All Turtles Podcast Episode 43: AI and neuroscience entrepreneur Katharina Volz

When it comes to curing Parkinson’s disease, the biggest obstacle is in making use of siloed research. So says Katharina Volz, founder and CEO of OccamzRazor, an AI-neuroscience startup. They’ve built a “super brain” to read everything ever published about Parkinson’s and related diseases, and to make connections to clinical research no human possibly could. Hear Volz’s plans for finding cures for patient subgroups—and why she recommends wearing rollerblades in the lab.

Show notes

 

Conversation with Katharina Volz (0:53)

OccamzRazor is an AI-neuroscience startup focusing on treatments for Parkinson’s Disease (0:55)

What is the connection between AI and Parkinson’s disease? (1:14)

Why the “one solution fits all model” is a fallacy (2:31)

The problem with the breakthrough mentality (6:12)

PubMed is a search engine for scientific research (9:01)

Why is Parkinson’s disease OccamzRazor’s first focus? (14:48)

 

Eyeroll, please (20:10)

“Move fast and break things” (20:39)

The Unscaled podcast series is about how economies of scale have changed (22:55)

 

Listener question (26:39)

I was elated that my most recent question read on the AT podcast revealed Phil’s 3 design principles. I wonder, however, if there should be another principle added to the three: decision criteria auditability.

Examples: an AI was trying to identify which dogs were wolves, and when researchers looked into the AI’s decision-making criteria, they realized the AI’s primary differentiating criterion was whether or not there was snow in the background of the image.
So what do you think of auditability as a fourth design principle for AI?

 

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