In the article below, you can check out twelve examples of AI being present in our everyday lives.
Artificial intelligence (AI) is growing in popularity, and it's not hard to see why. AI has the potential to be applied in many different ways, from cooking to healthcare.
Though artificial intelligence may be a buzzword today, tomorrow, it might just become a standard part of our everyday lives. In fact - it's already here.
They work and continue to advance by using lots of sensor data, learning how to handle traffic and making real-time decisions.
Also known as autonomous vehicles, these cars use AI tech and machine learning to move around without the passenger having to take control at any time.
Let's begin with something really ubiquitous - smart digital assistants. Here we are talking about Siri, Google Assistant, Alexa and Cortana.
We included them in our list because they can essentially listen and then respond to your commands, turning them into actions.
So, you hit up Siri, you give her a command, like "call a friend," she analyzes what you said, sifts through all the background noise surrounding your speech, interprets your command, and actually does it, all in a couple of seconds.
The best part here is that these assistants are getting smarter and smarter, improving every stage of the command process we mentioned above. You don't have to be as specific with your commands as you were just a couple of years ago.
Furthermore, virtual assistants have become better and better at figuring out filtering useless background noise from your actual commands.
One of the most well-known AI initiatives is a project run by Microsoft. It comes as no surprise that Microsoft is one of the top AI companies around (though it's definitely not the only one).
The Microsoft Project InnerEye is state-of-the-art research that can potentially change the world.
This project aims to study the brain, specifically the brain's neurological system, to better understand how it functions. The aim of this project is to eventually be able to use artificial intelligence to diagnose and treat various neurological diseases.
The college students' (or is it professor's?) nightmare. Whether you are a content manager or a teacher grading essays, you have the same problem - the internet makes plagiarism easier.
There is a nigh unlimited amount of information and data out there, and less-than-scrupulous students and employees will readily take advantage of that.
Indeed, no human could compare and contrast somebody's essay with all the data out there. AIs are a whole different beast.
They can sift through an insane amount of information, compare it with the relevant text, and see if there is a match or not.
Furthermore, thanks to advancement and growth in this area, some tools can actually check sources in foreign languages, as well as images and audio.
You might have noticed that media recommendations on certain platforms are getting better and better, Netflix, YouTube, and Spotify being just three examples. You can thank AIs and machine learning for that.
The three platforms we mentioned take into account what you have already seen and liked. That's the easy part. Then, they compare and contrast it with thousands, if not tens of thousands, of pieces of media. They essentially learn from the data you provide, and then use their own database to provide you with content that best suits your needs.
Let's simplify this process for YouTube, just as an example.
The platform uses data such as tags, demographic data like your age or gender, as well as the same data of people consuming other pieces of media. Then, it mixes and matches, giving you your suggestions.
Today, many larger banks give you the option of depositing checks through your smartphone. Instead of actually walking to a bank, you can do it with just a couple of taps.
Besides the obvious safeguards when it comes to accessing your bank account through your phone, a check also requires your signature.
Now banks use AIs and machine learning software to read your handwriting, compare it with the signature you gave to the bank before, and safely use it to approve a check.
In general, machine learning and AI tech speeds up most operations done by software in a bank. This all leads to the more efficient execution of tasks, decreasing wait times and cost.
And while we are on the subject of banking, let's talk about fraud for a little bit. A bank processes a huge amount of transactions every day. Tracking all of that, analyzing, it's impossible for a regular human being.
Furthermore, how fraudulent transactions look changes from day to day. With AI and machine learning algorithms, you can have thousands of transactions analyzed in a second. Furthermore, you can also have them learn, figure out what problematic transactions can look like, and prepare themselves for future issues.
Next, whenever you apply for a loan or maybe get a credit card, a bank needs to check your application.
Taking into account multiple factors, like your credit score, your financial history, all of that can now be handled by software. This leads to shorter approval wait times and a lower margin for error.
Many businesses are using AI, specifically chatbots, as a way for their customers to interact with them.
Chatbots are often used as a customer service option for companies that do not have enough staff available at any given time to answer questions or respond to inquiries.
By using chatbots, these companies can free up staff time for other tasks while still getting important information from their customers.
These are a godsend during heavy traffic times, like Black Friday or Cyber Monday. They can save your company from getting overwhelmed with questions, allowing you to serve your customers much better.
Now, this is something we can all be thankful for - spam filters.
A typical spam filter has a number of rules and algorithms that minimize the amount of spam that can reach you. This not only saves you from annoying ads and Nigerian princes, but it also helps against credit card fraud, identity theft, and malware.
Now, what makes a good spam filter effective is the AI running it. The AI behind the filter uses email metadata; it keeps an eye on specific words or phrases, it focuses on some signals, all for the purpose of filtering out spam.
This everyday AI aspect got really popular through Netflix.
Namely - you might have noticed that a lot of thumbnails on websites and certain streaming apps have been replaced by short videos. One of the main reasons this got so popular is AI and machine learning.
Instead of having editors spend hundreds of hours on shortening, filtering, and cutting up longer videos into three-second videos, the AI does it for you. It analyzes hundreds of hours of content and then successfully summarizes it into a short bit of media.
AI also has potential in more unexpected areas, such as cooking.
A company called Rasa has developed an AI system that analyzes food and then recommends recipes based on what you have in your fridge and pantry. This type of AI is a great way for people who enjoy cooking but don't want to spend too much time planning out meals ahead of time.
If there is one thing we can say about AI and machine learning, it is that they make every tech they come in contact with more effective and powerful. Facial recognition is no different.
There are now many apps that use AI for their facial recognition needs. For example, Snapchat uses AI tech to apply face filters by actually recognizing the visual information presented as a human face.
Facebook can now identify faces in specific photos and invite people to tag themselves or their friends.
And, of course, think about unlocking your phone with your face. Well, it needs AI and machine learning to function.
Let's take Apple Face ID as an example. When you are setting it up, it scans your face and puts roughly thirty thousand dos on it. It uses these dots as markers to help it recognize your face from many different angles.
This allows you to unlock your phone with your face in many different situations and lighting environments while at the same time preventing somebody else from doing the same.
The future is now. AI technology will only continue to develop, to grow and to become more and more vital for every industry and almost every aspect of our everyday lives. If the above examples are to be believed, it's only a matter of time.
Artificial intelligence will continue developing and being present in new areas of our lives in the future. As more innovative applications come out, we'll see more ways that AI can make our lives easier and more productive!
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12 examples of artificial intelligence in everyday life - ITProPortal
