A lot of the buzz swirling around artificial intelligence and machine learning is that it is the technology of the future. While it is true that both AI and ML are both being rapidly developed, the fact of the matter is that they are both widely used today. In fact, you have most likely encountered one of them or both without even knowing. Today, we decided to shed some light on the AI and ML technologies we encounter every day.
A lot of people rely on Google maps to get them to work on time or simply how to get from Point A to Point B, but few suspects that the app is powered by AI algorithms. In fact, Google Maps relies heavily on AI to determine the estimated time of arrival, traffic delay time and factoring in unexpected delays such as accidents and construction. Google maps received a big boost after it acquired Waze, a crowdsourced traffic app, in 2013. This allowed them to better estimate the traffic flow which would determine the optimal route to take in order to get to your destination on time.
We all love to use ridesharing apps like Uber and Lyft, but did you know that they run on AI? Have you ever thought about how they calculate the price of the trip or how they minimize the time you have to wait for the car to reach your location? All of this is done with the help of machine learning. Uber uses to predict the user demand for rides during rush hour and other peak usage times and includes a price surcharge as well as for many other details involved in hailing a ride. In fact, Uber uses ML algorithms for additional services that it offers such as food delivery with UberEats.
Whenever we get on a flight, w are greeted by the pilot over the intercom who tells us about the time of the trip and whether any turbulence will be expected. However, thanks to AI the pilot’s job is much easier. In fact, the pilot only has to steer the aircraft for seven minutes, which done only during takeoff and landing, according to data from Boeing. This is a great example of how AI is keeping us safe while reducing the number of hours humans have to work.
Have you wondered why certain emails get caught by the spam filter? The reason is that AI algorithms scan the email content for specific keywords which are common to most spam messages. These can include words such as “One-time offer” or messages that come from an unknown origin. Moreover, the AI algorithms behind the spam filters are constantly learning in order to adapt to the new tactics used by the scammers in order to catch them before the email gets to you. In fact, such spam detection has been used to almost perfection by Google. The industry giant reports filtering out 99.99% of spam messages.
Grading and Assessment
A lot of students, faculty, and staff know about products such as Turnitin, which is a popular tool used by teachers to check for plagiarism. Such services rely on machine learning in order to search a huge database of texts to find similarities which could be classified as plagiarism. Also, the system goes even further and scans even work in other languages as well. Also, it is interesting how such plagiarism detectors work. They realize that using solely machines or humans is not effective because machines can notice some similar text, but it might not be plagiarism in reality. Therefore it provides teachers with the original sources where it found the similarity and lets people make the final decision.
Glimpse Into the Future
AI technology is being rapidly developed and its usage is expected to be either adopted or perfected across industries. For example, if we take a look at the first example involving daily commutes, the development of self-driving cars will further shorten the commute time because they will there will be fewer accidents, thus causing fewer delays and will reduce the sheer quantity of vehicles on the road by as much as 75% according to research by MIT. if we look at the plagiarism checker, it will be able to find more matches as far as ideas are concerned. Plagiarism is not simply copying the text, but rather ideas and the plagiarism checker will be better able to such incidents.
Even though artificial intelligence and machine learning are fairly common nowadays, we have only scraped the surface of its potential. There are certain industries that have constant contact with AI that are beyond the scope of this article. For example, chess players constantly play against AI-powered engines because these machines always make the best possible moves and know all of the combinations and variations played to date. Therefore, these engines can be used for honing the skills of the chess players and trying to find new moves and combinations that have not been played yet to see what the best move against such an idea would be.
For the business world, AI means more engagement. AI algorithms will be able to learn about the content each individual user prefers, be it a video, movie or article and the system will provide more personalized recommendations. In fact, companies like YouTube, Netflix, and Facebook have already started incorporating AI into their service offerings. This means that businesses will need to start investing in AI and adapting it for their specific business ventures in order to get a competitive advantage. Business across industries are using AI to improve their service offering and build relationships with clients, therefore, if you are not using AI, you risk falling behind the competition.