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Food Made Simple: AI vs Machine Learning

At Journey Foods, we know there’s a better way to approach the future of food. We’re an AI-powered platform that supports product management and data services to help thousands of food businesses save money and create better products efficiently. We’ve sold several thousand units of our inaugural data-driven product line, Journey Bites, with more than 1 million cubes manufactured, which supports our machine learning-based algorithms.

It seems like every year there’s a new set of buzz words you just can’t seem to get away from. This year, those words seem to be ‘machine learning’ and ‘artificial intelligence’. Everybody seems to be taking a stance on the topic, from saying AI is going to take all of our jobs to say AI is the key to our future. Despite all the talk, people still seem to be confused about these terms or are at least misusing them.

AI and Machine learning are integral to Journey Foods, so it’s fair to say we know a thing or two. We know that food systems and the evolving tech scene are complex, and we think the conversation about the relationship between artificial intelligence and food needs to be louder.

That conversation won’t be productive if everyone doesn’t understand the basics, so let us explain:

‘Artificial intelligence’ and ‘machine learning’ actually refer to two separate, albeit related, things. While all machine learning is AI, not all AI is machine learning. (Sometime’s it’s deep learning, symbolic logic, etc. But we won’t get into that right now.)

The most basic definition for artificial intelligence comes from the godfather of AI himself and states that it’s “the science and engineering of making intelligent machines”. The process of machine learning, or ML, is a subset of AI that involves training a piece of software to make useful predictions using data. Basically, it’s a long process of running continuous experiments until the software does what you need it to do.

The Machine Learning Process

An example of machine learning you’ve probably heard before is YouTube’s “Watch Next” feature which used a system that predicts which video a user will like and then recommends it to them. For Journey Foods, we use machine learning to optimize data services and product management software to food companies. This massively cuts down on the research and development time spent making new and nutritious food for people like you (and like us!)

This is a very rapidly moving field, with 77% of consumers already using an AI powered service or device while 31% of companies planning to incorporate AI within the next year. (AKA, you’re going to need to learn and talk about these things more and more).

Infographic from TechJury
It’s hard to make predictions about the state of the art 6 months from now, let alone 15–20 years from now. One thing we can predict (because it won’t change) is the core of artificial intelligence: solving problems and humans.

Neither artificial intelligence nor machine learning can exist without humans. As scary as AI might sound to some, the “intelligent” part is in reference to human intelligence. Human’s can identify problems, such as the excessive time product development takes, but they can’t always solve those problems on their own. The goal is to make machines that can do tasks requiring human intelligence that might be too hard or too time-consuming for people to reasonably do.

The food industry is one that might benefit the most from the growth and development of AI.
Sample machine learning process for food category identification

These intelligent machines and machine learning programs can and will be used to solve a variety of problems in the world. From monitoring crop fields, supply chain management, product development, delivery, to restaurant cooking, there is room for intervention at every stage before the food actually enters your hands. As the world population hurtles towards 9 billion, AI and machine learning will also be used by companies like Journey Foods to enhance and increase the nutrition density of food to support the health and wellness of all these new humans.

We see the rise of this “new” tech to be full of promise for everyone, especially when specifically used for good. Now that you understand what the difference between AI and ML is, you can go out and start finding companies creating solutions to your everyday problems with it.