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Better EV Batteries with Jason Koeller from Chemix

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Manage episode 425317074 series 3401994
Content provided by Heather D. Couture. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Heather D. Couture or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Batteries are arguably the most important technological innovation of the century, powering everything from mobile phones to electric vehicles (EVs). Unfortunately, most batteries have a significant impact on the environment, requiring increasingly scarce and valuable resources to manufacture and typically not designed for easy repair, reuse, or recycling.

Today on Impact AI, I'm joined by Jason Koeller, Co-Founder and CTO of Chemix, to find out how his company is leveraging AI to create better, more sustainable EV batteries that could reduce our reliance on elements like lithium, nickel, and cobalt, all without compromising vehicle performance. For a fascinating conversation with a data-driven physicist working at the intersection of software, machine learning, chemistry, and materials science, be sure to tune in today!

Key Points:

  • Jason’s background in theoretical physics and how it led him to create Chemix.
  • Products and services offered by Chemix and the role that AI plays.
  • Four reasons that machine learning (ML) is at the core of everything Chemix does.
  • Unique challenges that their ML models need to contend with.
  • What goes into validating these models to ensure accuracy.
  • Why now is the right time for the technology that Chemix is developing.
  • Metrics for measuring the impact of a better EV battery.
  • Jason’s data-driven advice for leaders of AI-powered startups.
  • His “electrifying” vision for Chemix in the next three to five years.

Quotes:

“All data analysis and decision-making is automated by our AI system. This includes analyzing terabytes of battery test data each day.” — Jason Koeller

“Looking at broad trends, [electric vehicles (EVs)] and AI have both become [things] that people have been talking a lot more about in the past 10 years and even more so in the past four or five years, and that has happened simultaneously.” — Jason Koeller

“Why is everyone not buying an EV? It's largely because they're too expensive or because people are worried they're not charging fast enough or they don't hold enough range for long road trips. – Improving any one of these metrics would be a measure of impact.” — Jason Koeller

Links:

Jason Koeller on LinkedIn

Chemix

Chemix on LinkedIn

Resources for Computer Vision Teams:

LinkedIn – Connect with Heather.

Computer Vision Insights Newsletter – A biweekly newsletter to help bring the latest machine learning and computer vision research to applications in people and planetary health.

Computer Vision Strategy Session – Not sure how to advance your computer vision project? Get unstuck with a clear set of next steps. Schedule a 1 hour strategy session now to advance your project.

  continue reading

96 episodes

Artwork
iconShare
 
Manage episode 425317074 series 3401994
Content provided by Heather D. Couture. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Heather D. Couture or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Batteries are arguably the most important technological innovation of the century, powering everything from mobile phones to electric vehicles (EVs). Unfortunately, most batteries have a significant impact on the environment, requiring increasingly scarce and valuable resources to manufacture and typically not designed for easy repair, reuse, or recycling.

Today on Impact AI, I'm joined by Jason Koeller, Co-Founder and CTO of Chemix, to find out how his company is leveraging AI to create better, more sustainable EV batteries that could reduce our reliance on elements like lithium, nickel, and cobalt, all without compromising vehicle performance. For a fascinating conversation with a data-driven physicist working at the intersection of software, machine learning, chemistry, and materials science, be sure to tune in today!

Key Points:

  • Jason’s background in theoretical physics and how it led him to create Chemix.
  • Products and services offered by Chemix and the role that AI plays.
  • Four reasons that machine learning (ML) is at the core of everything Chemix does.
  • Unique challenges that their ML models need to contend with.
  • What goes into validating these models to ensure accuracy.
  • Why now is the right time for the technology that Chemix is developing.
  • Metrics for measuring the impact of a better EV battery.
  • Jason’s data-driven advice for leaders of AI-powered startups.
  • His “electrifying” vision for Chemix in the next three to five years.

Quotes:

“All data analysis and decision-making is automated by our AI system. This includes analyzing terabytes of battery test data each day.” — Jason Koeller

“Looking at broad trends, [electric vehicles (EVs)] and AI have both become [things] that people have been talking a lot more about in the past 10 years and even more so in the past four or five years, and that has happened simultaneously.” — Jason Koeller

“Why is everyone not buying an EV? It's largely because they're too expensive or because people are worried they're not charging fast enough or they don't hold enough range for long road trips. – Improving any one of these metrics would be a measure of impact.” — Jason Koeller

Links:

Jason Koeller on LinkedIn

Chemix

Chemix on LinkedIn

Resources for Computer Vision Teams:

LinkedIn – Connect with Heather.

Computer Vision Insights Newsletter – A biweekly newsletter to help bring the latest machine learning and computer vision research to applications in people and planetary health.

Computer Vision Strategy Session – Not sure how to advance your computer vision project? Get unstuck with a clear set of next steps. Schedule a 1 hour strategy session now to advance your project.

  continue reading

96 episodes

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