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”.
While you have a look at the rising prices of recent graphics playing cards in contrast with their forebears, that is perhaps onerous to fathom. It positive seems like the price of a GPU has simply been steadily rising to most of us once we have a look at the objects of our silicon needs. However once 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 wherever 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 finished in creating extra highly effective graphics silicon, pushing down the relative worth of GPU computational energy, to the affect of Moore’s Regulation.
“The rationale 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 may as effectively simply begin throwing it at AI to resolve all our issues. Or, , draw us an image of a gold fish once you completely, positively simply have to have a freshly generated image of a fish.
There is not any getting away from it, the graphics card, and its constituent part, the GPU, have change into crucial items of silicon in our trendy time. There’s additionally no getting away from the truth that Nvidia is answerable for among the most vital silicon of our time, nonetheless you are feeling in regards to the rise and rise of synthetic intelligence and its potential affect 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 because the delivery of the GPU as we all know it, the cost-to-performance ratio has solely been going in a single course.
