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Subvolts take Waymo's research chief details building and testing AI drivers for safe, real-time autonomous vehicles. Nov 13, 2025
For you
Developers
Learn about the research challenges and testing methodologies for building robust AI drivers.
Business
Understand the technological hurdles and safety considerations in deploying autonomous vehicle systems.
Hype note
3/5Notable

A solid interview with a research leader from a prominent autonomous vehicle company, discussing core development challenges.

Practical AI
Practical AI · Ep 336 Episode

Autonomous Vehicle Research at Waymo

52 min Interview Hosts: Daniel Whitenack, Chris Benson
0:0052:08

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From Subvolts

Summary and analysis by Subvolts editorial, AI-assisted.

Summary

Waymo's VP of Research, Drago Anguelov, joins Practical AI to discuss autonomous vehicle development. The episode explores how advances in autonomy, vision models, and large-scale testing shape driverless technology. Anguelov details the challenges of building an onboard driver and testing it through simulation, while ensuring safety and reliability for intelligent, real-time performance.

Explained simply

This episode explains how Waymo builds and tests the AI that drives cars. They discuss using computer vision and running millions of simulated miles to make sure the self-driving system is smart and safe for everyone.

Why listen

This episode offers insight into the complex research behind Waymo's autonomous driving efforts. It's for engineers and AI enthusiasts interested in the practical application of large-scale testing and vision models in real-world AI systems. The discussion on building and testing AI drivers connects to current frontier lab work in developing robust, safe AI for critical applications, highlighting the immense simulation and data needs.

On the mic
  • HostDaniel Whitenack
  • HostChris Benson
  • GuestDrago AnguelovVP of Research, Waymo
About
ResearchSafetyModels
Key facts
  • Guest: Drago Anguelov, VP of Research at Waymo
  • Show: Practical AI
  • Length: 52 minutes
  • Topics Discussed: Autonomy, vision models, large-scale testing, onboard driver development, simulation testing, safety, reliability
Key moments and transcript

Chapters from the publisher ↗ · Transcript ↗ Key moments and transcript search come with a later piece.

Show notes from Daniel Whitenack and Chris Benson

Waymo’s VP of Research, Drago Anguelov, joins Practical AI to explore how advances in autonomy, vision models, and large-scale testing are shaping the future of driverless technology. The conversation dives into the dual challenges of building an onboard driver and testing that driver (via large scale simulation). Drago also gives us an update on what Waymo is doing to achieve intelligent, real-time performance while ensuring proven safety and reliability.

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Jargon decoded
vision models
Drago Anguelov
AI systems that help computers 'see' and understand images or video.
onboard driver
Drago Anguelov
The AI system that controls the vehicle's driving functions.
large-scale simulation
Drago Anguelov
Running many computer-generated driving scenarios to test the AI extensively.
Published
Show
Practical AI · Daniel Whitenack and Chris Benson
Length
52 min
Summary by
Subvolts, using an AI model (how we work). Spotted a mistake? Tell us.
#Research#Safety#Models

Best of Practical AI

Questions people ask

What are the main challenges in autonomous vehicle research?
The episode discusses the dual challenges of building an onboard AI driver and rigorously testing that driver through large-scale simulation.
What is Waymo's focus for driverless technology?
Waymo aims for intelligent, real-time performance while ensuring proven safety and reliability in their autonomous vehicles.

Page generated Oct 19, 2026. Summaries are Subvolts' own; the audio, artwork and notes belong to Daniel Whitenack and Chris Benson.