Artificial intelligence was officially founded as a discipline in 1956, and in the years since, it has experienced tremendous growth and development—allowing AI systems to do a lot more things in ways we could only just imagine in the past. Let’s take a look at some of the best applications of artificial intelligence in the world today.
Among the many applications of artificial intelligence these days, smartphone virtual assistants are definitely at the vanguard, since these are the types of AI people are familiar with the most. Examples of these are voice activated assistants like Siri on the Apple iPhone, Bixby on the Samsung Galaxy S8, and Cortana on Microsoft devices. As you may very well know, these personal assistants can perform tasks and services for the user, facilitating the use of device features that would take much longer to access without AI aid. These include reading emails and messages aloud, scheduling events, looking up and dialing contact details, performing internet searches, and other duties that were traditionally performed by actual personal assistants or secretaries.
In the future, smart personal assistants are likely to become more ubiquitous, especially in homes, where they can act as automation hubs for smart houses. There are already a few such AI technologies operating today, including the likes of Amazon Alexa on the Amazon Echo device, Siri on the Apple HomePod, and the Google Assistant on the Google Home device.
In a world that is slowly transitioning to value-based care—a healthcare delivery model where providers and compensated according to the quality of patient health outcomes—it is important for health payers, providers, and public health agencies to become more sophisticated when it comes to handling data. With the help of artificial intelligence solutions, it become possible for these organizations to sift through and analyze voluminous amounts of data, which they can then use to empower their policies and practices. What are the implications? Consider being able to detect healthcare fraud, reduce resource wastage, develop the best healthcare plans, improve population health, and even cure diseases. In short, health organizations are poised to benefit a lot.
The financial services sector is one of the most data-driven industries in the world, with financial organizations exchanging large amounts internal documents and customer transaction information on a daily basis. Because banks and other financial institutions are also confronted with numerous regulations and compliance standards, they should see to it that that they are not failing on their legal and institutional obligations.
By analyzing data with the proper artificial intelligence tools, financial organizations will be able to understand the risks, comply with regulations, and meet customer needs effectively. They’ll be able to perform specialized tasks, whether it’s building regulatory risk models or predicting and preventing criminal activities like fraud and money laundering.
Transportation and Navigation
Have you ever wondered how map services like Google Maps and Waze calculate the best routes from your location to a certain destination? Or how about the methods by which ridesharing applications like Uber and Lyft determine the price for your ride? If you guessed artificial intelligence and machine learning, then you are correct.
Google Maps, which acquired Waze from the Israeli company Waze Mobile in 2013, efficiently makes use of crowdsourced data from the latter in order to help commuters avoid traffic jams caused by roadwork, accidents, and other disturbances, while also providing estimated times of arrival. Uber, on the other hand, uses machine learning in its proprietary algorithms in order to predict which areas will have increased rider demands at which hours. This way, they are able to implement what they call surge pricing, a strategy in which ride prices are increased at certain locations and at certain hours in order to bring down rider demand while also encouraging more drivers to pick up riders from those locations.
Aviation has always been an early adopter of AI technologies, and autopilot systems are one of them. Autopilot is a technology employed to control the flight path of an aircraft without constant intervention by a human agent. Although an autopilot system is not a complete substitute for human operators, it does help them significantly by allowing them to place their attention on other important aspects of aircraft operations, whether it’s monitoring weather conditions or reviewing and configuring instruments.
Surprisingly, autopilot systems have been in existence since the 1912, when the Sperry Corporation developed the first aircraft autopilot technology. Modern aviation AI systems, however, are much more advanced and are powered by computers—from coupled autopilot systems and full authority digital engine control systems to more recent developments such as digital cockpit assistants and next-generation autoflight systems that use machine learning to mimic expert pilots.
Without a shadow of doubt, artificial intelligence and machine learning will become more important in our daily lives as these technologies advance. What sort of challenges do you think AI will solve in the future?