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Louis-François Bouchard에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Louis-François Bouchard 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.
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The Role of Data in Advancing AI: Insights from Expert Jerome Pasquero

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Manage episode 396945382 series 3496315
Louis-François Bouchard에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Louis-François Bouchard 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.

A new episode with Jerome Pasquero, a Machine Learning Director at Sama, a leading company for data annotation solutions, where we dive into the role of data in AI's evolution. We explore the nuances of data annotation, the ethical implications of data in AI, and how data is shaping the future of technology. Don't miss Jerome Pasquero's insights on the intersection of data and AI!

►Jerome Pasquero: https://www.linkedin.com/in/jeromepasquero/

►Twitter: https://twitter.com/Whats_AI

►My Newsletter (My AI updates and news clearly explained): https://louisbouchard.substack.com/

►Support me on Patreon: https://www.patreon.com/whatsai

►Join Our AI Discord: https://discord.gg/learnaitogether

Timestamps:

00:00:00 Coming up in the conversation

00:01:34 Jerome shares about his background

00:04:07 How did Jerome get into the data field?

00:05:23 AI back in the days of 2000s

00:07:20 Back then, what piqued Jerome's interest the most in AI?

00:08:40 Using AI to try to mimic human comprehension

00:12:47 Present challenges and the prospective outlook of computer vision

00:14:54 Using Humans vs. ML Models to Annotate Data

00:17:46 Jerome's perspective on Constitutional AI or RLAIF

00:24:52 Impact of LLM and AI on the Job market

00:26:27 Is the AI revolution bigger than previous tech revolutions?

00:28:35 Will there be something more interesting than AGI?

00:31:15 Dealing with complex annotation tasks and different perspectives

00:33:33 Dealing with biases

00:36:18 Using a single annotator vs. multiple annotators on the same data

00:37:49 Synthetically generated data

00:40:47 Scaling quality assurance for large datasets

00:42:46 When is machine learning better at annotation than human annotators?

00:45:34 Reduction of Humans-in-the-loop due to the constant evolution of AI

00:46:42 Data Requirements for Training Autonomous Vehicles

00:51:43 Sensors for transferring human driving skills to Autonomous cars

00:53:20 Why don’t we build only autonomous subway system?

00:55:26 Use of AI in the vision industry and example of vision technology used in our daily life

01:00:17 The potential of haptics and its link with AI

  continue reading

33 에피소드

Artwork
icon공유
 
Manage episode 396945382 series 3496315
Louis-François Bouchard에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Louis-François Bouchard 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.

A new episode with Jerome Pasquero, a Machine Learning Director at Sama, a leading company for data annotation solutions, where we dive into the role of data in AI's evolution. We explore the nuances of data annotation, the ethical implications of data in AI, and how data is shaping the future of technology. Don't miss Jerome Pasquero's insights on the intersection of data and AI!

►Jerome Pasquero: https://www.linkedin.com/in/jeromepasquero/

►Twitter: https://twitter.com/Whats_AI

►My Newsletter (My AI updates and news clearly explained): https://louisbouchard.substack.com/

►Support me on Patreon: https://www.patreon.com/whatsai

►Join Our AI Discord: https://discord.gg/learnaitogether

Timestamps:

00:00:00 Coming up in the conversation

00:01:34 Jerome shares about his background

00:04:07 How did Jerome get into the data field?

00:05:23 AI back in the days of 2000s

00:07:20 Back then, what piqued Jerome's interest the most in AI?

00:08:40 Using AI to try to mimic human comprehension

00:12:47 Present challenges and the prospective outlook of computer vision

00:14:54 Using Humans vs. ML Models to Annotate Data

00:17:46 Jerome's perspective on Constitutional AI or RLAIF

00:24:52 Impact of LLM and AI on the Job market

00:26:27 Is the AI revolution bigger than previous tech revolutions?

00:28:35 Will there be something more interesting than AGI?

00:31:15 Dealing with complex annotation tasks and different perspectives

00:33:33 Dealing with biases

00:36:18 Using a single annotator vs. multiple annotators on the same data

00:37:49 Synthetically generated data

00:40:47 Scaling quality assurance for large datasets

00:42:46 When is machine learning better at annotation than human annotators?

00:45:34 Reduction of Humans-in-the-loop due to the constant evolution of AI

00:46:42 Data Requirements for Training Autonomous Vehicles

00:51:43 Sensors for transferring human driving skills to Autonomous cars

00:53:20 Why don’t we build only autonomous subway system?

00:55:26 Use of AI in the vision industry and example of vision technology used in our daily life

01:00:17 The potential of haptics and its link with AI

  continue reading

33 에피소드

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