Chamath: US AI Startups Can Learn A Lot from DeepSeek
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Episode Description
Full episode: https://youtu.be/8RkgkOqWs0s
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Brief Summary
Innovation in AI algorithms thrives under constraints, suggesting smaller funding may lead to deeper creativity.
Key points
- Revolutionary Algorithm Development. A new algorithm was invented that uses significantly less computer memory and performs better.
- Breaking Free from Cuda. Innovators bypassed Nvidia's Cuda, creating a new approach called PTX.
- Rethinking Funding Strategies. Exploring alternative funding amounts for AI startups could lead to deeper innovations.
Transcript
this is a case where necessity was the mother of invention these guys were like well how am I going to do this reinforcement learning thing they invented a totally different algorithm it uses a lot less computer memory and it's highly performant and then the second thing that was crazy is everybody is used to building models and compiling through Cuda which is nvidia's proprietary language and these guys worked totally around Cuda and they did something called PTX which goes right to the bare metal we meaning the West with all the money that we've had didn't come up with these ideas and I think part of why we didn't come up is not that we're not
smart enough to do it but we weren't forced to because the constraints didn't exist and so I just wonder how we make sure we learn this principle meaning when the AI company wakes up and rolls out of bed and some VC gives them 200 million maybe that's not the right answer for a series A or a seed and maybe the right answer is 2 million so that they do these deep seek like Innovations
