Comment by logisticseh | Hacker News Reader

Comment by logisticseh | Hacker News Reader

Parent Full thread

I agree. There are two different sets:

1. Actual deep learning researchers, actively doing research. I rarely hear nonsense about impending AGI or mass technological unemployment from these folks. They might express tepid concern about the ethics of various applications of deep learning and tepidly point out that some technological disruption in employment is possible, but in both cases with an emphasis on tepid. And who, if anything, tend to under-estimate progress. (Self-driving is still very far off and also much further along than I thought it would be 9 years ago. I turned down jobs at self-driving cos because I didn't believe they would make enough progress to even have an ADAS product, but I was clearly wrong and if I could do it over I'd work on self-driving from 2013 onwards even though L5 is still a long way out.)

2. Deep learning fan-boys, for lack of a better term. The rationalist community in particular has a sub-community of tech-adjacent folks who aren't publishing in major conferences every cycle or running research labs but do talk a lot about AGI/UBI.

IMO it's not that dissimilar from climate science or even in the extreme the existence of aliens. Scientists with a lot of real expertise will sort of tepidly talk you through the full complexity. And then some "true believers" who aren't actually expert will sort of run to the extremes of anti-natalism or aliens among us. If that makes sense.

> IMO it's not that dissimilar from climate science or even in the extreme the existence of aliens.

Those may be similar to the contrasting attitudes regarding AI, but the analogy I first thought of for what you describe is the topic of cryptocurrency.

1. On the one hand, most people who have deep knowledge and experience of software development and databases, or professional experience of financial markets and banking, tend to be extremely sceptical, critical, or outright dismissive of the whole idea of cryptocurrency.

2. On the other, people who are technology "enthusiasts" and have some limited or self-taught programming skills, or those who have some moderate knowledge of the basics of finance and investments (often motivated by personal ambition), are much more likely to be cryptocurrency fan-boys.

This is just the hype cycle in action. New technology comes out and its fanboys and shallower (from a usecase perspective) users are adamant it'll change everything everywhere. Deep practitioners understand limitations because they're involved in the work. Eventually the fanboys are proved wrong or gravitate to the next hype and everyone else finds the place for a new technology.

A good example is Go some years ago and these days Rust. But it's the same thing, just the hype cycle at work.

I guess John Carmack falls somewhere in between but as a complete layperson when he said he gave AGI by 2030 a 50 percent chance, that at least indicated to me that some really smart people think there is a chance.

1. He predicts "signs of life" by 2030, which is a (probably intentionally) vague statement.

2. He raised $20MM for an AI startup, which is fine and well but also makes him not entirely disincentivized from hype.

3. I wouldn't characterize him as someone in the trenches of deep learning.

More of a meta point: technical depth in more than a few things is impossible in a human lifespan, and just a bit harder once you become a "somebody" since a portion of your life becomes consumed by the fact that you're a "somebody". You end up doing things like raising VC money and starting companies with bold ambitions. Its own time sink.

I had this realization when I had a conversation with Lamport about a niche topic in distributed systems and he expressed a position that was just wrong. It was a minor point that didn't really matter much at all, but he was pretty confident in a conjecture I knew was wrong. To be clear, the fact that no one can be an expert on everything -- even everything within a subfield of CS -- doesn't detract from the fact that geniuses exist. Someone can "forget more than you know" and also not know something that you know. Life is just sadly very short.

Thats true, he seems to have flopped on the rockets startup too, although you might argue AI is still much closer to his wheelhouse than aerospace so it make more sense. Before hearing that I had some vague idea that the most AI experts timeline for AI was significantly longer and some never.

Reply on news.ycombinator.com