The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 40 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 1 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
Park: Simile Optimizes for Human Biases Over Super-Rationality
“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 …”
Park: AI simulation can help solve wicked problems like climate change
“Simulation I do think can also be a cure for many of what we call quote unquote wicked problems.”
Park: Simulation models learn by validating daily real-world hypotheses
“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…”
Park: Simile models predict human behavior with 85% accuracy
“We show that we can actually predict people's behaviors and attitudes 85% as accurately as people replicate their own.”
Park: Synthetic panels will become larger than the human panel market
“The way I see it, synthetic panels will be larger than our, what we know to be the current human panel market, in part because this can really raise the ceiling of the kind of questions we can answer.”
Park: Within three years, single AI simulations will cost $20M
“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…”
Park: Stanford simulation first explicitly architected agent memory, planning, reflection
“And then was paired with memory planning and reflection. Really the first times that those concepts Came out to be an explicit part of the architecture in, quote unquote, agentic workflows.”
Park: Customers do not care about prediction unless trading stocks
“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.”
Park: Simile Replicated Multi-Month Consulting Studies in Two Minutes
“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…”
Park: PoC simulations are possible for anything; productionization is the real bottleneck
“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.”
Park: AI simulation can replace proxy representatives with direct societal modeling
“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.”
Park: AI Labs Without Clear Impact Visions Risk Failing as Companies
“I do think Neo Labs, without a clear vision for how they're going to impact the world, I do genuinely think there is some risk that they will turn out to be interesting research project, but not a viable company.”
Park: LLMs can simulate realistic human behavior across domains
“One of the early observations that we made was that these models are trained on so much of human behavior data, sentiment data that were expressed on the web. So if you poke at them sort of at the right angle, you could actually extract a lot of realistic huma…”
Park: Reflection Prompts Turn Raw Agent Memory Into Emergent Personality
“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? …”
Park: Simile Builds Foundation Models to Simulate Whole Markets
“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.”
Park: Simile sources data from everyday people, not elite experts
“We don't go after these expert programmers or expert scientists. We go after people like us, like everyday people living their everyday life.”
Park: Simulation extends far beyond traditional survey and interview tools
“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.”
Park: Simulation and AGI are the twin pillars of advanced technology
“The way I see it, simulation as a piece of technology is one of the twin pillars of technology. I'm a fan of science fiction. You read any advanced science fiction, there's always two pillars. One is some form of AGI that always shows up. The other is simulati…”
Park: Simile Models Improve by Comparing Simulation Outputs to Ground Truth
“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.”
Park: Coding agents improved rapidly due to clear accept/reject reward functions
“The reason why coding agents have had such massive improvement over the years was because their learning, their reward function was extremely clear. If you make a suggestion and your user says accept, fantastic. If they say reject, also very useful. You very q…”
Park: Simile co-founder Percy Liang coined the term foundation model
“Percy was the person who literally coined the term foundation model.”
Park: Simile Differentiates From Prediction Markets by Modeling Causality
“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.”
Park: The most compelling hires possess two contradictory superpowers
“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…”
Park: Great company builders balance daily paranoia with long-term religious optimism
“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…”
Park: Close AI research colleagues earn tens of millions in compensation
“So the research talent is very sought after today, and I have my closest colleagues and friends whose total com does range in tens of millions.”
Park: Back Academic Founders Driven by Impact and Revenue, Not Just Problems
“The thing I actually would look for is are they married to a problem or are they married to impact? Sometimes researchers are very much focused on a problem, and something about that problem fascinates them. But oftentimes it's just not a good company, or it's…”
Park: Simile raised $200M, reaching $300M total funding in six months
“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.”
Park: Simile raised capital because scaling data and compute accelerates progress
“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.”
Park: Parts of the AI Market Are Quite Frothy
“I do think there's parts of market that is actually quite frothy.
For sure.
There's a lot of capital going in, there's a lot of excitement.”
Park: OpenAI and Anthropic Grew via Foreseeable Model Progress
“One of the most interesting thing about how OpenAI Anthropics and these companies grew was there were very strong fundamentals they could actually map out.
They could actually see, oh, the models are getting better at this rate.
Oh, and there's this kind of de…”
Park: LLMs are the CPU of intelligence; simulation is the GPU
“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 …”
Park: Simile may own a small hedge fund down the line
“Maybe similarly, we'll actually own a small hedge fund down the line.”
Park: Future AI Companies Require Unique and Defensible Data Strategies
“I fundamentally believe that for AI companies in the future, you have to have interesting data strategy. Do you have access to data that no one else has access to? Do you know how to collect data that is very hard to collect?”
Park: Bullish on AI Hardware Startup Etched
“The recently etched came out of their stealth quite bullish on their team. I think they're going to be exciting.”
Park: Simile trains models on randomized control trials and A/B tests
“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 …”
Park: Simile cut production simulation model run costs by roughly 100x
“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.”
Simile uses enterprise research as wedge before expanding to consumers
“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…”
Park: Simile Customers Use Simulations to Avoid Multi-Hundred-Million-Dollar Blunders
“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.”
Park recruited doctoral advisors Percy Liang and Michael Bernstein to Simile
“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.”
Park: Simile raised Seed, Series A, and subsequent round within one year
“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…”