1) They are investing Loony Toons levels of money and using Loony Toons financing a lot of the time for DC buildout. Those are actual physical buildings that once built out, exist and don’t need to be built again.
2) They are pointedly ignoring FPGA and ASIC. With the current model quality, would it really be so bad to burn Claude irrevocably on a chip and have a non-modifiable, cheap to mass produce, order of magnitude faster Claude-in-a-chip? This is what happened to Bitcoin ultimately, there are huge performance gains we know exist lying on the table just because they don’t exist for training. And even for training, TPUs make the first steps in that direction.
Startups burning through VC money to build massive warehouses full of hardware those models need to run on currently seem to be quite power grid connector bottlenecked. A more efficient chip would help.
True, but only because they are choosing to actively burn VC money on training.
But it’s not like the models we have now would stop to exist if training stopped. Other than the occasional retraining to get the latest data in, if they stopped wanton experimentation with models, that admittedly is pushing the models forward, the training costs could plummet and inference would be the thing to optimize and scale.
> They are pointedly ignoring FPGA and ASIC. With the current model quality, would it really be so bad to burn Claude irrevocably on a chip and have a non-modifiable, cheap to mass produce, order of magnitude faster Claude-in-a-chip? This is what happened to Bitcoin ultimately, there are huge performance gains we know exist lying on the table just because they don’t exist for training. And even for training, TPUs make the first steps in that direction.
1) They are investing Loony Toons levels of money and using Loony Toons financing a lot of the time for DC buildout. Those are actual physical buildings that once built out, exist and don’t need to be built again.
2) They are pointedly ignoring FPGA and ASIC. With the current model quality, would it really be so bad to burn Claude irrevocably on a chip and have a non-modifiable, cheap to mass produce, order of magnitude faster Claude-in-a-chip? This is what happened to Bitcoin ultimately, there are huge performance gains we know exist lying on the table just because they don’t exist for training. And even for training, TPUs make the first steps in that direction.