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Artwork for Eye On A.I.

Eye On A.I.

Craig S. Smith
Artificial Intelligence
Machine Learning
Generative AI
Oracle Cloud Infrastructure
Large Language Models
Openai
Natural Language Processing
Multi-Agent Systems
AI Research
Cloud Computing
Reinforcement Learning
Agentic AI
Customer Service
Google Cloud
Deep Learning
Biotechnology
Unstructured Data
Open Source
Robotics
Software Development

Eye on A.I. is a biweekly podcast, hosted by longtime New York Times correspondent Craig S. Smith. In each episode, Craig will talk to people making a difference in artificial intelligence. The podcast aims to put incremental advances into a broader context and consider the global implications of the developing technology. AI is about to change your world, so pay attention.

PublishesTwice weeklyEpisodes335Founded8 years ago
Number of ListenersCategory
Technology

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Artwork for Eye On A.I.

Latest Episodes

What if the country that produces the world's top AI talent finally figured out how to keep it?

In this episode of Eye on AI, Craig Smith sits down with Professor Mausam, one of India's leading AI researchers, AAAI Fellow, and founding head of the ... more

YouTube

Why IBM Is Betting Everything on Small AI Models

In this episode of Eye on AI, Craig Smith sits down with Sriram Raghavan, Vice President of AI at IBM Research, to explore one of the most important debates in enterprise AI right now. Do you actuall... more

YouTube

What if the country that trained the world's engineers finally decided to keep them?

In this episode of Eye on AI, Craig Smith sits down with Abhishek, the civil servant leading India's $1.2 billion national AI Mission, to explore how one of the wo... more

YouTube

Most enterprises are excited about agentic AI. But very few are actually deploying it in production.

In this episode of Eye on AI, Craig Smith sits down with Adi Kuruganti, Chief AI and Development Officer at Automation Anywhere, to break down why ... more

YouTube

Key Facts

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Recent Guests

Dan Faulkner
CEO of SmartBear
SmartBear
Episode: #332 Dan Faulkner: The Code Is Clean. The App Is Broken. Why AI Development Has an Integrity Problem
Sebastian Risi
Researcher associated with Sakana, focusing on plasticity of networks, neuroevolution, and open-ended AI
Sakana
Episode: #330 Sebastian Risi: Why AI Should Be Grown, Not Trained
Izhar Medalsy
Co-founder and likely CEO of Quantum Elements
Quantum Elements
Episode: #329 Izhar Medalsy: How AI Solves Quantum Computing's Biggest Problem
Kevin Tian
Co-founder and CEO of Doppel
Doppel
Episode: #328 Kevin Tian: Exploring Doppel's AI-Native Social Engineering Defense Platform
Baris Gultekin
Head of Product for AI at Snowflake
Snowflake
Episode: #327 Baris Gultekin: The Next Phase of AI - Agents That Understand Your Company's Data
Zuzanna Stamirowska
Co-founder and CEO of Pathway/BDH researcher
Pathway
Episode: #326 Zuzanna Stamirowska: Inside Pathway's Post-Transformer Architecture Designed for Memory and On-the-Fly Learning
Phelim Brady
Co-founder and CEO of Prolific
Prolific
Episode: #325 Phelim Brady: Why AI's Future Depends on Human Judgement
Sharon Zhou
Vice President of AI at AMD
AMD
Episode: #324 Sharon Zhou: Inside AMD's Plan to Build Self-Improving AI
David Ha
Co-author and researcher focused on evolutionary AI and Sakana AI
Sakana AI
Episode: #323 David Ha: Why Model Merging Could Be the Next AI Breakthrough

Host

Craig S. Smith
Host and longtime New York Times correspondent who engages with experts making significant contributions to the field of artificial intelligence.

Reviews

4.7 out of 5 stars from 109 ratings
  • Ahead of the curve

    After each podcast I feel well informed. More than just surface level highlighting of latest developments, it presents case studies on how to think about AI.

    Apple Podcasts
    5
    987362847
    United States2 months ago
  • Featuring insightful conversations

    An insightful podcast that makes complex AI topics accessible and easy to understand. It is a a great listen for anyone interested in the future of technology.

    Apple Podcasts
    5
    SM405
    United Statesa year ago
  • Fantastic podcast…

    Review: bamdiggity!

