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Fei-Fei Li and Andrej Karpathy Back a New A.I. Use Case: Simulating Human Behavior

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Fei-Fei Li at the 29th Annual Webby Awards held at Cipriani Wall Street on May 12, 2025 in New York, New York. " width="970" height="675" data-caption='A.I. pioneer Fei-Fei Li is lending her support to Simile’s effort to simulate human behavior at scale. <span class="lazyload media-credit">John Nacion/Variety via Getty Images</span>'>

Every three months, public companies brace for analyst questions during quarterly earnings calls. But what if firms could predict these queries in advance and rehearse their responses? That’s one of the capabilities touted by Simile, a new A.I. startup spun out of Stanford and backed by acclaimed researcher Fei-Fei Li and OpenAI co-founder Andrej Karpathy.

Simile emerged from stealth yesterday (Feb. 12) with $100 million in funding from a round led by Index Ventures. Alongside Li and Karpathy, the startup—which hasn’t disclosed its valuation—also counts investors including Quora co-founder Adam D’Angelo and Scott Belsky, a partner at A24 Films.

Li and Karpathy both have close ties to Simile’s founding team, which includes Stanford researchers Joon Park, Percy Liang and Michael Bernstein. Li is the co-director of Stanford’s Human-Centered A.I. Institute and advised Karpathy during his Ph.D. study at the university. She is widely known for foundational work such as ImageNet, a large-scale image database that helped drive major breakthroughs in computer vision. Karpathy and Bernstein also contributed to that project.

Simile’s mission of using A.I. to reflect and model societal behavior taps into an underexplored research area, according to Karpathy, who previously worked at OpenAI and Tesla before launching his own education-focused A.I. startup. While large language models typically present a single, cohesive personality, Karpathy argues they are actually trained on data drawn from vast numbers of people. “Why not lean into that statistical power: Why simulate one ‘person’ when you could try to simulate a population?” he wrote in a post on X.

That idea underpins Simile’s broader goal. The Palo Alto-based startup aims to simulate the real-world effects of major decisions, from public policy to product launches, across virtual populations that mirror human behavior. The team has already tested this concept on a smaller scale through projects like Smallville, a 2023 Stanford experiment in which 25 autonomous A.I. agents interacted in a virtual environment.

Now, Simile is scaling the approach for business use. After spending the past seven months developing its model, the company is already working with clients on applications ranging from product development to litigation forecasting. CVS Health Corporation, for example, uses Simile to create simulated focus groups, while Gallup uses the platform to build digital polling panels. For earning calls, Simile can predict about 80 percent of the questions that analysts ultimately ask, said Park, the startup’s CEO, during a recent appearance on TBPN.

At present, Simile’s models are based on data from hundreds of thousands of people who have signed up for its studies. Over time, the company hopes to expand that to simulations representing the world’s entire population of roughly 8 billion people.

Simile joins a growing wave of A.I. companies focused on using simulation to model real-world scenarios. Much of the existing research in this space has centered on physical systems, such as robotics and autonomous vehicles, through “world model” platforms developed by firms like Google and Nvidia.

One of the most prominent figures in world models is Li herself. In 2024, she took a leave of absence from Stanford to launch World Labs, a startup that builds 3D digital environments from image and text prompts. The company has raised $230 million to date and is valued at more than $1 billion.






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