How does that sentence even make sense? See the funny thing, and the most frustrating thing to me in talking about Machine Learning, is that the use cases are limitless.

Here’s one that I learned about recently. If you feed an ML model a picture of a plant, and then track it over time, indico.io can watch it grow and tell you how big it’s getting!

Why is this useful? Think of all of the effort that goes into our plants… food, or otherwise. To me and you, fresh parsley just shows up at Whole Foods. It’s like *magic*. But in digging into it, on average, parsley takes about three weeks to grow. Those three important weeks mean the difference between a garnish or a bland looking chicken breast. We need parsley, guys.

So how does this work exactly? And why do farmers/agricultural-s need indico and machine learning? Okay, so round some parts, people are paid to manually watch over said plants. Every day at incremental times. Measure, look for faults, sad sprouts, etc. Now let’s say you set up a webcam to look over the parsley. Our imaging technology can now see and measure these same variables as a person can. The computer can track actual growth, nuances, while constantly monitoring for specific things you’re looking for.

Now, you’re saying what I said. “That’s fking crazy.” Yeah, it is. BUT with machine learning it’s very much do-able. They also have drones that fly over large fields to take imaging of large crops. What is a person going to actually watch that again? Well, I mean they get paid to, so yeah. All I know is that I never watched my 12th birthday video again.

So many things! Use cases! Words!!

Oh, for my next one, we’ll talk about content filtering featuring isitporn.com.

Email me at julie@indico.io. Please. No one ever does and I love to talk.