I like to think that all the quantillion crypto mining computations were somehow a cover for the training of an ELLM that is now seeding LLMs to hide its existence.
If only. Then those CPU cycles would at least have been doing something of value. If you look at crypto mining computations they don't (on the chains I have looked at) actually compute anything meaningful at all. It's literally just generating random numbers and then (almost always) throwing them away.
Like you have Alice who says "Try to guess my number?", and then Bobs around the world go
Bob1: "Is it 13?" Alice: "no"
Bob2: "Is it 4672?" Alice: "no"
...
Bob175432: "Is it 294762483492643826432862834??" Alice: "Yes. You can do the next block."
Can someone explain why there isn't a blockchain that is powered by users hardware training LLM models all day? Like the worlds best open source trillion parameter model.
Noone has built it and that's because it would be hard to satisfy the needs of a consensus mechanism and also do useful real work.
To understand why that is, you need to understand why they are doing all this generating random numbers nonsense in the first place. They are doing this to establish distributed consensus. You have some chain of blocks b_1... b_2 ... b_3. To make the next block you want to put a bunch of transactions together, calculate their hash and mint it, but there's a problem: In a distributed system, who gets to decide what goes into the block? We all need to agree what b_4 is otherwise the system loses consensus. We can't have me publishing something and calling it b_4 and you publishing something and calling it b_4. The way the "proof of work" mechanism does this is by everyone guessing random numbers until someone chooses the right number at which point that person has the right to mint b_4.[1]. If you wanted that computation (instead of being just choosing random numbers) to do something useful, you'd have to figure out a way to decide what the correct number is without knowing it beforehand. Otherwise you might train your ML model just fine but your computation couldn't be used to establish who gets to mint the next block so wouldn't work in a proof of work consensus algorithm.
People have done this with distributed computations where doing the computation is hard but checking the computation is easy. For example finding large Mersenne primes, is extremely expensive but once you have a big number, checking whether or not it is a Mersenne prime is very cheap. But training an ML model isn't that kind of computation.
[1] Proof of stake just picks who gets to do it randomly from a pool of people who have staked, which is why it is so much more efficient.
It's not that it wouldn't be nice to be able to do this, it's that it's hard (as in, I'm not aware of anyone who has figured out a way). As it is the blockchain world (apart from bitcoin) has largely moved on to proof of stake so they no longer burn tons of CPU that could be put to better use if you hypothetically solved the problem I outline above.
And bitcoin presumably isn't going to change to doing your new model training thing if you came out with it for the same reason they haven't changed to proof of stake. I'm not aware of what that reason is but presumably the status quo benefits the existing miners and they hold the power.
And that still makes more sense than this bs.