[sbierwagen]

>48GB ram

48GB VRAM? 48+ gigabytes of system ram is cheap, 48 gigabytes of ram on a GPU is still painfully expensive.

[moffkalast]

Yes, in this GPU market that's essentially a new car's worth of cash.

[robbedpeter]

Or $10 a month for colab or any of the various and sundry cloud services available. If you end up needing a dedicated service, huggingface is phenomenal - the barriers to using large language models are trivial.

[JudasGoat]

The Amd APU's would be interesting although under powered. They give you the option of setting "VRAM" size to almost any percentage of system memory.

[schleck8]

GPUs are the slowing factor in general if I'm not mistaken when it comes to Deep Learning progress.

[charcircuit]

Yes, vram

[x3al]

Would m1 max work?

[blovescoffee]

Right now there's meh Deep Learning support on the m1 max. TensorFlow is ~supported~, PyTorch is not. Apple has their Neural Engine and CPU/GPU architectures sort of hidden and so it's hard to port or support them.