Hacker News Reader

Comment by monero-xmr | Hacker News Reader

There just isn’t a lot of market opportunities where being right 99% of the time is good enough. If you are operating at scale and 1/100 decisions are wrong, the outcome is poor and often highly off-putting to users.

It’s possible this time is different, but people at my company were entertained by DALLE for all of 5 minutes before no one ever mentioned it again. The value proposition is simply low.

View on HN

Are you kidding? Many times corporate decisions are being made effectively at random. Thinking that the average company operates with a 999 batting average is a total fantasy.

When our c suite decides on an ad campaign and tells our artists to draw normal humans, those people have 3 legs or upside down teeth exactly 0% of the time. Humans have many many limitations, but with every model I’ve tested there’s a set of errors that would virtually never be made by any human.

> with every model I’ve tested there’s a set of errors that would virtually never be made by any human

I guess you've never seen my drawings...

I think it's interesting that drawing too many fingers is a mistake kids make, too, although with less photorealism otherwise. I guess there's a reason all thosr famous artists drew hundreds of hands as practice as well.

No one is suggesting anyone take the first image out of a model without any human-based filtering.

Exactly. I have a catchphrase for this "AI generate, human mediate".

This revolution is allowing us to conduct the orchestra instead of playing each instrument.

In fairness ad campaigns have people who review the creative. Now I could see a band using an image like that or something edgy

As an outsider, this rings true to me. I still don’t see any reduction of hours involved in producing professional level works. Generating YouTube thumbnails, sure.

I agree. Cars break down and crash, they'll never replace horses.

I think this analogy doesn't hold water - horses aren't exactly a beacon of reliability (having owned one).

I've already seen tools that support workflows where you compose art by iteratively generating a piece of it, performing some correction, and repeating. So, I think there's room in the art world for less than perfectly generated art. That said, let's not kid ourselves that the typical failure modality of ML today (99% correct enough, 1% disastrously incorrect) doesn't either cause it to be entirely useless in many applications or end up wreaking havoc on end users in others.

It's only an analogy, but it serves to underscore the last point you make. Initial versions of the technology can make some genuine horrors but you're blinding yourself to progress if you can't see the potential in it.

the cars we're talking about here have a random amount of wheels and sometimes morph into cosmic horrors mid-ride.

Reply on news.ycombinator.com