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Carbon Robotics built an AI model that detects and identifies weeds and plants

A model that learns any plant on sight lets farmers ditch herbicides and retraining for instant, targeted weeding.

Key takeaways

  • What is and isn’t a weed that needs to be eliminated in the field is determined by the eyes of the farmer — and now, increasingly, by a new Artificial Intelligence (AI) model from Carbon Robotics.
  • The LPM is trained on more than 150 million photos and data points collected by the company’s machines across the more than 100 farms in 15 countries where the robots currently operate.
  • Carbon Robotics has raised more than $185 million in venture capital from backers including Nvidia NVentures, Bond, and Anthos Capital, among others.
Cite or link to this article

Griffin, M. (2026) 'Carbon Robotics built an AI model that detects and identifies weeds and plants', 311 Institute, 9 April. Available at: https://www.311institute.com/carbon-robotics-built-an-ai-model-that-detects-and-identifies-weeds-and-plants/ (Accessed: 1 October 2026).

What is and isn’t a weed that needs to be eliminated in the field is determined by the eyes of the farmer — and now, increasingly, by a new Artificial Intelligence (AI) model from Carbon Robotics.

Seattle-based , which builds the LaserWeeder — a robot fleet that uses lasers and not increasingly expensive herbicides to kill weeds — announced a new AI model, the Large Plant Model (LPM), on Monday. This model recognises plant species instantly and allows farmers to target new weeds without needing to retrain the robots.

The LPM is trained on more than 150 million photos and data points collected by the company’s machines across the more than 100 farms in 15 countries where the robots currently operate. The model now powers Carbon AI, the AI system that serves as the brains inside the company’s autonomous weed-killing robots.

Paul Mikesell, the founder and CEO of Carbon Robotics, told reporters that prior to LPM, every time a new type of weed would show up on a farm — or even the same type of weed in different soil or with a slightly different appearance — the company would have to create new data labels to retrain its machines to recognise the plant.

This process took about 24 hours each time, Mikesell said. Now, LPM can learn a new weed instantly, even if it’s never seen it before.

“The farmer can live in real time and say, ‘Hey, this is a new weed. I want you to kill this,’ and that was something that had never been done before,” Mikesell said. “There’s no new labelling or retraining because the Large Plant Model understands, at a much deeper level, what it’s looking at and the type of plant.”

Mikesell said that the company, which was founded in 2018, started developing this model shortly after it began shipping its first machines in 2022. Mikesell has years of experience building these types of neural networks from previous roles at Uber and working on Meta’s Oculus virtual reality headsets.

This new model will reach the company’s existing systems through a software update. From there, farmers can tell the machine what to kill and what to protect by selecting photos that the machine has collected in the robot’s user interface.

Carbon Robotics has raised more than $185 million in venture capital from backers including Nvidia NVentures, Bond, and Anthos Capital, among others. Now, the company will look to continue to fine-tune the model as the machines continue to feed the LPM new data.

“We have over 150 million labelled plants now in our training set,” Mikesell said. “We have enough data now that we should be able to look at any picture and decide what kind of plant that is, what species it is, what it’s related to, what its structure is like, without having ever even seen that particular plant before, because we have so much data going into the neural net.”


FAQ

Why does instant plant recognition matter for farming?

Until now, every new weed, or even a familiar weed in different soil, meant a roughly 24-hour cycle of relabelling and retraining before the machines could act. A model that generalises to plants it has never seen removes that bottleneck, so farmers can point at something in the field and have the robots act immediately, cutting both herbicide use and downtime.

Matthew Griffin

About the author

Matthew Griffin Founder, 311 Institute

Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath."

Read full bio

Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath." 15-time best selling author of the "Codex of the Future" series, Matthew is the Founder and Futurist in Chief of the 311 Institute, a global Futures and Deep Futures advisory firm working with royal households, world leaders, G7, G20, and G77 governments, NGOs, and multi-national mid and mega cap firms to help them explore, shape, and lead the next 50 years of business and society.

An award-winning YouTube creator with over a million followers, with an unrivalled global reach and impact, Matthew is a highly sought-after international keynote speaker, lecturer, and mentor who collaborates with global leaders through the United Nations Alliance of Civilizations (UNAOC) and United Nations General Assembly (UNGA) to shape pivotal initiatives such as the UN’s AI for Humanity program, the United Nations Conference of the Parties (UN COP), and the World Economic Forum in Davos.

As the former Global Head of Cloud, National Security, and Enterprise Sales for companies including Atos, Dell-EMC, and IBM, Matthew has a proven track record of building multi-billion dollar business units and turning failing divisions into market leaders. His ability to identify, analyse, and communicate the implications of hundreds of emerging technologies and trends is unparalleled, and his insights are trusted by many of the world’s most respected organisations, including ABB, Accenture, Adidas, AON, ARM, BCG, Centrica, Citi, Coca-Cola, Dentons, Deloitte, Dow Jones, EY, Google, KPMG, Lego, Legal & General, LinkedIn, Microsoft, PepsiCo, Qualcomm, RWE, Samsung, Siemens AG and Siemens Energy, T-Mobile, UBS, VISA, Walmart, Workday, Worldpay and many others.

Regularly featured in the global media including the AP, BBC, Bloomberg, CNBC, Discovery, Forbes, Khaleej Times, Telegraph, TIME, ViacomCBS, WIRED, and the WSJ, Matthews mission is to help organisations create a fair and sustainable future whose benefits are shared by everyone irrespective of their ability, background, or circumstances.

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Sources and further reading

  1. Carbon Robotics carbonrobotics.com

Source: first published by the 311 Institute on 9 April 2026. Cite as: Griffin, M. (2026). Carbon Robotics built an AI model that detects and identifies weeds and plants. 311 Institute. https://www.311institute.com/carbon-robotics-built-an-ai-model-that-detects-and-identifies-weeds-and-plants/

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