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How does AI fit into cannabis cultivation?

In a clandestine, 40,000-square-foot cultivation facility in northern Arizona, we met with the founders of CEAD, Royce Birnbaum and Adam Klaasmeyer, a company that develops artificial intelligence applications for the cannabis industry.

These two are no strangers to innovation. Birnbaum, the lead back-end developer for the project, has had a career in developing systems for monitoring nuclear reactors for the Navy and AI technology for the defense industry, while Klaasmeyer, the front-end developer and coder, has contributed to projects for companies such as Atari and Microsoft.

The CEAD technology currently being tested at a cannabis research and development center in Arizona monitors operational and environmental systems including plant nutrition, growth rates, life cycles, and predictive pest outbreaks. In addition, it keeps a log of all movements made by the cultivation team and gathers data in regards to specific feeding and pruning schedules.

The machine learning capabilities take advantage of all of the data to continually expand its knowledge base. Initially, the AI system operates off of base assumptions. At the point the machine begins to learn all operational aspects of the cultivation, it then begins to present and suggest a list of options to the cultivator to prevent potential forecasted issues based on the data.


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