Learn more about AI and how to better leverage it. This podcast aims to share exciting discussions with AI experts to demystify what they do and what they work on. We will cover specific AI-related topics (e.g., ChatGPT, DALLE...) and different roles related to artificial intelligence to share knowledge from the people who worked hard to gather it. I also want to showcase these people's unique paths to get where they are as AI builders, experts, and users. From building to leveraging AI technologies. Owner of the What's AI channel on YouTube, co-founder of Towards AI, and ex-PhD at Mila.
https://www.louisbouchard.ai
episode 27: The Role of Data in Advancing AI: Insights from Expert Jerome Pasquero
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/
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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