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Data-Centric AI with Alex Ratner

50:19
 
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Manage episode 375510040 series 1437556
Data Archives - Software Engineering Daily에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Data Archives - Software Engineering Daily 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Companies have high hopes for Machine learning and AI to support real-time product offerings, prevent fraud and drive innovation. But there was a catch – training models require labeled data that machines can digest. As data volumes increase, the opportunity to get great ML results rises, but so does the problem of labeling all the data to get that excellent result.

Enter Snorkel AI’s programmatic data labeling and MLops platforms like Snorkel Flow. Today we are interviewing Alex Ratner, one of the founders of Snorkel AI. Snorkel AI evolved from research Alex led as part of his Ph.D. research at Stanford, focused on programmatic data labeling to enable much faster and more accurate ML training and retraining.

Alex is a born teacher who always has enthusiasm for the topic. Today he will share the newest evolutions of the product at Snorkel, shed light on why doing ML well requires programmatic data labeling, and talk about foundation models in actual enterprise settings and generally.

Starting her career as a software developer, Jocelyn Houle is now a Senior Director of Product Management at Securiti.ai, a unified data protection and governance platform. Before that, she was an Operating Partner at Capital One Ventures investing in data and AI startups. Jocelyn has been a founder of two startups and a full life cycle, technical product manager at large companies like Fannie Mae, Microsoft and Capital One. Follow Jocelyn on LinkedIn or Twitter @jocelynbyrne.

Sponsorship inquiries: [email protected]

Please click here to view this show’s transcript.

The post Data-Centric AI with Alex Ratner appeared first on Software Engineering Daily.

  continue reading

228 에피소드

Artwork
icon공유
 
Manage episode 375510040 series 1437556
Data Archives - Software Engineering Daily에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Data Archives - Software Engineering Daily 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Companies have high hopes for Machine learning and AI to support real-time product offerings, prevent fraud and drive innovation. But there was a catch – training models require labeled data that machines can digest. As data volumes increase, the opportunity to get great ML results rises, but so does the problem of labeling all the data to get that excellent result.

Enter Snorkel AI’s programmatic data labeling and MLops platforms like Snorkel Flow. Today we are interviewing Alex Ratner, one of the founders of Snorkel AI. Snorkel AI evolved from research Alex led as part of his Ph.D. research at Stanford, focused on programmatic data labeling to enable much faster and more accurate ML training and retraining.

Alex is a born teacher who always has enthusiasm for the topic. Today he will share the newest evolutions of the product at Snorkel, shed light on why doing ML well requires programmatic data labeling, and talk about foundation models in actual enterprise settings and generally.

Starting her career as a software developer, Jocelyn Houle is now a Senior Director of Product Management at Securiti.ai, a unified data protection and governance platform. Before that, she was an Operating Partner at Capital One Ventures investing in data and AI startups. Jocelyn has been a founder of two startups and a full life cycle, technical product manager at large companies like Fannie Mae, Microsoft and Capital One. Follow Jocelyn on LinkedIn or Twitter @jocelynbyrne.

Sponsorship inquiries: [email protected]

Please click here to view this show’s transcript.

The post Data-Centric AI with Alex Ratner appeared first on Software Engineering Daily.

  continue reading

228 에피소드

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