    Apple Podcasts
    5
    Info_Sprinkles
    United States2 years ago
  • Game-Changing! Redefining the AI Landscape

    Craig's guests are seriously rocking the tech scene, flipping the script on what it means to be a techie in this AI-dominated industry! Packed with all the classic elements that make an AI show absolutely informative, plus that extra dash of authenticity and insight you won't get anywhere else. Big shoutout to you, Craig—your show is absolutely fantastic, keep up the awesome work! 🚀

    Apple Podcasts
    5
    Linda__Lee_
    Philippines2 years ago
  • Well researched, great quality guests and calm, level headed interviewing

    Just what I was looking for.

    Apple Podcasts
    5
    josepcpea
    United States3 years ago

Listeners Say

Key themes from listener reviews, highlighting what works and what could be improved about the show.

Insightful conversations that simplify complex AI topics, making them accessible to a general audience.
Listeners appreciate the level of expertise from guests and the engaging interview style.
There are mixed reviews regarding production quality, with some praising the content while others mention editing issues.

Chart Rankings

How this podcast ranks in the Apple Podcasts, Spotify and YouTube charts.

Apple Podcasts
#104
United States/Technology
Apple Podcasts
#147
United Kingdom/Technology
Apple Podcasts
#120
Australia/Technology
Apple Podcasts
#222
Germany/Technology
Apple Podcasts
#31
South Korea/Technology
Apple Podcasts
#80
Denmark/Technology

Talking Points

Recent interactions between the hosts and their guests.

#331 Sergey Levine: The Robot Revolution Nobody Is Talking About
Q: Do world models have a place alongside VLAs in robotic systems?
Yes, the best approach is a spectrum of abstractions where world-model-like prediction and model-free policies are combined. The system should smartly choose the right abstraction for the task, leveraging each approach where it makes sense.
#331 Sergey Levine: The Robot Revolution Nobody Is Talking About
Q: How do you balance simulation and real-world data in building these models?
Simulation is great for controlled scenarios and edge cases, but real-world data is crucial for generalization. The plan is to use simulation to fill gaps while prioritizing real data collection from a variety of robots to drive broad understanding and then use simulation to address rare or dangerous events.
#331 Sergey Levine: The Robot Revolution Nobody Is Talking About
Q: What does it mean today to have robotic foundation models and how do you source data for them?
Foundation models in robotics are trained on broad, diverse embodied data rather than a single robot, enabling the model to generalize across morphologies. Data comes from a mix of teleoperation, real-world robot deployments, diverse robot platforms, and eventually more autonomous supervision as capabilities improve.
#330 Sebastian Risi: Why AI Should Be Grown, Not Trained
Q: So maybe you can start by explaining what neuroevolution is in AI.
Neuroevolution combines evolutionary algorithms with neural networks, optimizing not just weights but also architecture, learning rules, and hyperparameters. It uses evolution to explore many candidate networks and select the best, enabling continual learning and adaptation without requiring differentiability or backpropagation.
#329 Izhar Medalsy: How AI Solves Quantum Computing's Biggest Problem
Q: Where do you see quantum computing hitting practical utility in the next few years?
Progress will be incremental and often hybrid: improvements in noise handling, larger qubit counts, and efficient logical qubits will come together to enable practical benefits sooner, with quantum and classical components jointly driving acceleration rather than a single leap to full quantum supremacy.

Audience Metrics

Listeners, social reach, demographics and more for this podcast.

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Frequently Asked Questions About Eye On A.I.

What is Eye On A.I. about and what kind of topics does it cover?

Focused on the rapidly evolving field of artificial intelligence, this podcast features engaging conversations with industry experts, innovators, and researchers who are creating impactful AI technologies. By examining specific advances and their broader implications, the discussions often explore how AI is shaping various sectors like healthcare, finance, and customer service, alongside addressing ethical concerns and potential societal impacts. The unique approach involves a blend of technical insights and personal anecdotes, making complex topics accessible to both professionals in the field and general listeners interested in AI's future.

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Which podcasts are similar to Eye On A.I.?

These podcasts share a similar audience with Eye On A.I.:

1. Practical AI
2. Machine Learning Street Talk (MLST)
3. Latent Space: The AI Engineer Podcast
4. NVIDIA AI Podcast
5. No Priors: Artificial Intelligence | Technology | Startups

How many episodes of Eye On A.I. are there?

Eye On A.I. launched 8 years ago and published 335 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

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What guests have appeared on Eye On A.I.?

Recent guests on Eye On A.I. include:

1. Dan Faulkner
2. Sebastian Risi
3. Izhar Medalsy
4. Kevin Tian
5. Baris Gultekin
6. Zuzanna Stamirowska
7. Phelim Brady
8. Sharon Zhou

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