How to Use AI: A Google DeepMind's Perspective Titelbild

How to Use AI: A Google DeepMind's Perspective

How to Use AI: A Google DeepMind's Perspective

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This new episode of My Interface Podcast, featuring an interview with Ni Lao, an expert in machine learning and natural language understanding at Google DeepMind.

In an era where AI models are rapidly evolving, how do we distinguish between helpful tools and unreliable outputs? In this episode, Ni Lao joins hosts Yvonne and Mia to share his journey from electrical engineering to leading efficient model training at Google.

Ni explains the technical reality of AI hallucinations, the importance of deep theoretical foundations, and why he never trusts AI results without verifying the source. This conversation bridges the gap between high-level academic research and the practical challenges of managing complex production systems in the real world.


What You Will Learn

  • The Learning Paradox: Why AI can help you find what to read but can never replace the actual process of human learning.
  • Understanding Hallucinations: A deep dive into how probabilistic models "guess" information and why verifying sources is a non-negotiable skill.
  • Foundational Skills for the Future: Why statistics, coding, and hands-on project experience are the three pillars of a successful AI career.
  • The "Magic Desk" Vision: How the long-standing dream of instant knowledge access—dating back to the Manhattan Project—is finally becoming reality through AI.

Chapters

  • 00:00 Welcome to the Interface Podcast.
  • 00:33 Guest Introduction: Ni Lao’s background in machine learning and Google DeepMind.
  • 00:54 Academic Influence: From electrical engineering to robotics and AI.
  • 02:40 The Complexity of Large-Scale AI: Managing production systems and prioritizing knowledge.
  • 03:45 The Truth About Hallucinations: Why probabilistic models "fake" information.
  • 06:50 Essential Skills: Statistics, coding, and the feedback loop of projects.
  • 07:50 AI Ethics and Regulation: Protecting intellectual property in art and code.
  • 09:00 The History and Future of Information: From the Manhattan Project to AI-driven inference.
  • 10:50 Post-Interview Analysis: Collaboration, fact-checking, and human responsibility.


Quotes from the Episode

"AI can never replace the learning part. You have to do the learning by yourself, but it helps you to find stuff to read."


"For me, I don't trust any AI... I just treat them as a way to find sources of information. I will read the source by myself to verify that it's actually true."


"You need AI to help you understand the world... but still you need theory of how AI works. Statistics, coding, and also projects."


"Making decisions will be much faster now than before... what might need minutes or hours can be reduced to minutes or even seconds."


About the Hosts

Yvonne and Mia are high school sophomores on a mission to provide insights from top AI experts and entrepreneurs to help educate the next generation of innovators.


New episodes drop every Friday at 3:00 PM.

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