Okay but it is probably not going to be a tool that will be reliable or work as expected for too long depending on how complex it is, how easily it can be understood, and how it can handle updates to libraries, etc. that it is using.

Also, what is our trust with this “tool”? E.g. this is to be used in a brain surgery that you’ll undergo, would you still be fine with using something generated by AI?

Earlier you couldn’t even read something it generated, but we’ll trust a “tool” it created because we believe it works? Why do we believe it will work? Because a computer created it? That’s our own bias towards computing that we assume that it is impartial but this is a probabilistic model trained on data that is just as biased as we are.

I cannot imagine that you have not witnessed these models creating false information that you were able to identify. Understanding their failure on basic understandings, how then could we trust it with engineering tasks? Just because “it works”? What does that mean and how can we be certain? QA perhaps but ask any engineer here if companies are giving a single shit about QA while they’re making them shove out so much slop, and the answer is going to be disappointing.

I don’t think we should trust these things even if we’re not developers. There isn’t anyone to hold accountable if (and when) things go wrong with their outputs.

All I have seen AI be extremely good at is deceiving people, and that is my true concern with generative technologies. Then I must ask, if we know that its only effective use case is deception, why then should I trust ANY tool it created?

Maybe the stakes are quite low, maybe it is just a video player that you use to watch your Sword and Sandal flicks. Ok sure, but maybe someone uses that same video player for an exoscope and the data it is presenting to your neurosurgeon is incorrect causing them to perform an action they otherwise would have not done if provided with the correct information.

We should not be so laissez-faire with this technology.

Driving A to B takes 5 hours, if we get five drivers will we arrive in one hour or five hours? In research there are many steps like this (in the sense that the time is fixed and independent to the number of researchers or even how much better a researcher can be compared to others), adding in something that does not sleep nor eat isn't going to make the process more efficient.

I remember when I was an intern and my job was to incubate eggs and then inject the chicken embryo with a nanoparticle solution to then look under a microscope. In any case incubating the eggs and injecting the solution wasn't limited by my need to sleep. Additionally our biggest bottleneck was the FDA to get this process approved, not the fact that our interns required sleep to function.

>It doesn't need to dissect an animal if it has a perfect model of it that it can simulate. All potential genetic variations, all interactions between biological/chemical processes inside it, etc.

Emphasis on perfection, easier said than done. Some how this model was able to simulate millions of years of evolution so it could predict vestigial organs of unidentified species? We inherently cannot model how a pendulum with three arms can swing but somehow this AI figured out how to simulate evolution millions of years ago with unidentified species in the Amazon and can tell you all of its organs before anyone can check with 100% certainty?

I feel like these AI doomers/optimists are going to be in a shock when they find out that (unfortunately) John Locke was right about empiricism, and that there is a reason we use experiments and evidence to figure out new information. Simulations are ultimately not enough for every single field.