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Comment by sandspar | Hacker News Reader

I just don't understand how people can see "100 million signups in a week" and immediately dismiss it. We're not talking about fidget spinners. I don't get why this sentiment is so common here on HackerNews. It's become a running joke in other online spaces, "HackerNews commenters keep saying that AI is a nothingburger." It's just a groupthink thing I guess, a kneejerk response.

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I assume, when people dismiss it, they are not looking at it through the business lens and the 100m user signups KPI, but they are dismissing it on technical grounds, as an LLM is just a very big statistical database which seems incapable of solving problems beyond (impressive looking) text/image/video generation.

Makes sense. Although I think that's an error. TikTok is "just" a video sharing site. Joe Rogan is "just" a podcaster. Dumb things that affect lots of people are important.

> We're not talking about fidget spinners.

We're talking about Hitler memes instead? I don't understand your feigned outrage.

The actual valid commercial use case for generative images hasn't been found yet. (No, making blog spam prettier is not a good use case.)

You're right, nothing has value unless someone figures out how to make money with it. Except OpenAI, apparently, because the fact that people buy ChatGPT to make images doesn't seem to count as a commercial use case.

OpenAI is not profitable and we don't know if it ever will be.

Have we shifted the goalposts from "something people will pay for" to "needs to be profitable even with massive R&D" then?

OpenAI is not "something people will pay for" at the moment though.

Except lots of people are paying for it. I'll refer you to the other post on the front page for the calculation that OpenAI would have to get just an extra $10/yr from their users to break even.

Your response reminds me of that joke about selling a dollar bill for ninety cents.

Your response makes me think we have different definitions for profitability.

OpenAI is not profitable because it is spending resources into moving forward and training new models and creating new tools.

Everything Everywhere All At Once won a bunch of Oscars. They used generative AI tools for some of their post-production work (achieved by a tiny team), for example to help clean up the backgrounds in the scene with the silent dialog between the two rocks.

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