New Age Artificial Intelligence for Cannabis Production?

Published on: 
Cannabis Science and Technology, May 2021, Volume 4, Issue 4
Pages: 33-36

As globalization of demand for cannabis and its derivative products increase, new technology and artificial intelligence solutions can greatly boost the output of production and processing.

As artificial intelligence is introduced to many industries and applications,
cannabis productions stands to benefit. As globalization of demand for cannabis and its derivative products increase, new technology solutions can greatly boost the output of production and processing.

In Johannesburg South Africa graduate researchers at the University of the Witwatersrand (Wits) apply bioscience algorithms and artificial intelligence (AI) to cultivate high-yielding cannabis crops. They utilize lighting systems controlled by AI to combine with closed-loop hydroponics, combined with specialized organic fertilizer to use less resources to produce greater yields (1).

Becoming Artificially Intelligent

Cannabis is entering the age of high-tech agribusiness. Artificial intelligence employs sophisticated algorithms that compute aggregated granular data. Such computation helps predict, plan, automate, integrate, and apply scientific thinking for agribusiness growers of all types of crops, including cannabis. 

Syngenta Crop Protection (2), for example, is partnering with AI and deep learning company Insilico Medicine to develop innovations in crop protection solutions against diseases, weeds, and pests, while concurrently protecting the ecosystems in which they dwell. New, fast, and efficient solutions for farmers translates to a boost in productivity, lower costs, and the ability to meet an emergent demand—especially for the cannabis industry.

AI is also used at the molecular level. The company
efficacyAI recently began a collaboration with Georgia Tech Research Corporation to use their licensed algorithms for an AI software platform called MedicascyAI (3). This platform uses the input of the chemical structure of small molecules to make accurate predictions about the safety and efficacy of the molecule’s use for targeted indications. 

“We are excited about making this new technology widely available to anyone who can benefit from it in today’s evolving drug discovery marketplace,” said Tony Bellezza, CEO of MedicascyAI in a released statement (3). Belleza specified that using the platform “provides a cost-effective methodology to quickly identify molecules with high value predictions to pursue, or invest in, at the very beginning of the drug discovery or product development lifecycle. We plan to use MedicascyAI’s analytical capabilities to accelerate life-changing solutions and to transform the way pharmaceutical, nutraceutical, supplement, and cannabis companies develop their products.” This could be a huge leap for the future of cannabis production.


A New Face of Efficiency in Growing and Production

Michael Cammarata is the president and CEO of Neptune Wellness Solutions in Jupiter, Florida. He explained that AI will permeate the cannabis industry, just as it has in much of agribusiness. Cammarata expects that AI will insert the same innovation that is catapulting many industries with predictive analytics and efficiency in operations. 

“These applications are the next step for the industry,” said Cammarata. “AI and cloud computing will allow all of the different attributes of a cannabis-based business, to merge into one. Not only will production and logistics be revolutionized but it will reset the way the cannabis industry thinks about marketing and relationships with our customers.”

Cammarata added that as AI applications used via cloud-computing and software-as-a-service (SaaS) products become more widely available, much work will be performed by machine learning at a pace and level that exceeds what the human mind can accommodate. 

“The implementation of cloud-based applications, SaaS applications, and various AI, and data analytic platforms will fundamentally change the structure of the industry,” he said. “It will create a flat cannabis company structure by eliminating the manager. These technologies will effectively become the managers. They will have the ability to tap into market data in real time. The tech will see which SKUs are performing, what products are selling and will have the decision-making power to adjust production accordingly. It will be the best logistics partner because with the public databases available it can predict dramatic weather changes. It will allow companies to find issues with third party suppliers before being notified or adjust to geopolitical events resulting in an automatic reroute of the shipped product. The ability to complete 40 different tasks simultaneously and shift strategy in real time is all within the latest science.”

Eagle Eye Networks is a firm that provides video surveillance solutions for cannabis production firms. They use a cloud-based video management system (VMS) to aggregate data analytics related to cannabis growing.

“The most effective AI for the cannabis market is functionality that extends over the greatest group of users,” said Dean Drako, the president and CEO of Eagle Eye Networks. “The security analytics of line crossing, advanced motion, and people counting, are proven and widely applicable for numerous use cases today. The cannabis industry will be in the forefront of the next generation of widely applicable analytics. Many of the advances will come from regulatory requirements, while others will be driven by business needs such as recognition of people, things, and events that are still primarily focused on security.”

Drako adds that the next wave of AI is being driven by an urgency to create a cannabis industry that is most efficient and effective, as well as safe and secure. “The growing demand from businesses and greater supply from companies now offering AI is quickly coming together to move those applications to the mainstream,” he said. “Specifically, the need for recognition-oriented AI is growing in critical infrastructure for production, transportation, and retail as the industry moves to improve efficiency and safety of manpower, reduce shrinkage, accelerate incident resolution, and meet or exceed regulatory requirements across multiple jurisdictions.”

Rise to the Occasion of Available Opportunities

Drako explained that a remote production facility
might be plagued by false alarms from animals intruding into protected spaces, for example. He perceives cloud-based surveillance as a viable option for many in the cannabis industry.

“The ever-changing environment and need of cannabis businesses to monitor and maintain multiple locations and surveil people and product during transportation makes it the most cost-effective and viable solution,” Drako added. “True cloud [and] video-as-a-service (VSaaS) offerings enable ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (for example, networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. Making them ideal for the industry from 'seed to sell.'”

As cannabis production grows, so will the drive to find opportunities to help accelerate its growth. In a recent report (4), Deloitte set the table of opportunity as one that smart leadership will be ready and open to digital innovations such as AI, where industry growth may accelerate, stating: “The globalization of cannabis is inevitable. The question will be, which leaders are capable of rising to the challenge and making the most of available opportunities. Cannabis companies that are able to professionalize and establish brand recognition as legitimate, trustworthy players in the market are those that will survive and grow in the long term.”



About the Author

JIM ROMEO is a contributing writer focused on business and technology topics. He covers robotics, automation, and all things tech. Direct correspondence to:

How to Cite this Article

J. Romeo, Cannabis Science and Technology 4(4), 33-36 (2021).