90% of the time I code these days, I use Github co-pilot. I have premium ChatGPT for some general shit throwing at the wall. In addition, I also pay for their API for a few scripts that summarize 1-2 hour long YouTube videos for me. LLMs and Generative AI are proliferating fast, more and more I find myself reading articles that are written and have their illustrations generated by diffusion models. For example an article like this, greets you with the following aesthetics:

The economics of what is going on right now are clear: we, humans, like cheap shit. For a while China and India were the sources of that. Over a few decades markets all around the world got quickly saturated with cheap crap made there. Almost overnight artisans around the world would find themselves debating whether to buy a Makita drill that costs say $100, or a cheap Chinese version that looks almost identical and has the same specs that sells for say $50. It doesn’t matter that the damn thing breaks in like a week, everyone bought it and continues to buy. If China was a cheap shit source for goods manufacturing, India was the cheap shit source for services: whether you needed a cheap website for your headhunting business or an R&D project delivered “cheaper” than your inhouse team would, you would go to some Indian “company”. The guys there would do everything, “very very cheap and very very good”. For the business and management people who never wrote a line of code in their life, it made sense. For programmers that would always inherit the pile of shit from the East, the realization usually was that “the salary is not the most important thing in life”, and they would usually just jump ships.

Fast forward to 2020s, our services and content driven economy just got a Greek gift – “\(\text{very very cheap and very very good}^{\text{very very cheap and very very good}}\)”. What we have right now is a medium (Internet), where “things” spread at the speed of light (no need to wait for cargo ships, slow trains etc), and a tool (generative AI) that in seconds produces something that otherwise could take at least a couple of hours if one uses ignorance when judging quality. Thus the new wave of mega cheap shit is moving without barriers and the potential for its size is exponential. Basically, the wave gets surprisingly bigger every time we blink.

Clearly, I use LLMs myself, yet there is this clear disdain, so what is the message here? The good days won’t last. Generative AI has a version of Midas touch – everything it touches turns to shit. It is not an existential problem until our Midas will have to eat. One problem that I see discussed nowhere, is that given the economics of GAIs, how long will it take for the training sets to start being overrepresented by content generated by GAIs themselves? I bet that if we were to count all the images on the internet right now, the number of images where humans have 3 or 6 fingers, just went from ~0% to 10% over the last year alone. Obviously, that is a joke, but helps to visualize the problem. If I were to make a serious guess, “data inbreeding” will become a hot topic in the future, the quality of GAI models is close to a peak, pre-GAI datasets will be worth gold.