Long Live the 'GPU Poor' – Open-Source AI Grants

Thanks for providing context Jeremy. Fast AI has done an admirable job in communicating its commitment to an ethical pursuit of AI advancement. Do you feel such a commitment aligns with the bellicose rhetoric found in a16z's vision? Here is Marc Andreessen in a recent essay...

"There is one final, and real, AI risk that is probably the scariest at all:

AI isn’t just being developed in the relatively free societies of the West, it is also being developed by the Communist Party of the People’s Republic of China.

China has a vastly different vision for AI than we do – they view it as a mechanism for authoritarian population control, full stop. They are not even being secretive about this, they are very clear about it, and they are already pursuing their agenda. And they do not intend to limit their AI strategy to China – they intend to proliferate it all across the world, everywhere they are powering 5G networks, everywhere they are loaning Belt And Road money, everywhere they are providing friendly consumer apps like Tiktok that serve as front ends to their centralized command and control AI.

The single greatest risk of AI is that China wins global AI dominance and we – the United States and the West – do not.

I propose a simple strategy for what to do about this – in fact, the same strategy President Ronald Reagan used to win the first Cold War with the Soviet Union.

'We win, they lose.'

Rather than allowing ungrounded panics around killer AI, “harmful” AI, job-destroying AI, and inequality-generating AI to put us on our back feet, we in the United States and the West should lean into AI as hard as we possibly can.

We should seek to win the race to global AI technological superiority and ensure that China does not."

I don't think one needs to think too hard about the grave consequences a mission of "We win, they lose" may have for human survival.

Source: https://a16z.com/2023/06/06/ai-will-save-the-world/

1. I've updated the section now: https://gpus.llm-utils.org/cloud-gpu-guide/#so-which-gpus-sh... - that should answer it. Basically 1x 3090 or 1x 4090 is an ideal set up for stable diffusion, 1x A100 80GB is an ideal setup for llama 2 70b GPTQ (and you can use much smaller GPUs or even CPUs if needed, for smaller llama 2 models)

2. No, they don't have access to the internet unless you build something that gives them access

3. I'm not sure what you're asking