Building Defensible Healthcare AI Companies

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It's not to use a public LML and just hope that it won't have to be made too much. But having an open source, large language model and fine tune it with your own very high quality data is how we remove from just like text nodes towards more actual automations of lots of clinical tasks. And our job at AI has care of startups is to fine tune these terms. It's difficult. You need to, you need a very strong technical team and you need proprietary data sets. And you need to understand the users of the product to see what's working or not with them. I think this is the most. amazing.

Today, we’re excited to get to know Alexandre Lebrun, CEO and Cofounder of Nabla, a personalized AI assistant for doctors. Before founding Nabla, Alex was the Head of Engineering at Facebook AI research for almost four years, and is a seasoned entrepreneur, having sold his previous companies Wit.ai, an AI platform that makes it easy to build apps that understand natural human language, to Facebook in 2015 and VirtuOz, a customer service chatbot, to Nuance Communications in 2012.

In this episode, Alexandre shares his experiences after 22 years and founding 3 startups, why proprietary data is more important than ever for defensibility, tactics on GTM and customer focus specific to healthcare buyers, and opportunities and safety for generative AI in healthcare.