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Announcing Plant-Based Machine Learning

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Around this time last year, we announced that we’d expanded our AI and ML capabilities to pets, truly making machine learning paw-ssible for anyone, regardless of whether you’re human or not.

And while we were proud of that effort, some of us wondered if we could go further. There are, after all, other groups of living creatures on this planet. Although we initially considered an expansion into the fungal kingdom, early experiments only resulted in a lot of moldy circuit boards.

But we didn’t let that stop us! We kept working at it, and this year, we’re excited to continue expanding the reach of AI and ML by providing members of the plant kingdom with the ability to run their own machine learning models, using the cloud-based infrastructure of RapidMiner Go. We were so pleased with how much we’ve expanded machine learning beyond humans that we went so far as to revise our understanding of our mission statement:

Our new toolset is based on a proprietary, state-of-the-art plant/computer interface called Lexical-Epicotyl Access for Plants and Herbs (LEAPH) that our green friends can use to access the Internet to find data and then use RapidMiner Go to build and train models.

Let’s take a look at a few of the plants that we worked with during prototyping to give you a sense of the kinds of models that plants might be interested in building and how they can use this technology to have a positive impact on our world.

Potato (Solanum tuberosum)

Potatoes get a bad rap—carbophobes hate them, they’re not infrequently forgotten in a bottom drawer where they turn into brown slush, and they’re even the butt of internet jokes, comparing them to crummy cameras and computers.

But with LEAPH, they can fight back against their haters! Using RapidMiner Go, our resident potato plants were able to build a model that could detect negative sentiment about potatoes on various websites and forums. Their next step is to build a model that can respond to try and discourage people from saying things like photos have “potato quality”.

So if you see anyone complaining about language that’s disparaging to potatoes online, you’ve probably run into the first potato-built sentiment analysis and influencer bot.

Avocado (Persea americana)

Avocados are superstars of the produce aisle—high in healthy fats, great on toast, and popular at parties in the form of guacamole.

But avocados have their problems, too. No avocado wants to be purchased only to be taken home and tossed in the trash when its all-too-short eating window comes and goes without anyone taking notice. This is especially concerning to the avocados since their unpredictable ripening times drive up costs for end consumers, potentially impacting their popularity and thus the number of avocados grown each year.

With our LEAPH interface, a grove of avocado trees was able to model the development of their fruits—including subjective measures like “how brown under the skin are they” and “do they have any of those weird thread things” that’s inaccessible to us humans on the outside—and try to create a model that lets people know when the avocados are ready to be eaten.

Unfortunately, initial testing didn’t result in a model that was able to accurately predict when an avocado was ripe with better than chance accuracy. However, the avocado trees are hopeful that they’ll eventually crack their own code, providing more predictability about their ripeness, and in turn, driving down costs so that restaurants can stop charging extra for guac.

Kale (Brassica oleracea)

Kale has exploded in popularity in the last decade or so, and we have no idea why—and neither does kale! With LEAPH and RapidMiner Go, kale was able to plumb the Internet to look for evidence and chart its rise to health-food hero. Although celebrity endorsements seem to have played a role, the main driver is that people love to talk about how health they are on social media. Since eating kale is seen as a key part of a healthy lifestyle, more social media has driven more kale sales.

And the kale ain’t complainin’!

Wrapping Up

These are just a few examples of the kinds of impacts that RapidMiner can have when it puts the power of AI and ML in anyone’s hands—even plants. We’re excited to see what other plants come up with as we roll out our LEAPH interfaces in the coming weeks.

Our new plant-based options are sure to rock the machine learning world to its roots, as is our new slogan: RapidMiner Go: literally so easy a potato can do it.

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Chris Doty

Chris Doty

Chris has a PhD in linguistics, and has previously worked on ML projects for Amazon's Alexa. As RapidMiner's Content Marketing Manager, he works to evangelize for the power of AI and ML to upskill and empower people in a changing world. When he isn't working, he enjoys learning languages and drawing.