The use of AI and machine learning in agriculture is growing, with 87% of US agriculture businesses using some form of AI as of 2021. The technology is used to process vast amounts of data about everything from microclimate to soil pH, helping farmers make more informed decisions about when and how to apply resources like water and pesticides. However, there are concerns about potential drawbacks, including security threats, labor and inequality issues, and the need for rural broadband connectivity. Despite these challenges, AI is seen as a powerful tool for making agriculture more sustainable and efficient.
Key takeaways:
- Gilwoo Lee, a robotics expert, and Casey Call, a sixth-generation farmer, founded Zordi, an agricultural platform that combines AI, robotics, and greenhouse growing to tackle climate change and improve farming efficiency.
- Zordi uses robots to plant and harvest strawberries in greenhouses, while AI and machine learning monitor the growing process and control the environment. The company is backed by Khosla Ventures.
- AI and machine learning are increasingly being used in sustainable agriculture to manage vast amounts of data, improve yields, and make farming more efficient and sustainable. This includes precision farming, predictive analytics, and smart decision-making.
- While AI and machine learning offer significant benefits, they also pose potential risks, including unexpected results without human supervision, security threats, labor and inequality concerns, and issues of data ownership. Despite these challenges, AI is seen as a powerful tool to help agriculture adapt to climate change, resource scarcity, and increased global food demand.