Comment by __MatrixMan__
1 month ago
Is that constraint fundamental to what they are? Or are they just reflecting the behavior of markets when there's low hanging fruit around?
When you look at models that were built for a specific purpose, closely intertwined with experts who care about that purpose, they absolutely propel communities to new heights. Consider the impact of alphafold, it won a Nobel prize, proteomics is forever changed.
The issue is that that's not currently the business model that's aimed at most of us. We have to have a race to the bottom first. We can have nice things later, if we're lucky, once a certain sort of investor goes broke and a different sort takes the helm. It's stupid, but its a stupidity that predates AI by a long shot.
I don't know anything about the field but apparently AlphaFold having "solved the problem of protein folding" is overhyped? https://old.reddit.com/r/bioinformatics/comments/1e0s55e/did...
Experts making a specialized model isn't an example of an AI contributing value to society. All the value a model can offer comes from one of exactly two places: the person building the model, or the people the model trained on.
We know that the model training on the model training on the model leads to model collapse...
Your word choice implies a very zero-sum perspective on value.
Value is determined by what we value, it's a choice. If a bunch of scientists value good approximations for how a protein will fold, and then a model generates more such things in a year than those scientists could make in a century, that's a lot of value. Not extracted from anyone, created.
Yes. Value created by the people who made the data the model trained on, and the people who ensured that the training created a good model. I'm just saying it's not magic, just another kind of high-level work that people do.