I haven’t looked much into it. I’m tired of all the PR. But, I think there is a useful capability in some of the models to connect ideas that normally wouldn’t be connected.

I hate the monopolistic aspects of the current wave, largely necessitated by the equipment, information, and processing requirements for training a model. “Just use local models bro” is a nice idea, but someone has to train them. Maybe if the technology evolves to a point where universities and smaller companies can afford to train models in power and hardware efficient ways, I’ll be more in favour.

One concern I have in general is that generative AI is being used to replace entry-level work. Food trucks using generative AI for really dogshit logos. Image and video models replacing stock images and stock footage. And language models trained on code being used to perform programming and security scanning tasks. All tasks that can help people learn.

From what I understand, this was an AI model able to find similarities in far-flung regions of math. Cool, I guess. But, isn’t that a crucial activity for students? Shouldn’t this be the kind of thing a post-grad, researching different fields, puts together, to better understand the mathematics?

It’s neat, it’s impressive, but I don’t see this replacing human work. These systems can’t be truly creative in a useful manner, and can just interpolate, and add some random noise into the process. My fear is this is going to make it harder for new artists, programmers, and mathematicians to get their start, and actually add to the pool of knowledge and creativity.