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Ep 27: Oscar Co-Founder Mario Schlosser on How LLMs Can Be Used in Healthcare Today and The Path to AI Doctors

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Content provided by Redpoint Ventures and By Redpoint Ventures. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Redpoint Ventures and By Redpoint Ventures or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.

Oscar Health is a $4B public healthcare company, providing healthcare insurance to nearly 1 million members. Oscar is at the forefront of AI adoption, continuously developing new AI use cases in healthcare. On this week’s episode of Unsupervised Learning, we sat down with Oscar Health Co-Founder, former CEO, and now President of Technology Mario Schlosser to talk about where AI will have the biggest impact in healthcare, top AI use cases at Oscar today, AI adoption challenges Oscar is facing, and limitations of GPT-4 in healthcare. Mario also shared his takes on open-source vs. off-the-shelf vs. healthcare-specific LLMs, and why can't we have robot doctors today.

(0:00) intro

(1:26) how will AI change healthcare in the next decade

(9:29) how Oscar uses AI

(19:00) how to build around healthcare requirements

(26:06) when would GPT-4 fail "miserably" and fundamental limitations of LLMs

(36:48) we shouldn’t piss off our smartest robots

(38:35) sharing AI knowledge between companies

(42:10) developing healthcare-specific models

(44:55) hackathons and karaoke nights at Oscar

(49:27) the need for a safety layer in LLMs

(51:53) best commercial opportunities in healthcare

(55:39) will their be AI doctors this decade?

(59:38) over-hyped/under-hyped

With your co-hosts:

@jacobeffron

- Partner at Redpoint, Former PM Flatiron Health

@patrickachase

- Partner at Redpoint, Former ML Engineer LinkedIn

@ericabrescia

- Former COO Github, Founder Bitnami (acq’d by VMWare)

@jordan_segall

- Partner at Redpoint

  continue reading

49 episoade

Artwork
iconDistribuie
 
Manage episode 400755733 series 3495253
Content provided by Redpoint Ventures and By Redpoint Ventures. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Redpoint Ventures and By Redpoint Ventures or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.

Oscar Health is a $4B public healthcare company, providing healthcare insurance to nearly 1 million members. Oscar is at the forefront of AI adoption, continuously developing new AI use cases in healthcare. On this week’s episode of Unsupervised Learning, we sat down with Oscar Health Co-Founder, former CEO, and now President of Technology Mario Schlosser to talk about where AI will have the biggest impact in healthcare, top AI use cases at Oscar today, AI adoption challenges Oscar is facing, and limitations of GPT-4 in healthcare. Mario also shared his takes on open-source vs. off-the-shelf vs. healthcare-specific LLMs, and why can't we have robot doctors today.

(0:00) intro

(1:26) how will AI change healthcare in the next decade

(9:29) how Oscar uses AI

(19:00) how to build around healthcare requirements

(26:06) when would GPT-4 fail "miserably" and fundamental limitations of LLMs

(36:48) we shouldn’t piss off our smartest robots

(38:35) sharing AI knowledge between companies

(42:10) developing healthcare-specific models

(44:55) hackathons and karaoke nights at Oscar

(49:27) the need for a safety layer in LLMs

(51:53) best commercial opportunities in healthcare

(55:39) will their be AI doctors this decade?

(59:38) over-hyped/under-hyped

With your co-hosts:

@jacobeffron

- Partner at Redpoint, Former PM Flatiron Health

@patrickachase

- Partner at Redpoint, Former ML Engineer LinkedIn

@ericabrescia

- Former COO Github, Founder Bitnami (acq’d by VMWare)

@jordan_segall

- Partner at Redpoint

  continue reading

49 episoade

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