The Internet, or search engines to be more precise, has developed a stunningly revolutionary and equally complex network at its core; something not very different from the complex neural network of the human brain. While the brain is an incredibly complex network of neurons, the internet is an incredibly complex network of computers with billions of websites attached to them. And search engines perform the herculean task of finding content relevant to your search query from this tangled haystack.
From the first-born Archie (the very first search engine) to the omniscient Google, search engines have come a long way from archived indexes of FTP servers to AI powered beasts. What started as a primitive and limited listing of file links to your query has now become a context sensitive, keyword sensitive and domain sensitive result to your search that also adapts to your preferences – with each passing day! At the center of this shift is AI or Artificial Intelligence, the attempt to match machine intelligence with human intelligence; and fundamental to AI is machine learning – a term that is pretty self-explanatory (automated data-analysis that enables machines to ‘learn’ from the immense amount of data fed to them). Machine learning (ML) not only lets machines learn, but also to adapt through these lessons. To make a very complex topic simple, machines are taught to recognize patterns from large amounts of data. As new data comes in, they are able to apply what was learned from previous data to this new set and produce reliable results, over and over again.
Believe it or not you are using ML in almost every aspect of your daily life, right from transportation (in apps like Uber and Ola) to your financial dealings (in every online transaction you make). But no one else has explored the true possibilities of ML or AI like search engines and online platforms. Google for instance uses ML in every aspect of its business. It is ML that has resulted in the efficiency of email spam filtration, the precision of Google Maps, the accuracy of Google Assistant and the reliability of Google Search, all of which are still on a growth curve. It is ML that recognizes faces from images (remember how Facebook brings up tag-suggestions in pictures?). It is ML that brings up ads of stuff that you wanted to buy, the very next day after you browsed through them and decided against buying. It is ML that brings up shopping suggestions and combo suggestions in online shopping portals (“Customers who bought this also bought”).
The future of ML holds infinite possibilities. Imagine smart email responses; this has already started with customized reply options to mails in your inbox. Imagine a shopping experience tailor-made to your needs and preferences. Imagine a virtual personal assistant like Jarvis (refer to Iron Man – the movie) who can answer all your queries, save all your daily agendas and remind you of them, open the door for you, drive your car for you and do so much more. And just so you know, Jarvis has already been built and is being developed further, credits to Mark Zuckerberg.
So the future you see in Sci-Fi movies is already here. Just brace yourselves for the impact.