

Why it won’t reach AGI, ever, and how it might destroy the economy,

Deep analysis by a leading skeptic.

If you think AI is “smart” or “PhD level” or that it “has an IQ of 120”, take five minutes to read my latest newsletter (link below), as I challenge ChatGPT to the incredibly demanding task of drawing a map of major port cities with above average income.

The results aren’t pretty. 0/5, no two maps alike.

“Smart” means understanding abstract concepts and combining them well, not just retrieving and analogizing in shoddy ways.

No way could a system this is wonky actually get a PhD in geography. Or economics. Or much of anything else.

If you don’t understand why LLMs hallucinate so often, and most people don’t, read this.

For those wanting some background, rather than just wanting to vent:

1. Here is evaluation of my recent predictions: https://garymarcus.substack.com/p/25-ai-predictions-for-2025...

2. Here is annotated evaluation, slightly dated, considering almost line by line, of the original Deep Learning is Hitting a Wall paper: https://garymarcus.substack.com/p/two-years-later-deep-learn...

Ask yourself how much has really changed in the intervening year?

exactly. and the counterarguments boil down to “na na” and hope.

god these arguments are empty, personal and without any substance whatsoever

Show me the goalposts I have moved, with actual quotes to prove it. nobody ever has when I have asked.

Aso consider eg the bets I have made with Miles Brundage (and offered to Musk(, with money where I have backed up my views.

good summary of predictions i made - mostly correct – is here: https://open.substack.com/pub/garymarcus/p/25-ai-predictions...

you obviously never actually read the paper; you should.

because i correct foresaw quite a lot. you should actually read the paper.

100% - there has not been any solid theoretical argument whatsoever (beyond some confusions about scaling that we can now see were incorrect).

the common thread is rationality and an aversion to disinformation.

easier said than done, in the general case. the work I describe in the essay does it in a narrow case, but see also https://garymarcus.substack.com/p/getting-gpt-to-work-with-e...

You are a fool, if you think it is a “a mostly tribal distinction”. You would have said same about alchemy vs chemistry, or genes as proteins vs genes as DNA. In science, the details matter.

How models like GPT-3 could accelerate the production of misinformation, and what we might do about it

Wondering what @MetaAI's legit impressive new AI Cicero might mean for the next few years in AI?

Hint: It’s not all about scaling.

5 reasons why many are skeptical

in fact I wrote a whole article about this (linked in this essay, called Horse Rides Astronaut) and linked an example therein.

so much ad hominem in these comments, relatively little substance. (eg “notorious goal post move, without a single example of something i actually said and changed my mind on)

every time i ask someone to name a goal post that i have moved, they back down.

i have been pretty damn consistent since me 2001 book.

i would be glad to do if given proper access, but had into very limited indirect access.

what goalposts changed? i pointed out same limits in 2001, 2012, 2018, 2019, 2020.

please actually read my work and please don’t make stuff up.

How quickly they forget. 45 minutes after the DALL-E n release, Sam Altmann tweeted “AGI is gonna get wild”; Greg Brockman posted multiple tweets around the idea of AGI and walls broken. That invites a critical analysis.

Ad hominem against me won’t remedy the limitations that we and others have observed.

exactly - the article is a call to arms to do that difficult work.