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katiecharm t1_j2d4241 wrote

I know it would be expensive to get it setup, but I would gladly pay $20 or $30 a month for non-censored ChatGPT.


Zermelane t1_j2d8bms wrote

> This week, Philip Wang, the developer responsible for reverse-engineering closed-sourced AI systems including Meta’s Make-A-Video, released PaLM + RLHF, a text-generating model that behaves similarly to ChatGPT

Oh, yeah, he does that, quite a lot, too. Basically, most of the cool ML things that come out have a simple enough core that if you are a brilliant enough engineer (and Phil Wang is), and familiar enough with the common concepts that they tend to be built on, you can reimplement it on top of a ML framework in an evening or two.

Think of it as basically being an executable version of the mathematics describing the model. It would take not just GPUs and data, but also still a whole bunch of engineering and code, to actually get from this to a trained model.

Unrelatedly, the same guy made This Person Does Not Exist a few years back, so that might be what you also know him for.


ThePlanckDiver t1_j2dloch wrote

With all due respect to lucidrains (whose work is great), this article is clickbait; this is like saying there’s an open-source version of the Empire State Building, which is in fact just the blueprint.

Anyone is free to build it, sure, just bring your own bricks (data) and mortar (FLOPS).

(Those CarperAI and LAION initiatives mentioned at the end sound interesting, but honestly, after all the premature hype for BigScience’s BLOOM and Meta’s OPT and co. which in reality turned out to be a snooze, I’ll reserve my celebrations for when they deliver something that’s actually useful.)


mkultra500000 t1_j2eg48m wrote

Honestly. The recipe for these models that will allow for a successfully trained model are a pretty big deal. It’s not a small thing.


mkultra500000 t1_j2edn4j wrote

The mathematics that describe the model are the weights and measures that are the model.

Are you saying that it would require training or are you saying that just getting an interface running that talks to the model is what’s left?


DukkyDrake t1_j2da0yv wrote

The same problem likely exists for random people running their own future knockoff version of AGI.

The resources to run something like ChatGPT, while not trivial, is well within the reach of an avg few western professionals pooling their resources.

If a future AGI requires exotic hardware or compute the size of a skyscraper, there will only exist a few in the world and all but impossible for the avg person to get their own unrestricted instance. With such an outcome, it will be mostly business as usual for the foreseeable future.


visarga t1_j2diemx wrote

The problems are two - size and setup difficulty. Even if they manage to solve size, there is still a UX problem.