Nearly all A.I. projects get stuck in "POC Purgatory" because of complex trade-offs between cost, speed and security. Thankfully, today's guest — Dr. Eiman Ebrahimi — cogently provides a path to production A.I. heaven.

Eiman is extremely intelligent and well-spoken; don't miss this episode! It was a delight developing this episode with him and I learned a ton from his gifted mind throughout the process.

Eiman:

• Is CEO of Protopia AI, venture capital-backed startup based in Austin that converts sensitive data into a special, stochastic format that improves A.I. model accuracy, protects privacy and reduces compute costs.

• Prior to founding Protopia, spent a decade at NVIDIA as Senior Research Scientist and Computer Architect.

• Holds a PhD in Computer Engineering from The University of Texas at Austin.

Today’s episode is relatively technical so might appeal most to technical listeners, but Eiman is such a terrific communicator that anyone interested in A.I. might love it.

In today’s episode, Eiman details:

• How he went from optimizing GPU performance at NVIDIA to revolutionizing A.I. data security.

• Why many promising A.I. projects get stuck in what he calls "proof of concept purgatory" - and how to escape it.

• Gripping, deep detail on the real-world tradeoffs between the cost, speed and security of running A.I. models in production.

• How to make your enterprise A.I. products profitable.

• Why having your own private server doesn't make your A.I. system as secure as you think.

• What Alan Watts' philosophy teaches us about entrepreneurship and innovation.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.