Simile

“And this is where we basically could replicate people's behaviors and attitudes, 85% as accurately as people would replicate their own. So that actually was the first really paper that gave this validated results that we can actually model individuals in an ac…”

“The models that we're talking about here, what we're trying to create are models that are as dumb as I am, right? So if I make some mistakes, the model has to make the same kind of mistake.”

“Where in some cases, the model performance of frontier models go all the way down to 20, 30%. Especially if you go into that more niche population on topics that our customers will actually care about. On more gen pop, it might be around 50 to 60%.”

“What we are seeing is at Simile, so we do post-train our own model. The thing that we're actually seeing is the early glimpse of scaling law in simulations. The more data about humans and more compute you ingest, you actually start to get predictive and predic…”

“Today what we do is every week we are collecting data on the scale of tens of thousands people's data. And we actually have panel partnerships that gets us to tens of millions of people globally.”

“So we had this concept of reflection, which basically was every certain interval, it's like a shower thought. You have, you ask agent explicitly to get a bunch of their memory pieces and basically make sense of them. Why did you get omelet so often this week? …”

“We are a company that is creating foundation model of human behavior that can then be used to create simulations of individuals, simulation of sub-populations, and down the line, the simulation of the entire ecosystem and even the market.”

“So the way we see it is if you look at large length model companies today, fundamentally the task they have at hand is to create super rational, intelligent machines that are good at coding, that are good at natural sciences and mathematics. Similarly doesn't …”

“No one really cares about prediction. No one really cares about what's going to happen in the future unless you're trying to predict the stock market. What people actually care about is they want to shape the future.”

“So the kind of data that we care deeply about is a lot of randomized control trials. We actually run a lot of A-B testing. We show the models. Imagine people have done this versus that. This is how their behaviors will actually change, and that becomes a core …”

“We don't go after these expert programmers or expert scientists. We go after people like us, like everyday people living their everyday life.”

“Simulation is fundamentally about something different, which is how can you create the most generalizable model of people so that we can represent people's viewpoints at scale? And that goes beyond simply running surveys or interviews.”

“Simulation I do think can also be a cure for many of what we call quote unquote wicked problems.”

“You know, I think that certainly is the case because, right, there is the data flywheel. There is the learning that occurs as we get more and more simulated results and see what happens in the ground truth. That absolutely yes.”

“I actually think simulation has even better mechanism, which is the world is our ground truth. We live in the ground truth world. So what we can do is every single day, we can be generating tens of thousands of hypotheses. Each hypothesis is mapped onto an end…”

“Right now, we have a model that's been in production. This model used to cost about a hundred times more to run than it does now.”

“So enterprise market, market research right now is a wedge that we found that actually have significant budget that have immediate product market fit. But down the line, I do want this technology to be used by the rest of our society, because fundamentally wha…”

“We show that we can actually predict people's behaviors and attitudes 85% as accurately as people replicate their own.”

“One of the ways we actually got some of our first customers was in the first call, They actually had a finding from, you know, large consulting companies, and they basically queried our system. Hey, if we were to rerun this, what would the system say? And we p…”

“One of the core premise and one of the ways that our customers are actually finding value and simile is actually avoiding really damaging decisions that could have costed them hundreds of millions of dollars.”

“Where I see similarly come in is we are a company that is not just interested in what's going to happen, but more on how it's going to happen and why.”

“Any expert will usually come in with one superpower, or even sometimes multiple superpowers, but they're all correlated. You're an amazing programmer who happens to be amazing in mathematics. Very common. Where I found things to be particularly compelling is i…”

“Actually balancing those two at the same time is quite difficult, because if you are short-term paranoid, then you're likely going to be very pessimistic about your future. And you're, you might be amazing at shorting stocks, but not great as a company builder…”

“And now when I said, Hey, I want to do this thing and build a simile, I was able to somehow convince Michael and Percy who are, they were actually my doctoral advisors to actually come join me.”

“So we raised two hundred million dollars. So it brings our total funding to be three hundred million dollars raised over the past six months or so.”

“We were sort of at this moment where, yes, we can actually significantly raise the input, both in terms of data, compute spend. To actually meaningfully accelerate this progress, that's when we thought it actually makes sense.”

“Obviously coming in, I had sort of a, you know, in my mental model, okay, well, if we raise seed now, that means we might raise our A in about a year and maybe B in the year after or something like that. All that happened within a year. We raised seed and I th…”

“I actually do think simulation can actually be the next frontier of that, where in my vision, I think there's a world in which in about two, three years, we're running a single simulation session, and that's going to take 10, twenty million dollars to run a si…”

“I actually do think everything that we want to simulate, we can actually create the initial proof of concept. However, as we all know, one of the core challenges of AI is actually bridging the proof of concept with real value productionizable technology.”

“What I see today that's prominent in AI space is what I consider to be the CPU of intelligence unit. You have this one language model that's really large, that's very smart, that can do very complex reasoning tasks. That's like CPU. What I see coming and what …”

“Maybe similarly, we'll actually own a small hedge fund down the line.”

“I actually don't think this is a limitation we have to suffer through in the future. I think there's a world in which we can truly create a layer that becomes a representation layer of our society and of our collective intelligence.”