> The training and deployment of LongCat-2.0 are built on large-scale clusters of tens of thousands of AI ASIC superpods. Compared to the mature Nvidia GPU ecosystem, the supporting software community is still less developed. We have therefore put significant effort into building a stable, secure, and scalable infrastructure.
This is the real news story. It looks like they may have used Huawei Ascend 910C chips: https://nitter.net/teortaxesTex/status/2071708141037781407#m
If they really managed this from pre-training a 1.6 T parameter model through to post-training without NVIDIA, Dwarkesh Patel got what he wanted.
It is interesting how much people doubt Huawei’s capabilities in this area - Jensen does not (in the dp interview) - of course you can dismiss this as him talking his own book.
Who? What did he want?
Dwarkesh Patel has AI/ML guests on his podcast. BoorishBears may have been referring to the Jensen Huang episode where they discuss TPUs: https://youtu.be/Hrbq66XqtCo?t=982
Specifically Dwarkesh couldn't understand that GPUs are not enough: it's GPUs plus multiple ecosystems to leverage them at massive scale during training vs inference.
Instead of giving China open access to US controlled chips and creating a misalignment between labs that want to train a model on whatever is best, and hardware manufacturers that need labs to suffer the growing pains for their new ecosystems built from scratch... we removed the option from the board and now they've beat the growing pains decisively, with a speed that reflects the non-optionality.
I don't listen to Dwarkesh but I'm aware of who is and his influence. I was baffled that he could not understand it...Don't know if he had his own agenda or just not intelligent (which is scarey for someone with influencec), but I sensed the frustration in Jensen Huang for something that is fairly obviously.
The same scenario happens all the time when the US takes away something from China and China doubles down, gets into survival mode and then beats the US.
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