Artificial intelligence startup Simile has raised US$100 million in funding to build a limited learning model designed to attempt to predict human behavior, including by helping companies anticipate questions likely to be asked on earnings calls.
The financing, announced on Thursday last week, was led by Index Ventures, with participation from Bain Capital Ventures and Hanabi Capital. Other people, including Fei-Fei Li and Andrej Karpathy, contributed to the round. Simile did not disclose a valuation.
Simile spun out from Stanford University and assumed a more public profile this week after spending seven months developing an AI model trained on interviews with numerous real people about their lives. The company fed its system data on historic transactions and text from scientific journals focused on behavioral experiments.
PhOTO: Reuters
The startup said it aims to use its technology to anticipate decisions a person might make in any given situation. To do that, it builds simulations populated by AI agents that represent the preferences of real people.
“In a recent earnings call, we simulated, we actually predicted, eight out of 10 questions that were actually asked on this call,” Simile CEO Joon Park said in a Bloomberg Television interview.
“Simile is a real combination of amazing frontier researchers but also amazing product and engineering talent,” Park said.
The company’s approach might provide another option for companies beyond relying on focus groups. CVS Health Corp has been using the model for five months to create AI agents that represent real customers instead of human-driven focus groups, according to Simile. CVS has been able to inform decisions about what items to stock up on and display in stores.
Simile said its technology can help companies better prepare for questions that analysts might pose on earnings calls or attempt to predict how a particular corporate announcement might be received by analyzing prior calls and research.
The startup is led by founding members Park, Michael Bernstein, Percy Liang and Lainie Yallen, all of whom have ties to Stanford. Bernstein, in particular, is the co-author, along with Li, of the influential ImageNet project, which set a benchmark for computer vision technology.
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