“In 10 years, computers will be doing this a million times faster.” The head of Nvidia does not believe that there is a need to invest trillions of dollars in the production of chips for AI
“In 10 years, computers will be doing this a million times faster.” The head of Nvidia does not believe that there is a need to invest trillions of dollars in the production of chips for AI
Despite the fact that Nvidia is now almost the main beneficiary of the growing interest in AI, the head of the company, Jensen Huang, does not believe that
“In 10 years, computers will be doing this a million times faster.” The head of Nvidia does not believe that there is a need to invest trillions of dollars in the production of chips for AI::Despite the fact that Nvidia is now almost the main beneficiary of the growing interest in AI, the head of the company, Jensen Huang, does not believe that
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Sorry I have doubts, because that would require a factor 4x increase every year for 10 years! 4x^10 = 1,048,576x
Considering they historically have had problems achieving just twice the speed per year, it does not seem likely.Twice for AI or computing in general?
Why does that make a difference? Compute for AI is build on the progress for compute first for GPU then for data center. They are similar in nature.
Yes they have exceeded 2x for AI for a while, but that has been achieved through exploding die size and cost, but even that won't make a million times faster in 10 years possible, because they can't increase die sizes any further.Building an ASIC for purpose built computation is significantly faster than generic gpu compute cores. Like when ASICs were built for bitcoin mining/sha256 and a little 5 watt usb device could outperform the best GPUs
The H200 is evolved from Nvidia GPU designs, and will be by far the most powerful AI component in existence when it arrives later this year, AI is now so complex, that it doesn't really make sense to call it an ASIC or to use an ASIC for the purpose, and the cost is $40,000.- for a single H200 unit!!! So no not small 5 watt units, more like 100x that.
If they could make small ASICS that did the same, they'd all do it. Nvidia AMD Intel Google Amazon Huawei etc. But it's simply not an option.Edit:
In principle the H200 AI/Compute system, is a giant cluster of tiny ASICS built onto one chip for massive parallel compute and greater speed.
It may be even more specialized than that. It might be a return to analog computers.
Which isn't going to work for Nvidia's traditional products, either.
There's also software improvements to consider, there's a lot of room for efficiency improvements.
Yes, but usually we keep those 2 kinds of optimizations separate, only combining chip design and production process. Because if the software is optimized, the hardware isn't really doing the same thing.
So yes AI speed may increase more than just the hardware, but for the most sophisticated systems, the tasks will be more complex, which may again slow the software down.
So I think they will never be able to achieve it even when considering software optimizations too. Just the latest Tesla cars boast about 4 times higher resolution cameras, that will require 4 times the processing power to process image recognition, which then will be more accurate, but relatively slower.
We are not where we want to be, and the systems of the future will clearly be more complex, and on the software are more likely to be slower than faster.even software that does the same thing gets slower example: Microsoft Office, Amazon, the web in general, etc.
That is so true, increased complexity tend to slow things down.