Are recent developments in AI anything new?

What has been is what will be, and what has been done is what will be done, and there is nothing new under the sun – Ecclesiastes 1:9, King James Bible

The modern practice of AI is not new. Most of these techniques were developed in the 1960s and 1970s and fell out of favor because the computing machinery of the day was insufficient for the complexity of software or the number of calculations required. They only waited for computers to get bigger and for another very significant event – the invention of the internet. In previous decades, if you needed 10,000 digitized pictures of cats to compile a database to train a neural network, the task would be almost impossible – you could take a lot of cat pictures, or scan images from books. Today, a Google search for cat pictures returns 126,000,000 results in 0.44 seconds. Finding cat pictures, or anything else, is just a search away, and you have your training set for your neural network – unless you need to train on a very specific set of objects that don’t happen to be on the internet, as we will see in this book, in which case we will once again be taking a lot of pictures with another modern aid not found in the sixties, a digital camera. The happy combination of very fast computers, cheap, plentiful storage, and access to almost unlimited data of every sort has produced a renaissance in AI.

Another modern development has occurred on the other end of the computer spectrum. While anyone can now have what we would have called a supercomputer back in 2000 on their desk at home, the development of the smartphone has driven a whole series of innovations that are just being felt in technology. Your wonder of a smartphone has accelerometers and gyroscopes made of tiny silicon chips called Micro-Electromechanical Systems (MEMS). It also has a high-resolution but very small digital camera and a multi-core computer processor that takes very little power to run. It also contains (probably) three radios – a Wi-Fi wireless network, a cellular phone, and a Bluetooth transceiver. As good as these parts are at making your iPhone fun to use, they have also found their way into parts available for robots. That is fun for us because what used to be only available for research labs and universities is now for sale to individual users. If you happen to have a university or research lab or work for a technology company with multi-million-dollar development budgets, you will also learn something from this book, and find tools and ideas that hopefully will inspire your robotics creations or power new products with exciting capabilities.

Now that you’re familiar with the concept of AI for robotics, let’s look at what a robot actually is.