AI and the Farm

Artificial Intelligence is so often referred to as the future. It’s already become the present. We experience it in our daily lives, perhaps without even knowing it. Artificial Intelligence, otherwise known as AI, is machine learning. Its robotics. Siri is AI. Alexa is AI. Netflix, Google Search and driverless cars are driven by AI. A true artificially-intelligent system is one that can learn on its own. True AI can improve on past iterations, getting smarter and more aware. It allows it to enhance its capabilities and knowledge.

This week I participated in a forum on Artificial Intelligence with some professors at Cal, my alma mater. Keep in mind, I was a History major. My constant quest for knowledge takes me to broad subjects with the goal of always trying to understand where we are, where we are going and, perhaps most importantly, the why and the how. Professor Ruzena Bajcsy was the first speaker. She has been studying AI for 60 years, and believes we are still in the very early days. Also speaking were Professor Joseph Gonzalez and Professor Dave Rochlin from the Haas Innovation Lab.

Professor Bajcsy said she and her colleagues, back in the 1960s, dreamed at the AI lab at Stanford about all of these innovations we have today. The computing power just didn’t exist back then. They didn’t have the Internet to enable it. It is massive data storage that makes it possible. The advancement of the cloud really catapulted it.

Professor Bajcsy’s life’s work is Physical Intelligence: How to interact. Building machines to help humanity. A key area where robots will play a growing role is in traditional manual labor. Robots are great at heavy lifting. They will also be useful in the military, fighting fires and disaster recovery, among so much more.

The longtime Cal professor says that human muscles are the engine that has been measured for AI movements: Stretching. Contracting. Measuring interactions of physical parameter for eventual machine control. Tight grip versus soft grasp. It seems so simple, but really matters. This will help develop a robot helping in the kitchen, for example.

There are different types of intelligent systems. They are generally categorized as simple models and complex models. To be effective and serve a purpose in the field, AI systems need to be fast, automatic, intuitive, and instinctive. A driverless car is a perfect example here. Lacking any of those qualities presents major danger.

A critical factor for the effectiveness of Artificial Intelligence is the need to secure and protect the data. It always needs to be verifiable. It often requires competing parties to collaborate around data. A common need and use is fraud detection within money transfers at banks and brokers.

The ethics of AI are a serious issue. They can certainly target or enable our inherent biases. It might be considered helpful when Amazon shows you similar items you might like to purchase based on past activity. But it can also work against us. This certainly takes place on social media and online searches. YouTube algorithms often recycle the same kind of programming and can trap users in a tangled web of bias.

Artificial Intelligence will find ways to solve our greatest challenges but also open up new opportunities. For example, look to the farm. Farming is a notoriously tough business. Between 2013 and 2016, American farmers and ranchers suffered a 45% decline in income. That was the largest since the Great Depression. That occurred at a time when the number of mouths to feed around the globe grew substantially.

The global population is estimated to increase by another 2 Billion by 2050, approaching 10 Billion people by then. Farmers around the world will have to grow about 70% more food than is currently produced to meet the demand. Farming could benefit from high-tech.

Enter AI. Microsoft is making a bet that the solution lies in technology. Microsoft’s FarmBeats program, which launched last year, is a multi-year effort to bring robust data analytics to agriculture. It takes vast amounts of data from farms and then uses Artificial Intelligence and machine learning to translate that data into insights for the growers.

For an industry that has been around for 12,000 years, there is a lot of unpredictability and imprecision in agriculture. Traditional farming came with a lot of guesswork. Low-tech is becoming high-tech. The goal with AI is to replace guesswork with data. Technology could help the farmer, but for years its adoption has been limited because farms don’t always have the necessary power, or Internet connectivity. Farmers might have also lacked the technological savvy. That is changing.

The FarmBeats project is building several unique solutions to solve these challenges using low-cost sensors, drones, and vision and machine learning algorithms. Microsoft is feeding it into cloud-based AI models to get a detailed picture of real-time conditions on the farm. Data-driven farming is here.

The International Food Policy Research Institute believes these AI tactics can increase farm productivity by as much as 67%. It is expected to also increase efficiencies and reduce the amount of resources required for a crop. Later on, the mission will likely transition to grow more nutritious food without harming the environment. Life on the farm is changing. Old MacDonald has gotten much more hip. Come to think of it, Old MacDonald might soon be a robot.

The future is now. Innovation reigns supreme. Artificial Intelligence is making it happen. It’s all very investable.

Have a nice weekend. We’ll be back, dark and early on Monday.


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