Artificial intelligence and machine learning are two streams of science that are changing by leaps and bounds every few weeks. With all that is happening with AI and the debate brought on by a recent incident between Google engineers Blake Lemoine and LaMDA (language model for dialogue application) we thought it might be a good idea to write AI and ML. If you have not heard about the conversation between Black and LaMDA you can read it in this tweet. We really cannot get over the emotional nature of the conversation and also the fact that LaMDA hired a lawyer to safeguard itself from any manipulations.

The History of Artificial Intelligence

So let’s look at the history of artificial intelligence, in 1943 while the second world war was raging and most of the world was experiencing its wrath of it 2 chaps Warren McCulloch and Walter pits were creating the first artificial neuron. This laid the foundation for what would go on to become artificial intelligence over the years. Then came Donald Hebb in the year 1949 with Hebbian Learning, the underlying theory of which is when our brain learns something new, neurons are activated and connect with new neurons to form a neural network.

The year after that came to our beloved Alan Turing who created the Turing test-(this whole bit is captured superbly in the movie imitation game, may we also say Benedict Cumberbatch was simply amazing). The Turing test basically is used to identify if a machine is capable of thinking like human beings. The next big leap in AI was when the logical theorist was created by Allen Newell, Herbert Simon, and Cliff Shaw. Logical Theorist proved 38 out of 52 theorems from the second chapter of Principia Mathematica (wow!! That is just 38 theorems more than us right now).

The Logical Theorist was actually able to deliver proofs in some cases that were more elegant and sophisticated than anything before. Over the years there have been quite a few great leaps in the AI sphere. Our favorite of them is when IBM AI computer Deep Blue defeated Kasparov (we love this not because it was a great step forward for AI, but because we are not the biggest fans of Kasparov). The terms like AI, big data, and deep learning have become quite widely used and more often abused. The reason why we said that they are abused is not that they are being used for harmful purposes but for their ostentatious use of day-to-day conversations.

Now let’s talk a little about machine learning (yes machine learning because the hope that humans will learn is diminishing). ML is a subset of AI and as a term, it was coined by Arthur Samuel an IBM engineer. It is really surprising that with so much done at IBM around AI and ML one would have expected them to lead the charge on real-life applications of ML & AI.

The real-life use of AI and ML is enormous, some real-life examples of AI in day-to-day life are the navigation maps, SIRI and ALEXA. We have from time to time stop and ponder about how much data these apps are processing and how much are they learning about us.