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How machine learning can change the way we all look at cannabis

May 8, 2019

Machine learning is more than just a pair of Google glasses or a self-driving car. It is quickly integrating itself into many consumer industries, and cannabis is just the latest market to tap into the potential of machine learning technology.

What does machine learning mean to cannabis?

Machine learning is a specific pattern of algorithms used by computers to automate tasks. It is a kind of Artificial Intelligence that helps systems learn on their own but cannot improve upon itself like AI does. What machine learning does is simplify and automate tasks on its own.

Namaste Technologies Inc. (OTC:NXTTF) is one of the latest cannabis stocks to hop on this growing tech trend. Last week, the company acquired Findify, an e-commerce platform that uses machine learning to build consumer profiles and improve search results for cannabis users shopping online. According to the press release, the platform has already helped Namaste improve its product recommendations and will eventually evolve to create a more customized experience for shoppers.

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“We are thrilled to apply [Findify’s] deep A.I. expertise to cannabis,” said Laurens Feenstra, Director of Namaste. “There are approximately 800 identified strains of cannabis, each with hundreds of active ingredients, meaning each plant works differently for each person. Understanding which plant works for whom will be key in helping cannabis benefit everyone.”

With a product as medically diverse as cannabis, machine learning makes it easier for companies and consumers to understand the kind of cannabis they are growing and consuming. Just as cultivators use machine learning technology to manage light and color spectrums while they grow, they can use the same tech to test the potency of the very plant they are growing.

The latest developments in cannabis machine learning

The team at HiGrade developed an application that will test exactly that. The cannabis analytics app launched this month and is already being called the “Shazam of weed” for its uncanny ability to tell the potency of your marijuana just by a picture. More than that, the app reports back who is asking the questions and why, giving the team at HiGrade a broader look at consumer trends in the cannabis market.

“A label on a bag is useless,” said Assaf Gavish, Chief Scientist at HiGrade, the canna-tech company using machine learning to help consumers and cultivators test the potency of their product. “[Potency] is the easiest thing for us to normalize and so are the consumption trends. Our algorithms are being improved based on the needs of the market. This way, the market allows consumers to be connoisseurs.”

As a snapshot, Assaf told PotNetwork News that Canadian consumers are two times more likely to test the potency of their products than Americans. In Holland, tokers have higher potency requests than anyone else in Europe, while Swedes are looking for more high-CBD strains than any other country. Understanding disparities like these can help cannabis companies across the globe hone in on their niche or even rebrand themselves according to their local markets.

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Cultivators, too, can use this app. While consumers are the primary focus for HiGrade’s potency tools, Assaf noted that over the past six months, more and more cultivators are starting to use the potency app on top of asking their common harvesting and grow questions.

“Cultivators have much broader needs,” Assaf explained. “They can actually ask whatever questions they have, but since they ask so many questions, it can’t all be automated.”

For consumers, the algorithm in the potency app is completely automated and can garner a response in under fifteen seconds. But for cultivators, the algorithm is semi-automated. A human being fills in any blanks by examining photos, asking more questions, and finally curates an answer based on the specific needs of the cultivator who’s doing the asking.

But potency is becoming a bigger topic on everyone’s mind in the industry. Consumers with specific medical needs want to know if and how a certain strain of marijuana will work for them. Cultivators need a tool they can trust to measure potency accurately in order to keep up with state and city-wide regulations. HiGrade’s tool delivers on both groups’ needs, giving Assaf and his team an optimistic look at the future of the market.

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“People will start to get educated and understand that the variability of the plant is so high,” Assaf said. “They are caring more about what they consume, are getting more acquainted with cannabis, and they can now predict their high by testing it first.”

The role machine learning plays in the personal ways consumers and cultivators both interact with cannabis will only continue to evolve as the needs of the market get more and more complicated. From online shopping to potency testing, technology is at the forefront of almost every facet of the cannabis industry. And where the actors in this industry have the opportunity to influence its evolution, machine learning will be the most important tool in their kit.

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