Putting hype and usefulness on the same axis is a common mistake. It helps to think of AI as a discovery, a feat of science we now are unlocking using experime

Putting hype and usefulness on the same axis is a common mistake. It helps to think of AI as a discovery, a feat of science we now are unlocking using experimentation rather than a traditional engineering product. Once you make that shift, the expectations we project on it start being silly. It’s marginally useful as a search engine but discussed like one primarily because Microsoft used they framing as the most business model advantageous they saw hurting google - not because it’s a particularly good fit for that usecase. Once you understand it as a discovery you understand how silly much of the framing and opinionation really is - the “flaws” usually being projection of expectations used by the companies trying to monetize it. Just because the technology isn’t fitting their business model framing doesn’t mean it can’t be phenomenally transformative to society and wreck a whole bunch of stuff. Scientific discovery this year has been breathtaking on every dimension - not even taking hardware into account. And we don’t have a sense of where it ends beyond - not going on forever and not stopping tomorrow. Most people arguing about the technology is from a perspective of todays limitations in regards to todays usecases. And that’s not a good way to approach the problem.