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11 results for “operational intensity”
Somebody who wants who is like us, who needed to buy for a month can actually buy for a month. They can, like, place the order and there is actually a price for that. And it typically comes from somebody else who's selling back. Somebody who bought a
25:35 / 26:38
from transcript25:35 – 26:38
Then it went to 10, then it went to 15, then it went to 20, and now it's upwards of $50,000,000,000 for the powered shell, for all the land, for all the permits, then for all the infrastructure, all the people, all of it. Okay. Sarah Friar said, I th
45:00 / 46:00
from transcript45:00 – 46:00
now I can do in eight out like, in four hours, I can do what used to take me eight. Sure. But how does the cup company's like, oh, wow. You're still you're you're you're operating on your baseline. But, actually, you should be able to do twice as muc
16:38 / 18:22
from transcript16:38 – 18:22
So what you kinda want is you want both parties to benefit, which is always tough because sometimes it's very, very hard to sell products to people that eliminate their jobs. Sure. That's probably the hardest thing to sell. But, like, I mean, maybe k
16:24 / 17:53
from transcript16:24 – 17:53
Yeah. Yeah. It's true. In terms of power utilization, the human brain is really impressive. What is it, like, tens of watts, 20 watts? How much like, what's the power utilization of a human brain? Right now. It is it is two magnitudes. It's, like, 10
19:31 / 20:39
from transcript19:31 – 20:39
because these clouds in the storage realm today generally sell object storage like s three, which is something that is billed per byte used, it is very low margin for the cloud. And then in addition to that product, all of the hyperscalers also sell
1:06:45 / 1:07:50
from transcript1:06:45 – 1:07:50
The only times in which you get kicked off is if there is a big price spike. And, you know, let's say one day out of the year, there's like a $4 an hour price because of some weird fluke or something. If there are other periods of time, you're actual
45:05 / 46:10
from transcript45:05 – 46:10
four u system with eight GPUs. This is kind of been the standard so far until the GB three hundreds and two hundreds came about in in the AI accelerator world. And you can stack a rack of them. It's very, very energy efficient. You know, each server
34:53 / 36:15
from transcript34:53 – 36:15
Our costs have more than tripled since November '25 between the inference cost that we pay AWS, which is ginormous, between our cost with Cursor, between Anthropic, we are just spending millions. So now more per unit and more more in aggregate? Both.
56:01 / 57:16
from transcript56:01 – 57:16
computer out there that is very performant for AI and runs on 20 watts, and we're using it to converse right now. It's our brains. Exactly. Right? So so that's very encouraging. And again, the brain to us instead of how you know, we we build it with,
42:42 / 43:46
from transcript42:42 – 43:46
have the most parameter efficient model and, hence, data efficient. Because the more parameters that you have, the more you gotta chisel away, using gradient descent. So you need more hits of the chisel, which is data points every time. Right? So unl
41:03 / 42:17
from transcript41:03 – 42:17
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