Azalia Mirhoseini

Azalia Mirhoseini is an AI researcher and entrepreneur whose work focuses on machine learning, hardware design, and artificial general intelligence. Mirhoseini is a co-founder of Ricursive Intelligence, a research lab dedicated to recursive self-improvement through AI and the design of advanced chips. She is also an assistant professor of computer science at Stanford University, where she directs Scaling Intelligence, a lab focused on developing scalable and self-improving AI systems and methodologies related to artificial general intelligence.

Mirhoseini has held positions in industry AI labs, including Google Brain, Anthropic, and Google DeepMind, contributing to the development of "Claude" and "Gemini." Alongside her co-founder, she created AlphaChip, an AI tool that generates chip layouts in hours, a process that traditionally requires human designers a year or more. AlphaChip has been used in the design of multiple generations of Google's Tensor Processing Units. Mirhoseini holds a Doctor of Philosophy in electrical and computer engineering from Rice University.

Her research includes Mixture-of-Experts neural architectures, widely used in generative AI models; "AlphaChip," a deep reinforcement learning approach for layout optimization in advanced chip design; and work on LLM Test-Time Scaling. At Anthropic, Mirhoseini contributed to Constitutional AI for training large language models using AI feedback, and her research on "Large Language Monkeys" established scaling laws for inference-time compute. AlphaChip is recognized as one of the first reinforcement learning methods applied to real-world engineering challenges, influencing research in AI for chip design.

Mirhoseini co-founded Ricursive Intelligence to transform chip design, building on the foundation established with AlphaChip. The company automates semiconductor design with reinforcement learning, reducing chip development timelines and enabling advancements in AI hardware. Mirhoseini serves as chief technology officer of Ricursive Intelligence.

Her work has been recognized by the Okawa Research Grant, the Google ML and Systems Junior Faculty Award, MIT Technology Review's 35 Under 35 Award, the Best ECE Thesis Award at Rice University, and publications in venues such as Nature. Media coverage includes Wall Street Journal, New York Times, Forbes, MIT Technology Review, IEEE Spectrum, WIRED, and TechCrunch. Mirhoseini's scholarly work has received more than 27,000 citations, reflecting her influence in AI systems research, machine learning, and semiconductor design.