The AI industry has shifted from focusing on model training to inference, with inference now becoming the primary constraint; this transition is driving massive infrastructure investments, with new 'inference factories' projected to cost $40-50 billion and achieve 10x throughput improvements, while alternative solutions like custom ASICs from AMD cost $25-30 billion, creating significant market competition and strategic decisions about infrastructure investment.
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AI Inference: The BILLION-X BOOM You Can't Ignore! #shortsAdded:
Radios, radios will become uh edge devices. Factories, warehouses, you name it. And so So, there are three these three basic computers, all of them, you know, are going to be necessary. Jensen, last uh last year, I think you were ahead of the the rest of the world in in in saying inference isn't going to a thousand >> Just last year? Yes. Is it going to Is it going to Is it going to one million X? Is it going to one billion X?
>> Yeah. Right? And I think people at the time thought it was pretty hyperbolic because the world was still focused on pre-scaling, on training. Here we are.
Now, inference has exploded. We're inference constrained. Um you announced an inference factory that I think is leading edge that's going to be 10X better in terms of throughput to the next factory. But yet, if you if I listen to what the chatter is out there, it's that your inference factory is going to cost 40 or 50 billion. And the alternatives, the custom ASICs, AMD, others, are going to cost 25 to 30 billion, and you're going to lose share.
So, why don't you talk to us? What do you see? How do you think about share?
And does it make sense for all these folks to pay something that's a 2X premium to what others are marketing?
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