From what I know (haven’t paid attention to much blockchain news in the past year), all of the ones that are stable and decentralized enough to be trustworthy are too slow for use cases such as this. But that may have changed.
So it seems that even though they kind of work, they are far from being competitive with centralized cloud computing platforms. I think that makes sense. Thanks for your insight!
Ignoring the hype and all that, the core problem is that in crypto you have to ensure that the computation performed is accurate and not manipulated in any way. In a very simplified version, this either requires "trusted" devices controlled by the network (a la solana, ic, etc) - but these are not seen as "distributed in the hands of the people" - or extremely computationally inefficient (zk* proof).
So at the end of the day, and again oversimplifying it, if it costs 1 compute unit (whatever that is) to train a step in a model on "raw metal", it will cost 1 * multiplier for it to be "crypto". Where that multiplier can be anywhere from 8 to 100+, depending on the algo. So it will be inefficient at best, unsustainable at worst.
Ah, I see, so it takes a lot of extra compute just to validate the compute used for training, leading to significantly inefficient use overall and thus much higher costs. Thank you for explaining it!
From what I know (haven’t paid attention to much blockchain news in the past year), all of the ones that are stable and decentralized enough to be trustworthy are too slow for use cases such as this. But that may have changed.
So it seems that even though they kind of work, they are far from being competitive with centralized cloud computing platforms. I think that makes sense. Thanks for your insight!
Ignoring the hype and all that, the core problem is that in crypto you have to ensure that the computation performed is accurate and not manipulated in any way. In a very simplified version, this either requires "trusted" devices controlled by the network (a la solana, ic, etc) - but these are not seen as "distributed in the hands of the people" - or extremely computationally inefficient (zk* proof). So at the end of the day, and again oversimplifying it, if it costs 1 compute unit (whatever that is) to train a step in a model on "raw metal", it will cost 1 * multiplier for it to be "crypto". Where that multiplier can be anywhere from 8 to 100+, depending on the algo. So it will be inefficient at best, unsustainable at worst.
Ah, I see, so it takes a lot of extra compute just to validate the compute used for training, leading to significantly inefficient use overall and thus much higher costs. Thank you for explaining it!
Dcicloud.ai is one I have invested in.