- Joined
- Dec 17, 2019
LLM's are not working like a human brain and I'll never believe otherwise. Datacenters are multiple times more powerful than a human brain, yet they can't achieve true superintelligence. Why? LLM's are fundamentally not like a human brain. They try to imitate one, but the only point of reference it has are similarities between words. They are capable of a lot despite being so limited, but you'll find even the biggest, most powerful models making the same mistakes no human ever would. Why? They're still LLM's, and frankly, we are reaching the limits of what we can accomplish with such an architecture.
We need even bigger datacenters using even more power that we cannot generate, hence why there are warehouses full of unused hardware like the ones Satya Nadella owns, and clearly it's the wrong way to go about things. It's fine right now when the stock market speculation bubble is running wild so you can build infinite datacenters, but the reality of it all will hit this entire market, and many are seeing these limitations already. Hence why there's more effort in managing to achieve the same capabilities and accuracy of LLM's at a lower hardware cost, reducing VRAM usage, optimizing token generation speed and so on. But IMO the true breakthrough that's needed is not compacting Fable/Astra/Sol/Civic/Espero into a smaller package that you can run on a single Mac Mini, but another breakthrough akin to that caused by Attention Is All You Need that kickstarted it all.
Most importantly, the whole craze has to pop, people have to realize it's not "AI" or "AGI", it's LLM's, ML models, clever but dumb pieces of software that cannot replace an entire workforce overnight, but tools that can improve the existing workforce if they're used correctly. Everything bad about LLM's stems from people overestimating their capabilities and overrelying on them, and that's directly fueled by the current stock market grift.
We need even bigger datacenters using even more power that we cannot generate, hence why there are warehouses full of unused hardware like the ones Satya Nadella owns, and clearly it's the wrong way to go about things. It's fine right now when the stock market speculation bubble is running wild so you can build infinite datacenters, but the reality of it all will hit this entire market, and many are seeing these limitations already. Hence why there's more effort in managing to achieve the same capabilities and accuracy of LLM's at a lower hardware cost, reducing VRAM usage, optimizing token generation speed and so on. But IMO the true breakthrough that's needed is not compacting Fable/Astra/Sol/Civic/Espero into a smaller package that you can run on a single Mac Mini, but another breakthrough akin to that caused by Attention Is All You Need that kickstarted it all.
Most importantly, the whole craze has to pop, people have to realize it's not "AI" or "AGI", it's LLM's, ML models, clever but dumb pieces of software that cannot replace an entire workforce overnight, but tools that can improve the existing workforce if they're used correctly. Everything bad about LLM's stems from people overestimating their capabilities and overrelying on them, and that's directly fueled by the current stock market grift.