Also some of them really struggled with people not being "different". Finnish Medieval couple used to come up with like a black dude and Asian woman lmao. It's bizarre.

The faces in the last set were awfully similar in each image. Didn’t understand Caucasian perhaps?

It's an AI thing. Nearly all small models struggle with separating multiple characters.

Yeah, Meta's 100% far white AF.

"AI" isn't needed to solve optimization problems, that's what we have optimization algorithms for.

Define an objective and parameters and give the problem to any one of the dozens of general solvers and you'll get approximate answers. Large cities already use models like these for traffic flow, there's a whole field of literature on it.

The one closest to what you mentioned is a genetic algorithm, again a decades-old technique that has very little in common with Generative "AI"

We don't want/need to analyze porn.

We need to generate our individualy optimized porn.

I really like your take on this and I totally agree. So far generative AI can only create mediocre or flawed results quicker than ever before. As you said it's pretty incredible it can do it at all, but the results are still a step down (or several) from a skilled professional.

I hope that as time moves on people start using it for what it's good at, not what it's mediocre at.

Generative AI has taken off so much because it works so well out of the box and can be interacted with by anyone.

The examples you gave require training specific to the role it will fulfil - that requires expertise, data and money - and needs to be repeated for every use case!

That has existed, and will continue to exist, but is not something the average person, or even the average developer sees.

Generative AI has the data, and the required data is immense. The challenge for other potential applications is that the data is not there or not available. There are no other aspects of human productivity that are as widely recorded and available as images and text. The next big thing will require an actual data collection effort; you won't get it from scraping the Internet.

That's absolutely true, generative AI is mostly a parlor trick with very few applications beyond placeholder art and faster replies to emails. But even for your kind of engineering problem, there's still a big issue that's often disregarded.

If we keep your example of an AI for a city grid, an important aspect of this type of engineering problem is guaranteeing that the system has as few catastrophic failures as possible (usually guaranteeing less than 1 for every 10^9^ hours of uptime for systems where catastrophic means a certain quantity of dead bodies or high monetary costs, like a city grid, train signalization, flight control...). AI models may very well end up being discarded in those problems because even if you observe a better accuracy in simulations and experiments, mathematically proving this 10^9^ figure is impossible because we don't know how they work. Proving a threshold experimentally can happen, but a 10^9^ number would require something like centuries of concurrent testing in every city in the world... I've just had a class with this example for trains. They were testing a system that reads signalization with a camera in order to move towards a more autonomous train. Deep learning performed better that classical image processing, but image processing allows you to prove that the train won't misread less than x% of the time with way higher certainty than a black box, so they had to go with that if they ever wanted to pass safety certifications.

So I guess deep learning explainability might be a more significant challenge even that finding a dataset that isn't racially biased...

The perfect problem to solve if you want a society that only runs on cars in detriment to any other way of transportation or mobility.

I'm thinking it's an issue that's more along the law of averages in the training data. Interracial images don't tend to have descriptions specifying that the content is interracial, or which individual is which race, but there are many photo's of individuals who are known to be of a specific race, so it falls back to the stronger probabilistic confidence in race x OR y OR z and completely ignores the weak "AND" correlation coefficients.

Rtfa. The prompts don't say "interracial" they just say things like "show an Asian man with his white wife."

Dalle-E 3 seems to be able to do it. Prompt for this was just "a white cat and an orange cat"

We tried it in class, after hearing about the US founding fathers being black and Nazis being surprisingly diverse with Asian women in the ranks too. Finnish Medieval couple was a black guy with an Asian wife. Maybe the AI was thinking of Netflix version of Finnish history.