The song sucks, but here was the cutting edge of AI music just seven years ago.
That it's gone from some nightmarish fever dream mashup to wannabe pop influencer levels of quality in less than a decade is pretty crazy, and as long as there isn't a plateau in the next seven years we'll probably be in a world where AI generated musical artists have a popular enough following that they will have successful holographic concert performances by 2030.
I over and over see people making the mistake of evaluating the future of AI based on the present state while ignoring the rate of change between the past and present.
Yeah, most of your experiences of AI in various use cases is mediocre right now. But what we have today in most areas of AI was literally thought to be impossible or very far out just a number of years ago. The fact you have any direct experiences of AI in the early 2020s is fucking insane and beyond anyone's expectations a decade earlier. And the rate of continued improvement is staggering. Probably the fastest moving field I've ever witnessed.
Technically we already have things like Vocaloid, which aren't AI yet, but do have their own holographic concerts that are popular in places like Japan and China. So having an AI artist come on stage and sing be too farfetched for me, despite the fact I'd hate it because it's a soulless entity devised by the corporate fascists. As for the quality of AI generated songs, no clue, but I can totally see them just ripping off up and coming human artists and then sending cease and desist letters to them for "StEaLiNg Ai GeNeRaTeD mUsIc" that was originally stolen or just stealing popular vocaloid songs and piggybacking off of every single person they can for profit.
Keep in mind, though, AI progress is often more like punctuated equilibrium.
Each new approach gets you much further, and polishing each approach gets you slight improvements until the next approach comes along. Improvements to chatgpt might plateau until the next big breakthrough architecture. Or maybe not.
polishing each approach gets you slight improvements
Without the base model changing at all, research into better use of the models has, depending on the measurement, gone from around 35% success rates to 85% success rates.