Many of the business models were good too but they had the timing wrong.
Petfoods.com IPO for about $300 million. $573 million adjusted for inflation.
Chewy is at a 14 billion market cap right now.
I think comparing LLMs and the dotcom bubble is just incredibly lazy and useless thinking. If anything , all previous bubbles show is what is not going to happen again.
Like when a relationship is obviously over. Some people enjoy the ending fleeting moments while others delude themselves that they just have to get over the hump and things will go back to normal.
I suspect a lot of the denial is from the 30 something CRUD app lottery winner. One of the smart kids all through school, graduated into a ripping CRUD app job market and then if they didn't even feel the 2022 downturn, they now see themselves as irreplaceable CRUD app genius. Something understandable since the environment has never signaled anything to the contrary until now.
I think it is how our expectations of the latest model change over time.
I expect to be completely blown away by GPT-5 in the first few days and then over time I will figure out the limitations of the model. Then I will be less impressed because you don't know what it can't do at first.
I am on a GLP-1 level calorie restricted diet right now without a GLP-1 and of course it is just miserable.
I love eating a giant sandwich at night that is more calories than what I am eating all day now but it isn't the taste it is the brain chemical release.
It is an addiction like any other addiction. I have never felt that same craving for chicken breast.
IMO I think it is a combination of being a really great programmer already and then either not all that intellectually curious or so well read and so intellectually curious that LLMs are a step down from being a voracious reader of books and papers.
For me, LLMs are also the most useful thing ever but I was a C student in all my classes. My programming is a joke. I have always been intellectually curious but I am quite lazy. I have always had tons of ideas to explore though and LLMS let me explore these ideas that I either wouldn't be able to otherwise or would be too lazy to bother.
Machine-learning for audio is just a different form of audio synthesis.
That is not the issue. The issue is how incredibly generic the music is.
It also doesn't let you combine genres to make really strange sounds like audioLM can do.
This is just another Muzak generator like they use to play at Dennys. As generic music as possible to the appeal to the most average of average listener.
I think you really need to train your own model if you want to explore creative sound design or algorithmic composition. It just isn't going to be a mass market product worth venture capital money.
wow I just listened to Eleven Music do flamenco singing. That is incredible.
Edit. I just tried it though and less impressed now. We are really going to need major music software to get on board before we have actual creative audio tools. These all seem made for non-musicians to make a very cookie cutter song from a specific genre.
HN is just for insecure , miserable shitheads.