We all know that dogs are a man’s best friend, but has the world really come to this?

On a particularly blustery day in New York City, I found myself (as one with the income bracket of a writer sporadically does) on the Upper East Side, amidst tribes of cooler-than-thou high school students, dedicated dog walkers and women wearing hats that looked like a Shar-Pei had potentially suffered in the making of it.

Nonetheless, I braved the chilly air and found solace in the Cooper Hewitt Museum, the design institution that is part of the Smithsonian. Upon entering, visitors are greeted with a magic wand-looking pen tool, that serves as an interactive notekeeper for items you are interested in. “How innovative.” Perfect for a museum about innovation, am I right? With my magic wand in hand, I entered the Narnia of objects, with the first stop being an exhibition titled “Access and Ability.” Featuring “artifacts” designed for people with disabilities, I was surprised to find among the various innovations, a very cute-looking puppy that I instinctively wanted to pet. But I did not, for fear of being arrested, a la Ocean’s 12.

AI pioneer Frank Rosenblatt in his famous 1958 paper on perceptron, wrote that the physical connections of the nervous system are not identical and at birth, the construction of the most important networks is largely random. This was the early days of computational breakthroughs and the researchers were already hinting that it’s okay to be unorganised when it comes to machines.

Today, the success of deep learning approaches owes in large to the enhancements of neural networks over the years. These networks are built on rules which allow them to interact with other nodes within the network. The way a connection is established also has a say in the rate at which the network learns a certain task.