Many people are surprised at the advancement of AI, as they thought that generative fields (art, poetry) would be hardest for AI to excel at, whereas “simple” tasks like driving would be easier.
What we are actually seeing is that AI is useful to the degree that being wrong is okay. AI’s mess up, and that’s okay with poetry because a human can quickly read the poems and pick out the good ones. It’s not okay when driving.
It kind of feels that ChatGPT is "just" missing some kind of adversarial self clone that can talk back to itself and spot errors. Most times when I spot an error and mention it it seems that it already had some notion of this problem in the model.
Analysis based on introspection is dangerous, but it definitely feels like I have such an adversarial model. A lot of the time my brain tosses out five or ten ideas before I hit on one without obvious flaws.
It's usually serial, so it's not clear to me that this is using different hardware than I use to generate the ideas in the first place. We might be surprisingly close to human-level AI.
> Most times when I spot an error and mention it it seems that it already had some notion of this problem in the model.
By this do you mean that it correctly incorporated what you said and convincingly indicated that it understood the mistake? Because that's not the same thing as it having the truth latently encoded in the model—it just means that it knows how people respond when someone corrects them (which is usually to say "oh, yeah, that's what I meant").
I talked to it about the Turing completeness of PowerPoint. Initially it thought it was impossible, then possible with some scripting language, and then with some prodding I got it to believe you can do it with hyperlinks and animations. Then it gave me an example that I was unable to verify, but was definitely in the ballpark of the actual solution.
For humans, this is science. It's hard, time-consuming, often expensive and limited, involves ethics and consent, and gets a lot of wrong answers anyway.
So I guess we need to get to the point where you give an AI a prompt without a known answer, and instead of confidently spewing bullshit, it can propose a research study, get it funded, find subjects, and complete the study.
Of course, there are easy forms of "science." I just asked it "Is it cloudy in Dallas?" It answered:
It can be cloudy in Dallas. The city experiences both sunny and cloudy days throughout the year.
That is true, but not an answer. It is cloudy and I can conduct the very simple experiment of looking at the sky to get that answer.
However is this not a known limitation with how it's currently setup? It has no way of knowing what the current weather in Dallas is simply because it has no way of finding out (eg it could query a weather website, but it has no internet browsing yet)... to be an accurate comparison you'd need to repeat your simple experiment blindfolded.
How would you make it navigate an api? We don't even know how to make it perform basic arithmetic's correctly, it is an enormous black box model so we can't just inject code into.
Or automate the process even further; let the AI run the code, feed back the output (including errors), and ask "Does this output look correct? If not, please refine the code to fix any problems." Repeat until the AI says "LGTM".
Or tell the AI to write the unit tests itself, and let it run those to check its work. After all, that's how humans write code. We aren't so great at writing bug-free code on our first try without testing it either.
It's so weird to me that people pretend that Waymo and Cruise don't exist. And with the recent wider release of Tesla's "FSD", if it wasn't handling 99% of it properly you would hear about collisions all over the place. And I know there have been some here and there before. But this is a massive deployment of AI. If it doesn't work there are going to be a LOT of crashes. But there are not. Because it works.
You think if it was failing any significant amount to drive in a safe way, with this wide deployment, there wouldn't be a lot of crashes? Having an AI drive is the best way to make the driver zone out. At this point, it usually fails by going into intersections a little too slowly.
There's entire YouTube channels dedicated to videos of Tesla Self Driving doing stupid things like trying to turn into a tram. At scale, 99.99% correct will still kill many thousands of people. Compared to the sheer volume of cars, there aren't actually that many Teslas out there.
I enjoy videos on the self driving space and Tesla's technical (not business) approach to it. Its produced results that were actually quite a bit better than I expected at this stage.
I still regularly see videos of Tesla's beta software attempting to pull out into traffic in situations that clearly could have very bad outcomes. I still see so much phantom braking that its a collision risk.
I wouldn't call it dangerous, in the sense that it is done well enough that the person at the wheel should be able to handle it, but it'd crash a lot without an attentive driver.
Its a long way from 99% reliability at this point.
so much of the modern economy is basic economic messaging "wrapped" in storytelling. The media is an enormous industry that (apart from news) is a few basic stories wrapped in elaborate ornamentation.
I completely agree with this comment. It is surprising to see how well AI is able to perform in fields like art and poetry, which require creativity and nuance, especially when compared to tasks like driving which may seem more straightforward. However, this shows that AI is most effective when it is able to make mistakes and learn from them. In the case of poetry, a human can easily sift through the generated poems and pick out the good ones, but in the case of driving, mistakes can have serious consequences. This highlights the importance of considering the potential risks and limitations of AI when applying it to various tasks.
I'm assuming this comment was written by ChatGPT, am I correct? It's got quite a predictable writing style, and also your comment doesn't add anything to the original, it's just reworded
"Indeed, AI's ability to make mistakes is what makes it so useful in generative fields like art and poetry, while its lack of mistakes is what makes it essential for tasks like driving."
Do you think this could actually be more of an indictment of how derivative and formulaic most "art" is? I don't think writing a poem requires any less perfection, just that we're more accepting of shitty poetry than we are terrible drivers.
What we are actually seeing is that AI is useful to the degree that being wrong is okay. AI’s mess up, and that’s okay with poetry because a human can quickly read the poems and pick out the good ones. It’s not okay when driving.