Technology

This is where "universal basic income" comes into play

So long as there are big players releasing open weights models, which is true for the foreseeable future, I don't think this is a big problem. Once those weights are released, they're free forever, and anyone can fine-tune based on them, or use them to bootstrap new models by distillation or synthetic RL data generation.

And a third intrinsic problem is that the current models with infinite training data have been proven to never approach human language capability, from papers written by OpenAI in 2020 and Deepmind in 2022, and also a paper by Stanford which proposes AI simply have no emergent behavior and only convergent behavior.

So yeah. Lots of problems.

Welcome to every technological advancement ever applied to the workforce

Eno does strike me as the kind of person who could use AI effectively as a tool for making music. I don’t think he’s team “just generate music with a single prompt and dump it onto YouTube” (AI has ruined study lo fi channels) - the stuff at the end about distortion is what he’s interested in experimenting with.

There is a possibility for something interesting and cool there (I think about how Chuck Pearson’s eccojams is just like short loops of random songs repeated in different ways, but it’s an absolutely revolutionary album) even if in effect all that’s going to happen is music execs thinking they can replace songwriters and musicians with “hey siri, generate a pop song with a catchy chorus” while talentless hacks inundate YouTube and bandcamp with shit.

Yah, I'm an AI researcher and with the weights released for deep seek anybody can run an enterprise level AI assistant. To run the full model natively, it does require $100k in GPUs, but if one had that hardware it could easily be fine-tuned with something like LoRA for almost any application. Then that model can be distilled and quantized to run on gaming GPUs.

It's really not that big of a barrier. Yes, $100k in hardware is, but from a non-profit entity perspective that is peanuts.

Also adding a vision encoder for images to deep seek would not be theoretically that difficult for the same reason. In fact, I'm working on research right now that finds GPT4o and o1 have similar vision capabilities, implying it's the same first layer vision encoder and then textual chain of thought tokens are read by subsequent layers. (This is a very recent insight as of last week by my team, so if anyone can disprove that, I would be very interested to know!)

But the people with the money for the hardware are the ones training it to put more money in their pockets. That's mostly what it's being trained to do: make rich people richer.

The real issues are capitalism and the lack of green energy.

If the arts where well funded, if people where given healthcare and UBI, if we had, at the very least, switched to nuclear like we should've decades ago, we wouldn't be here.

The issue isn't a piece of software.

That is a big issue, but excessive power consumption isn't intrinsic to AI. You can run a reasonably good AI on your home computer.

The AI companies don't seem concerned about the diminishing returns, though, and will happily spend 1000% more power to gain that last 10% better intelligence. In a competitive market why wouldn't they, when power is so cheap.