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Comment by kbyatnal | Hacker News Reader

I saw something along these lines on Twitter and think it's very true:

the right way to think about ChatGPT is not "what can I do if I had API access to an intelligent person?" which is how most are treating it (because it's not that smart), but rather "what can I do with API access to 1000 people of medium intelligence?"

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Well, exactly - the disruption is closely analogous to what happened with a lot of crafting trades during the first Industrial Revolution. Early weaving mills (etc) were okay at weaving, but certainly not better than the very best weavers - but they didn't need to be, as they just needed to do well enough to displace enough workers to "pay for themselves". (And, as a reaction, the Luddites formed to protest about the destruction of their industry wholesale.) And, even now, you can still buy - very expensive! - hand-woven items, but there's not really an industry in it any more, and a lot of crafting skills have become mostly hobbies. The current disruption in creative trades from the various AI generative models is the same for artistic etc creativity - and will probably have the same societal tradeoffs. [IMO, the copyright argument is actually distracting here from the actual problem people should be arguing about - the conversion of more types of human production into capital.]

I think people here on HN are super biased IQ wise.

If you or some random person on the street can list 20 similar concepts to Heiddigers "dasein" from similar philosphers, or apply Pierre Bordious forms of capital to multiple fictitious people (or even animals lol) outline the history of calculus and explain core coding concept, music theory -etcetera ad infinitum - all very pedagogically and "pretty" accurately i'm impressed.

To me it's not "pretty average", but like at person with 300+ bachelor level degrees thats's way overconfident, but a great starting point.

This kind of intelligence is in the absolute top percentiles. If it can reach "senior" lvl intelligence and be a bit more self doubting remains to be seen though.

I have similar opinion! Many people are not taking into account the fact that this learning technique significantly outscales the average in terms of numbers. While the very best may not be affected, the fact that it generates results that are on average or slightly below average is concerning. Additionally, its ability to imagine and contextually change random garbage means that there is already room for improvement. Given the compute and resources available to top labs, they will likely be able to add more context, which could exacerbate the problem.

To my knowledge, no other system has been able to retain context, imagine garbage, and refine it based on the given input context. For details, it can imagine a game, change the premise of the game and craft stories or lines based on the new context. It doesn't even have to be perfect. It is already capable of doing 60% job. Wait till it reaches 80%.

Now you do not have one skill, but you can have multitude of average looking skill on top of your own craft. Further, this thing provides a good entry point to dive into research and investigate. Just like how stable diffusion sparked curiosity on art culture, technicalities, photography, this can do it but on wider context and problems. Therefore, it is not the matter of will it, it is just the matter of when?

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