Aaron Levie

And I don't think people realize the scale of the opportunity.

No, no. Jump the fence. This is... That was all crazy pills when I just heard. There...

I think there's like 10 higher psyops you would do if you wanted to get us to have a collapsing economy than going after drone deliveries. What would they be? Well, first of all, I think you'd have AI do a robot. I like conspiracy corner. I think you'd have a robot AI thing that runs amok. That's a good idea.

Robocop. Yeah. Yeah, I think that would be way sooner than you worry about food delivery.

I'm liking Geiger these days. Oh, you're into Geiger.

Geiger Capital is good. I read them all. PC Braggs? PC Braggs? I think the nighttime thing would be, it would be at least typical of this government to do a Streisand effect of of just like, maybe if we cover it up, nobody will see. And then obviously it's the biggest thing. So yeah.

Gary Gensler said he's super happy. I'm going skiing. That's enough. I'm going skiing. I thought it was cool how he read the entire congressional bill earlier.

J. Cal loves to filibuster.

I mean, we have a very similar model as what Shma said, which is we're agnostic, so we work with multiple AI vendors. But I think a friend deep in AI land a couple years ago, right before ChatsBT, said there's no secrets in AI. And I didn't totally understand kind of at the time. It hadn't registered what that meant.

But very quickly, it kind of became obvious, which is the research breakthroughs sort of propagate insanely quickly across the AI community.

And so back back to this Moss framework, if you just think about it as if the research effectively becomes open at some point in time quickly enough, because either the researchers move or people publish it or whatnot, then it really is a compute game and then maybe a data access game. And that means that there's four or five at scale players that can that can fund this.

And I think as we've seen in other areas where it's an infrastructure play, you eventually have the underlying service. With enough competition, you have the underlying service eventually trend toward the cost of the infrastructure. So what we should expect is that the price of a token in AI land, you know, basically will be whatever the price of running the computers are.

And maybe with like a, you know, plus 10, 20% margin.

Let me give you a fun stat. We give our customers unlimited storage. We have 82% gross margin. So what happened was the price of the underlying storage has gone down by hundreds of times since we started the company. And then all our value is in the software layer on top of the storage.

So we've benefited by this incredible, just ruthless competition between Western Digital, Seagate, other players that are just trying to pack more more, you know, basically more storage density into these drives. And every couple of years, they have a new breakthrough. We're now, you know, upcoming, we're heading toward maybe a 50 terabyte hard drive.

When we started the company, they were kind of 80 gigabytes.

Yeah, so back in the day, if we had 10 people in engineering, 80% of them was doing pure infrastructure work. Now, if we have 1,000 people, it'd be inverted in terms of the ratio. So you get more leverage, both as you get the advancements in the technology, but then also as you get scale.

But all of this is to say, you should basically anticipate a world where, and I think Zuck is this interesting counterbalance on all of this because of open source,

If at any moment you know that Zuck will basically provide an open source model that is at kind of best in class benchmarks and at the frontier, then there is a limit on how much you can charge for the tokens of your hosted model because anybody will then be able to go host the open model and be able to provide infrastructure around it.

So if you always have that counterbalance and the tokens eventually kind of look the same, the output tokens kind of look the same.