[heavyset_go]

> as soon as the gravy train stops rolling, all this intelligence will be out of access for most humans. unless some more efficient generalizable architecture is identified.

All Chinese labs have to do to tank the US economy is to release open-weight models that can run on relatively cheap hardware before AI companies see returns.

Maybe that's why AI companies are looking to IPO so soon, gotta cash out and leave retail investors and retirement funds holding the bag.

[PeterStuer]

They could still eliminate relatively cheap hardware.

[thin_carapace]

i was under the impression that we were approaching performance bottlenecks both with consumer GPU architecture and with this application of transformer architecture. if my impression is incorrect, then i agree it is feasible for china to tank the US economy that way (unless something else does it first)

[heavyset_go]

I think it just needs to be efficient or small enough for companies to deploy their own models on their hardware or cloud, for more inference providers to come out of the woodwork and compete on price, and/or for optimized models to run locally for users.

Regarding the latter, smaller models are really good for what they are (free) now, they'll run on a laptop's iGPU with LPDDR5/DDR5, and NPUs are getting there.

Even models that can fit in unified 64GB+ memory between CPU & iGPU aren't bad. Offloading to a real GPU is faster, but with the iGPU route you can buy cheaper SODIMM memory in larger quantities, still use it as unified memory, eventually use it with NPUs, all without using too much power or buying cards with expensive GDDR.

Qwen-3.5 locally is "good enough" for more than I expected, if that trend continues, I can see small deployable models eventually being viable & worthy competition, or at least being good enough that companies can run their own instead of exfiltrating their trade secrets to the worst people on the planet in real-time.

[g947o]

I mean, they have been doing that for at least a year, and I haven't seen signs of US economy tanking?... You need to find some better arguments

[heavyset_go]

There aren't any released open-weight models that are "good enough" yet, but Qwen-3.5 is getting really damn close to the point where more than half of my LLM usage gets routed to it.

I suspect, but don't know, some fields of inquiry will be fruitful when it comes to "good enough" small models. Especially when it comes to constrained tasks like software development. Software development models don't have to generalize to anything a chatbot can be asked or tasked with, the space it's required to generalize on is pretty small compared to literally the whole world.

If I was a betting man, I'd put my money where my mouth is, but I'm not. I am betting with my time and focus that smaller local models are worth it, and will be worth it, though.