The Youngest Iranian Billionaire I Ali Ansari, Founder & CEO of micro1
Host Ardalan Javadi interviews Ali Ansari, Founder & CEO of micro1, about building an AI data company and his principles for founders.
15 Sept 2026TRANSCRIPT
She Took Fitbit From $700M to $2.2B | Yasi Baiani
Host Ardalan Javadi interviews Yasi Baiani, former Fitbit executive, about scaling revenue, strategic product decisions, and navigating the future of wearables.
2 Aug 2026
Is AI Revenue Inflated? | The Dejima Mafia
Babak Hodjat has been building AI agents since 1998. He said that in front of a room in San Francisco last week, sitting next to his brother Siamak for the first time in 25 years. His argument is narrower than the bubble talk, and more useful. Enterprises are not buying AI because a need has been identified. They are buying because the business side expects productivity in return.
The engineering that would actually deliver that productivity has not been done yet. Until it is, the revenue is running ahead of the value. He also thinks most of the layoffs attributed to AI were cuts companies could already afford. Babak co-founded Dejima in 1998. The patent behind it, "Adaptive interaction using an adaptive agent-oriented software architecture," carries a June 15 1998 priority date and became foundational to Apple's Siri. Sybase acquired the company in 2004. He went on to co-found Sentient Technologies, applying evolutionary algorithms to trading, and now leads AI at Cognizant.
Siamak Hodjat was at Dejima from the start and stayed in the assistant world through Siri, Viv Labs and Gameplanner alongside Adam Cheyer.
Recorded live in San Francisco on July 25, 2026, in front of a room of founders and researchers.
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Babak Hodjat : https://www.linkedin.com/in/babakhodjat/
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Inside a recent episode
The Youngest Iranian Billionaire I Ali Ansari, Founder & CEO of micro1
Published 28 Sept 2026 · Transcript excerpt
[…] Yes, now we have three products. First we call Realm, which is the data product and the RL environment product. They focus on Frontier Model Training. So when we name all the top labs, It's kind of one of the main architectures is RL. You basically run rollouts and in a bunch of different areas you run rollouts and then you train in any given domain. The way to think about it is, you can pick a domain, you can pick M&A, M&A Law. You can pick M&A Law, you can pick M&A Law, you can pick a data generation model for synthetic data generation. The human experts and the data generation models to create the environments, but two environments are the task. […]
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