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NVIDIA AI Podcast

Carbon Robotics on a New Era of Farming with Robots and Sustainable Innovation - Ep. 270

34 min episode · 2 min read
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Carbon Robotics

Episode

34 min

Read time

2 min

Topics

Health & Wellness, Startups, Fundraising & VC

AI-Generated Summary

Key Takeaways

  • Laser weeding technology: AI vision systems identify weeds and direct lasers to destroy meristematic growth cells (plant stem cells), killing weeds without touching soil or using chemicals, while dead plant matter returns as fertilizer for crops.
  • Unexpected yield improvements: Eliminating herbicides, manual labor, and mechanical soil disturbance produced dramatic crop yield increases beyond initial projections, revealing how severely conventional weed control methods damage crop health and quality throughout the growing season.
  • Data flywheel advantage: Once machines reach market scale, continuous image uploads from deployed units create self-reinforcing training data growth, allowing Carbon Robotics to build the world's largest labeled agricultural image dataset for ongoing model improvements.
  • Modular autonomous systems: Carbon's unified AI architecture powers both laser weeders (6-60 foot widths) and retrofit autonomous tractor kits that use computer vision to detect furrows and navigate fields without GPS, enabling 24/7 operations without scaling labor.

What It Covers

Carbon Robotics founder Paul Mikesell explains how his company uses AI-powered lasers to destroy weeds without herbicides, having eliminated over 15 billion weeds across 100+ crops while improving yields and soil health.

Key Questions Answered

  • Laser weeding technology: AI vision systems identify weeds and direct lasers to destroy meristematic growth cells (plant stem cells), killing weeds without touching soil or using chemicals, while dead plant matter returns as fertilizer for crops.
  • Unexpected yield improvements: Eliminating herbicides, manual labor, and mechanical soil disturbance produced dramatic crop yield increases beyond initial projections, revealing how severely conventional weed control methods damage crop health and quality throughout the growing season.
  • Data flywheel advantage: Once machines reach market scale, continuous image uploads from deployed units create self-reinforcing training data growth, allowing Carbon Robotics to build the world's largest labeled agricultural image dataset for ongoing model improvements.
  • Modular autonomous systems: Carbon's unified AI architecture powers both laser weeders (6-60 foot widths) and retrofit autonomous tractor kits that use computer vision to detect furrows and navigate fields without GPS, enabling 24/7 operations without scaling labor.

Notable Moment

Mikesell reveals that approximately 90 percent of people currently have glyphosate (Roundup's active carcinogenic ingredient) detectable in their urine samples, positioning laser weeding as essential technology to end this multi-generational chemical exposure experiment.

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Episode Transcript

Hello, and welcome to the NVIDIA AI podcast. I'm your host, Noah Kravitz. The history of agriculture is closely intertwined with the history of weeds. As farms and farming techniques developed over human history, weeds evolved as well, adapting and thriving as farmers employed ever more rigorous weed management techniques from manual pulling to herbicides. Seattle, Washington based Carbon Robotics may have found a better way to weed through a combination of farm machinery, lasers, and AI. The company has destroyed more than 15,000,000,000 weeds on more than 100 crops to date without the use of herbicides. They were recently named CNBC's disruptor 50 list of innovative companies. They're actually in the top 20. And last fall, they closed a series d funding round whose investors included nVentures, NVIDIA's venture capital arm. Here to take us into the world of laser weeders and the future of farming is Paul Mikesell, founder and CEO of Carbon Robotics. Paul, welcome, and thanks for taking the time to join the NVIDIA AI podcast. Yeah. You bet. Thank you for having me. So let's start at the top. You had a impressive successful career as an engineer and an entrepreneur before founding Carbon. What inspired you to take on the fit of farming and technology and getting into this, this sector? Yeah. You know, so it really started when I was at Uber working on neural nets and AI systems for vision and perception. Okay. And what I was really excited about at the time as an as an engineer was the ways in which computers were being able to, for the first time ever, really understand the world around them. Mhmm. And so so through the use of neural nets and all these AI systems and, you know, this was back in the day when this stuff was all pretty new, and you wouldn't find, you know, thousands of people claiming to be AI AI experts at any, you know, at any random coffee shop or whatever. Right. And we were really I was really excited about the technology. And I found that in my in my career, whenever you get that level of excitement about something, you really have to dive in. Yeah. Because there's a good chance it might be the future. And so and so really just focusing on that stuff. And, you know, we were working on self driving cars and a bunch of other stuff at Uber, a bunch of very interesting problems. We were talking about global logistics in a broad sense, and that that was really a lot of what we were doing there beyond just the self driving car work. So, anyway, I got, I left I left Uber after the IPO and wanted to go do something new and interesting, and I met some farmers. And just nothing to do with technology. Actually, the first farmer I met, I actually sold him an airplane, and that was how that was where the connection came …

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