Scale

“What I realized is if I'd met them at the sea, which I didn't, because it was outside our price bracket, but if I'd met them, I would have done exactly what you did, Jess, and I would have listened to the doom warnings, and I said, that's all silly and wrong, …”

“At scale, I think with scale, with assortment, with brand value new channels become unlocked, new efficiency grows leverage accelerates with assortment. I think it often only goes one way, but I don't think always.”

“And I think that's right because realistically, in the journey of what's going on, the only significant things we've done, I've said this before in the podcast, we put in the money and we put in more money when they need it. We decide to hire or not hire and f…”

“In my year, actually there were a ton of others who all kind of went into AI. And so obviously Steven and Andrew, who started the company you know, who started Cognition with us but also a ton of others. And so Alexander Wang, who started Scale. Demi Guo, who …”

“There's a ton of really interesting apps that, you know, for five, seven, eight percent of revenue on tokens are building huge value, which my sense at least is very different than the coding apps where you might be at 40 or 50%.”

“We haven't done deals with a billion dollars, but we kept it in a 100 to three, four hundred million dollar pre-money valuation, and right now that's been the wrong play, just to put it out there, right?”

“One of the misconceptions that exists today is that scale will solve everything. Scale will not solve everything. You need a different kind of architecture, and this continual learning is a difficult problem.”

“I'll tell you what I am betting on. I'm betting on that they can carve out a significant space in that market for that product, and that they've had explosive growth in it, and coming from the sass, I'm betting that I'm betting that that team coming from the S…”

“We looked at a number of companies that were behind Sierra and Decagon and came to the conclusion that a direct head-to-head Against those companies, when you're a smart, it's just a little bit too hard.”

“Scale is not going to get us to the type of AI development that we want to be at in, in the future as these models get more powerful and get deployed and all these sorts of like mission critical contexts.”

“You should know for each of the tools, professional does, how many of that profession exist, how many lawyers, how many doctors, how many bankers, how many wealth advisors, cause that's your time, you know, and I'm tracking that. And then it, so it's really nu…”

“It was higher.”

“Basically, the level of bureaucracy inside of Meta specifically in its AI division is really a problem for a lot of people. I think that this is something that new employees that have come in from OpenAI and, you know, scale and whatnot have complained about, …”

“Generations of people have developed clever methods of encoding priors about how they think an artificial intelligence should reason. And encoding it into the model, and all of this gets wiped out by scale and, you know, planning, like, basically, like, search…”

“It's just that scale is easier, and it's more reliable, and I think you, we're still seeing really big gains to that.”

“I assume that there will be a much more efficient way than that of doing it. You're exactly right. I'm sure, for example, that there will be a corpus available of a purchased copy of every, you know, I'm sure that Scale some one of these label guys that says w…”

“A lot of the clever approaches were, that we were doing in academia were ultimately, like, nothing in the face of scale, and that, like, if I wanted to build something impactful, I felt like I needed to do it in, like, an industry setting at that time.”

“The stunning thing is we've looked at it like you see about seven to 10 more good deals for every one deal you do, right?”

“I think the fact of the matter is like two billion dollars is enough to do a GPT four level run to do a deep seek style run. And so you, if you take all the best practices from deep seek V three and R one, like the reasoning model, and you spend the money to g…”

“There's no way that scale can recover from losing its founders. I love you, but it's a dead man walking instantly.”

“So as of September of last year, there were nearly a billion in ARR. In the first half of last year, they were at 400”

“And then the other bit is their margin is about 49%”

“At our stage, you know, 30, 35% of our deals don't work out, right? At the stage these guys are at, most of their deals, 90% plus of their deals, when you're writing those kind of checks, should be a one X plus IPO pop.”

“I am more proud of my two X's and three X's in 2004 and 2005, six, than any 10 X that kind of sailed into the 21 bubble and made me a fortune.”

“If you want to be the cost leader, it is rare that you can be the cost leader without having dominant scale in the territory in which you're operating. So if you want to be a niche. Cost leader, you know, good luck to you. That's almost never going to happen.”

“Yes, you know, this algorithm's a little better. Yes, this algorithm's a little worse. Yes, this data set's a little better. Yes, this data set's a little worse, but it's the scale that is primarily driving. And so it drove it in the large language models, hen…”

“And then it was a funny experience cause like scale came along and totally ate our lunch on the, in the self-driving market, which is a market like I knew and loved.”

“The next tier down just doesn't have the scale for owning your own workforce, owning the strategic purchasing, being able to rent houses because of your advertising budget in a more efficient way.”

“The thing that many people miss early on is that paid degrades with scale. Yeah. Everyone says like, you know, you'll get better at it. So you'll fight kind of the laws of gravity that might happen in a short term, but on a long-term time horizon, performance …”

“If you do one strategy, if you're a one trick pony, even if you're amazing at it, you're going to limit yourself in scale until you start to do other things.”

“Something that I learned early on working in media is that, you know, if you're dealing in scale, you're in a race to the bottom. There's no two ways about it.”

“And so if you ask the question, gee, why are people so excited about neural networks when we've been working on this since the 19 forties, the answer is scale.”