Michael Carbin is Co-Founder and Senior Fellow at Unconventional AI, a groundbreaking deep-tech startup rethinking the physical foundations of computing to deliver biology-scale energy efficiency for AI workloads.

Michael earned his BS in Computer Science from Stanford, followed by an MS and PhD from MIT, where he has served as an Associate Professor of Electrical Engineering and Computer Science since 2016, leading the MIT Programming Systems Group.

A pioneer in AI/ML systems, programming languages, and approximate computing, Michael's research on verifying program reliability on unreliable hardware earned best paper awards at OOPSLA 2013 and 2014 and a Communications of the ACM Research Highlight in 2016.

Prior to co-founding Unconventional AI, Michael served as a Founding Advisor at MosaicML (acquired by Databricks for $1.3B in 2023) and as a Principal Research Scientist at Databricks, and also conducted research at Microsoft.

Unconventional AI raised a landmark $475M seed round at a $4.5B valuation, co-led by Andreessen Horowitz and Lightspeed Venture Partners, targeting analog chip technology capable of up to 1,000x lower power consumption than conventional digital computers.