|
|
|
|
|
|
by dragontamer
1750 days ago
|
|
|
But Tesla isn't a cloud-provider company, nor is it a hardware company. None of the technical specs, assembly language, API, SDKs or whatnot have been released for Dojo. The model of "someone will find this training computer useful" is... fine. Google TPUs, NVidia DGX, Intel Xe-HPC, AMD MI100, Cerebras wafer scale AI. These are computers that nominally are aiming for the market of selling computers / APIs / SDKs that will make training easier. Its a pretty crowded field. Someone probably has struck gold (NVidia has a lead but... its still anyone's game IMO) ------- If Tesla's goal is to compete against everyone else (or make a chip that's cost-competitive with everyone else), Tesla needs more volume than (allegedly) 3000 chips (quoted from the article: I dunno where they got this figure but... there's no way in hell 3k chips is cost-effective). That's the name of the game: volume. The reason why NVidia leads is because NVidia sells the most GPUs right now, which means their R&D costs are applied to the broadest base, which means those company's engineering costs (aka: CUDA training) is spread across the widest number of programmers, leading to a self-reinforcing cycle of better hardware, lower costs, with a larger community of programmers to learn from. |
|
|