[atodorov99]

Are u talking about incurring technical debt from the generated AI code that vastly out prices the original low cost of using AI. I cannot answer ur question on how big is one compared to the other but I have an idea that can sideline them. I don't think it will matter, AI is so exceptionally good at generating just good enough spam, so exceptionally good at delivering a shitty minimally viable product that it might warp the expectations and needs of consumers. Where the new shittyness becomes the new norm because it drowns out everything else around it with shear volume. People around me prefer to generate their Dungeons and Dragons characters and cities with AI because it good enough even though it looks painfully bad and often doesn't completely fit their vision. Music songs are being composed for small communities almost constantly at the moment because people do not want to bother to go out of their way to find a real human composer.

It's easy, it's fast and it gets the point across. Quality is only encouraged socially, people don't really care that much about quality. Rather people have 100 things they care about in their lives - an app for their groceries, a small game of their own idea to show to friends and play, a piece of music about that one time their group of friends got drunk and went into the mountains to fight a bear that in the end turned out to be some old granpa's cow. And only one or two which are important enough to spend the effort to find a quality product.

For software - the places where hard identifiable metric matter... Sensors, weapons, performance, networking, etc. They won't be replaced by AI's any time soon but so many other types of product imo will be assimilated by the machine. All desktop apps for regular people, all websites for blogs, posting, sharing. Probably most IoT related things in your own home

It is hilarious that the machines will first devour the industries that need more feelings and ideas rather then raw precision.

[reaperman]

> Are u talking about incurring technical debt from the generated AI code

I think they're talking about the marginal cost and capital cost of running all those GPU's, as well as the capital costs of training foundational models. With GPT-(n+m) projected to require new nuclear power plants dedicated to GPU usage, there's a question of what the payback time will be and whether the marginal costs will exceed that of a human.

[namaria]

What we get from the sun isn't energy. All the energy we receive has to be irradiated away, or we'd be cooked. We get low entropy energy that we dissipate to sustain our local low entropy systems going and growing.

What LLMs offer is second hand low entropy data. They feed off the low entropy human generated data and give it back. But they raise the entropy of the total body of data, inevitably. The more AI slop there is, the less useful work LLMs can extract from data.