Proton Mail is famous for its privacy and security. The cool trick they do is that not even Proton can decode your email. That’s because it never exists on their systems as plain text — it’s always…
It’s when the coffers of Microsoft, Amazon, Meta and investment banks dry up. All of them are losing billions every month but it’s all driven by fewer than 10 companies. Nvidia is lapping up the money of course, but once the AI companies stop buying GPUs on crazy numbers it’s going to be a rocky ride down.
I think it’s different. The fundamental operation of all these models is multiplying big matrices of numbers together. GPUs are already optimised for this. Crypto was trying to make the algorithm fit the GPU rather than it being a natural fit.
With FPGAs you take a 10x loss in clock speed but can have precisely the algorithm you want. ASICs then give you the clock speed back.
GPUs are already ASICS that implement the ideal operation for ML/AI, so FPGAs would be a backwards step.
It’s when the coffers of Microsoft, Amazon, Meta and investment banks dry up. All of them are losing billions every month but it’s all driven by fewer than 10 companies. Nvidia is lapping up the money of course, but once the AI companies stop buying GPUs on crazy numbers it’s going to be a rocky ride down.
Is it like crypto where cpus were good and then gpus and then FPGAs then ASICs? Or is this different?
I think it’s different. The fundamental operation of all these models is multiplying big matrices of numbers together. GPUs are already optimised for this. Crypto was trying to make the algorithm fit the GPU rather than it being a natural fit.
With FPGAs you take a 10x loss in clock speed but can have precisely the algorithm you want. ASICs then give you the clock speed back.
GPUs are already ASICS that implement the ideal operation for ML/AI, so FPGAs would be a backwards step.