How Sama is Improving ML Models to Make AVs Safer // Duncan Curtis // #307

How Sama is Improving ML Models to Make AVs Safer // Duncan Curtis // #307

Author: Demetrios April 18, 2025 Duration: 45:34

How Sama is Improving ML Models to Make AVs Safer // MLOps Podcast #307 with Duncan Curtis, SVP of Product and Technology at Sama.


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// Abstract

Between Uber’s partnership with NVIDIA and speculation around the U.S. President Donald Trump enacting policies that allow fully autonomous vehicles, it’s more important than ever to ensure the accuracy of machine learning models. Yet, the public’s confidence in AVs is shaky due to scary accidents caused by gaps in the tech that Sama is looking to fill. As one of the industry’s top leaders, Duncan Curtis, SVP of Product and Technology at Sama, would be delighted to share how we can improve the accuracy, speed, and cost-efficiency of ML algorithms for ​A​Vs. Sama’s machine learning technologies minimize the risk of model failure and lower the total cost of ownership for car manufacturers including Ford, BMW, and GM, as well as four of the five top OEMs and their Tier 1 suppliers. This is especially timely as Tesla is under investigation for crashes due to its Smart Summon feature, and Waymo recently had a passenger trapped in one of its driverless taxis.


// Bio

Duncan Curtis is the SVP of Product at Sama, a leader in de-risking ML models, delivering best-in-class data annotation solutions with our enterprise-strength, experience & expertise, and ethical AI approach. To this leadership role, he brings 4 years of Autonomous Vehicle experience as the Head of Product at Zoox (now part of Amazon) and VP of Product at Aptiv, and 4 years of AI experience as a product manager at Google, where he delighted the +1B daily active users of the Play Store and Play Games.


// Related Links

Website: https://www.sama.com/

Tesla is under investigation: https://www.cnn.com/2025/01/07/business/nhtsa-tesla-smart-summon-probe/index.html

Waymo recently had a passenger trapped: https://www.cbsnews.com/losangeles/news/la-man-nearly-misses-flight-as-self-driving-waymo-taxi-drives-around-parking-lot-in-circles/

https://coruzant.com/profiles/duncan-curtis/

https://builtin.com/articles/remove-bias-from-machine-learning-algorithms

Look At Your ****ing Data :eyes: // Kenny Daniel // MLOps Podcast #292: https://youtu.be/6EMnkAHmoag


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Connect with Luca on LinkedIn: /duncan-curtis


Timestamps:

[00:00] Duncan's preferred coffee

[00:08] Takeaways

[01:00] AI Enterprise Focus

[04:18] Human-in-the-loop Efficiency

[08:42] Edge Cases in AI

[14:14] Forward Combat Compatibility Failures

[17:30] Specialized Data Annotation Challenges

[24:44] SAM for Ring Integration

[28:50] Data Bottleneck in AI

[31:29] Data Connector Horror Story

[33:17] Sama AI Data Annotation

[37:20] Cool Business Problems Solved

[40:50] AI ROI Framework

[45:11] Wrap up


Hosted by Demetrios, MLOps.community is a space for honest, meandering talks about the real work of making artificial intelligence systems actually work. This isn't about hype or theoretical papers; it's about the messy, practical, and often surprising journey of taking models from a notebook into a live environment. You'll hear from engineers and practitioners who are in the trenches, discussing the tools, the frustrations, and the occasional breakthroughs that define the day-to-day. The conversations are deliberately relaxed, covering everything from traditional machine learning pipelines to the new world of large language models and even the intangible "vibes" of team culture and process. Each episode peels back a layer on what "production" really means, whether that involves deploying a predictive service, managing an agentic system, or maintaining reliability as everything scales. Tuning into this podcast feels like grabbing a coffee with colleagues who aren't afraid to dig into the technical nitty-gritty while keeping the tone conversational and accessible. It's for anyone who builds, manages, or is just curious about the operational backbone that allows AI to deliver value, offering a grounded perspective often missing from the broader conversation.
Author: Language: en-us Episodes: 100

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