Technology moves at breakneck speed and Artificial Intelligence (A.I.) is fast turning out to be an integral part of the technology world – influencing the way we live and interact, much like electricity did a century ago.
With A.I. emerging from sci-fi movie plots and most recently appearing in mainstream headlines as the heart of highly anticipated new tech innovations, such as driverless cars and robots – it’s easy to see why many of us are not aware that A.I.-based algorithms and models are already highly ingrained in our everyday lives.
We’ve rounded up 5 examples of A.I. you’re already using – right now!
Depending on how autopilot is defined, A.I. has been automating flights dating as far back as 1914. The New York Times reported that a human pilot only spends 7 minutes on average steering a typical Boeing plane, mainly during takeoff and landing!
Not surprisingly, ride-sharing apps used on a daily basis, like Uber, operate with machine learning algorithms too. Uber uses data from its 5 billion logged trips to learn where optimal pickup locations are, determine the price of your ride, and make accurate estimated time of arrival (ETA) taking into account traffic congestion and routes.
Ever wonder why when you upload photos to Facebook, it identifies your friend’s faces and suggests whom to tag? Well, Facebook uses A.I. to recognize faces, with an outstanding 97% accuracy rate! Well trained with a dataset of 4 million+ facial images, the network uses a 9-layer deep neural network with 120 million+ parameters for its facial recognition feature.
Similarly, relevant, personalized content and adverts appearing on your Facebook newsfeed and Instagram stories are driven by Facebook’s algorithms. They work behind the scenes to identify patterns and the probability you will comment or like on something similar based on the content you have interacted with previously.
In Your Inbox
Your inbox doesn’t seem like a place for A.I., but it’s a key feature in making your life easier when you navigate through hundreds of unread emails in the morning. Standard rule-based filters that filter out messages containing certain terms aren’t entirely effective, as spammers can shift and update their content to work around these rules. Instead, spam filters that use machine learning algorithms continuously learn from a number of signals, such as message metadata (origin of the sender etc.), words contained in the message, and of course your definition of what constitutes as spam.
Using a similar approach, Gmail’s algorithms categorize your emails into ‘Primary’, ‘Promotion’ and ‘Social’ inboxes. So remember, every time you highlight an email as ‘important’, Gmail learns and adapts!
Apps and streaming services like Spotify and Netflix are great at recommending playlists- and yes, it’s because of their extensive machine learning algorithms behind recommender systems! By understanding what movies you like based on previous films or shows you’ve awarded high ratings on, it identifies your taste and makes recommendations that you are likely interested in.
Online retail giants like Amazon shape customer experience and optimize their inventory by applying machine learning to their recommendation systems. You might often see product recommendations, such as “customers who viewed this item also viewed” and “customers who bought this item also bought”, as well as personalized product recommendations via email. These are all generated by Amazon’s artificial neural networks that automatically learn from your Amazon searches (‘food processor’, ‘waterproof speaker’, etc.) and recent purchases that feed into their algorithms to power personalized experiences.
Leave us a comment on any other examples of A.I. popping up in your everyday life, we’d love to know them! As always – make sure to subscribe to our blog & follow us on Facebook, Twitter, LinkedIn, Instagram and Kickstarter page for all updates!