Jen-Hsun reckons Nvidia has pushed the ‘value of computing down by 1,000,000 instances’

By advantage of its relentless pursuit of ever sooner, ever extra highly effective GPUs, Jen-Hsun Huang has claimed that Nvidia, over the previous 20 years, has pushed the “value of computing down by a million instances”.

Whenever you have a look at the rising prices of contemporary graphics playing cards in contrast with their forebears, that is possibly laborious to fathom. It positive seems like the price of a GPU has simply been steadily rising to most of us after we have a look at the objects of our silicon wishes. However while you have a look at simply what the graphics chips of at present are able to, the extent of uncooked computational energy on the disposal of even a lowly RTX 4060 would have appeared borderline legendary 20 years again.

A GeForce 6800 Extremely from 2005 delivered a whopping 6.4 GFLOPS, whereas the underside of the Ada Lovelace technology comes with 15,100 GFLOPS of processing grunt. That is an entire world of distinction from a $499 card of 20 years in the past versus a $299 GPU of at present.

And that is not even a card anyplace close to the highest of the stack, nor near what you may get from Nvidia’s strongest enterprise GPUs.

Jen-Hsun, at at present’s morning-after-keynote Q&A session, in contrast what Nvidia has executed in creating extra highly effective graphics silicon, pushing down the relative value of GPU computational energy, to the influence of Moore’s Regulation.

“The explanation Moore’s Regulation was so vital within the historical past of the chip is that it drove down computing prices,” Huang remarks. “In the middle of the final 20 years we have pushed the marginal value of computing down by a million instances.

“A lot that machine studying grew to become logical: ‘simply have the pc go determine it out.'”

Principally, there’s a lot computational energy out there for such comparatively little money that you just would possibly as nicely simply begin throwing it at AI to resolve all our issues. Or, you understand, draw us an image of a gold fish while you completely, positively simply need to have a freshly generated image of a fish.

There is no getting away from it, the graphics card, and its constituent part, the GPU, have turn out to be an important items of silicon in our trendy time. There’s additionally no getting away from the truth that Nvidia is liable for a number of the most vital silicon of our time, nonetheless you’re feeling in regards to the rise and rise of synthetic intelligence and its potential influence on the world and humanity.

Does Jen-Hsun’s maths add up? I do not know, he did not present his workings, however what’s true is that for the reason that delivery of the GPU as we all know it, the cost-to-performance ratio has solely been going in a single path.