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Well it could have happened but have required a non gpu-friendly architecture, it could have happened in 80 years from now and nvidia be long gone, etc. So fr

Well it could have happened but have required a non gpu-friendly architecture, it could have happened in 80 years from now and nvidia be long gone, etc. So from their perspective, it wouldn’t have happened at all. But I understand my comment was ambiguous.

KaoruAoiShiho 3y ago
No that doesn't make sense because NVIDIA physically built this field with their own hands. So there's no way it could have "not happened" or "not been GPU friendly" lol. Here is Jensen talking about building the industry 9 months before the founding of OpenAI: https://www.youtube.com/watch?v=_iBLoNG0qHk https://www.youtube.com/watch?v=_iBLoNG0qHk
- Agingcoder 3y ago
  I disagree, nvidia didn’t build ai. Gpgpu dates back to the early 2000s, and it happens that deep learning as a computational problem is very well suited to GPUs.People figured this out around 2012-2013, and just like with cuda a few years before, nvidia figured out there was a huge market for them, because the underlying compute problem was well suited to their hardware. Ai could have used different models which are not computationally friendly to gpus ( or may not even require a lot of computational power ) and nvidia wouldn’t have been so successful at ai, much like intel’s cpus are not well suited to current deep learning models. I remember discussing with friends in the hpc community what was going to happen to nvidia - we were wondering how they could grow their compute business. And bam, massive compute needs for ai, problem solved.
- hnfong 3y ago
  Hindsight is 20/20. "Could have not happened" means without hindsight, you could see the possibility that it might not have played out. nVidia didn't know for a fact that deep learning architectures would have been so successful in the past couple years. GP's point is that maybe deep learning would have worked 80 years later, and not have the great breakthroughs around 2016~now. The video from 2015 proves nothing. nVidia was deeply invested into this bet by then, and the mere fact that the video exist is evidence that they already betted heavily on AI by 2015 -- before the big results we know of today came about.

KaoruAoiShiho 3y ago

No that doesn't make sense because NVIDIA physically built this field with their own hands. So there's no way it could have "not happened" or "not been GPU friendly" lol. Here is Jensen talking about building the industry 9 months before the founding of OpenAI: https://www.youtube.com/watch?v=_iBLoNG0qHk https://www.youtube.com/watch?v=_iBLoNG0qHk

Agingcoder 3y ago
I disagree, nvidia didn’t build ai. Gpgpu dates back to the early 2000s, and it happens that deep learning as a computational problem is very well suited to GPUs.People figured this out around 2012-2013, and just like with cuda a few years before, nvidia figured out there was a huge market for them, because the underlying compute problem was well suited to their hardware. Ai could have used different models which are not computationally friendly to gpus ( or may not even require a lot of computational power ) and nvidia wouldn’t have been so successful at ai, much like intel’s cpus are not well suited to current deep learning models. I remember discussing with friends in the hpc community what was going to happen to nvidia - we were wondering how they could grow their compute business. And bam, massive compute needs for ai, problem solved.
hnfong 3y ago
Hindsight is 20/20. "Could have not happened" means without hindsight, you could see the possibility that it might not have played out. nVidia didn't know for a fact that deep learning architectures would have been so successful in the past couple years. GP's point is that maybe deep learning would have worked 80 years later, and not have the great breakthroughs around 2016~now. The video from 2015 proves nothing. nVidia was deeply invested into this bet by then, and the mere fact that the video exist is evidence that they already betted heavily on AI by 2015 -- before the big results we know of today came about.