TWIFT | Digital | Simple examples of how AI and ML affect your daily life

Simple examples of how AI and ML affect your daily life

Have you ever thought about how often you use Artificial Intelligence (AI) in your daily routines? You would probably say “idono” or hardly ever, but let me tell you the real fucking truth with stats and facts.

Now tell me what is the first thing that springs to your mind when you hear the term AI in your daily life? Let me guess. Are these wreaking havoc robots from the movies “I, Robot” or “Ex Machina”? Well, it was a good guess and so were the movies, but we have got to make it clear first what AI means indeed.

AI daily

Here are some key points to keep in mind if you do not want to look dumb when someone tells you that we are surrounded by AI and most likely will never ever be able to live without it.

  • AI refers to the simulation of human intelligence in machines.
  • Its goals include learning, reasoning, and perception.
  • AI is being used across different industries including finance and healthcare.
  • It can be either simple, single-task oriented or complicated and carry on multiple tasks that are more complex and human-like.

Self-driving cars, speech recognition, machine vision, instant machine translation, expert systems, and many other daily AI applications have revolutionized our regular life. If previously given examples are not convincing enough, just think about the way you get to work, search on the Web, or make online purchases. To get a better understanding of a mature and immature usage of IA we need to divide them into two categories: artificial intelligence itself and machine learning (ML). Mind that all ML is AI, but not all AI is ML. I am not going to complicate either mine or your life with a mishmash of scientific terms and definitions to seem to be a smartass. But I will come up with some specific AI examples, which are used on daily bases at work, school or home.

The way we commute

To change people’s commuting behavior is a baffling task as a single trip may involve multiple modes and means of transportation. We should also take into account force majeure circumstances such as extreme weather conditions, repair works, accidents on the road, or incidents on the way. Just take a look at how Google maps, ridesharing apps like Uber and Lyft, and AI Autopilot on commercial flights have settled these questions.

Google Maps and smartphone location data are commonly used to track the traffic. They give advice on how to bypass traffic jams and suggest the fastest routes to and from work. Ridesharing apps determine the price and time of your ride, show optimal pickup locations to meet your demands like your meal delivery. You might be surprised to know that one of the earliest use of AI technology was noted back in 1914. It was when commercial airlines, already at that time, were using AI autopilots. Not less surprising is that the average flight of a Boeing plane requires only seven minutes of human-steered flight, which are essential only for taking off and landing.

No one knows for sure how much time should pass until all of us will be driving fully-autonomous vehicles either private or public, but self-driving cars will definitely shorten our commuting time by up to 26%. Besides, the number of accidents will be reduced by up to 95%, the traffic density by up to 75%, and with the help of smart traffic lights the average waiting time will be up to 40% shorter. Even though the timeline for such changes is still malleable, Uber CEO Travis Kalanick says the timeline for self-driving cars is “a years thing, not a decades thing”; Andrew Ng, Chief Scientist at Baidu and Stanford faculty member, predicted in early 2016 that self-driving cars will be mass-produced by 2021.

The way we process information

What would you say if you heard that Gmail successfully filters out 99% of spam from your email inbox? Hell yeah, that is why you no longer receive lurid love letters from Nigerian princes or cure-all products and pay-in-advance credit offers. Well, you might be getting some new spam scams just because spammers quickly update their messages. And just as fast spam filters learn from a variety of signals, such as the words in the message, message metadata what exactly to filter out.

The good news is that Gmail also knows how to divide your emails into primary, social, and promotion inboxes, as well as prioritize them. It means that every time you mark an email as important, Gmail learns what matters to you. So if you do not want to waste your time on all sorts of rubbish, you have got to deliberately sort out your emails.

Would not it be awesome if your inbox could reply to necessary emails instead of you? Google had already been working on it when a next-generation email interface was introduced with its brief smart replies in 2015. I do believe that in the short term extended smart responses will be at your disposal as well. Check out a new instant messaging app Allo that can use smart reply to provide both text and emoji responses.

The way we assess and grade

In case you have ever used such services as Turnitin, you should definitely know what plagiarism is. The majority of high school and college students are aware of its precise detection analysis for plagiarism. If earlier it took a while to process all database and scan a particular text for similarities, nowadays it does not take a rocket scientist to determine a plagiarized text even in foreign languages or older sources that have not been digitized. Bear in mind that ML can detect plagiarism with 87% accuracy. By the time a universal AI-powered plagiarism detector will have been invented, you will still need to check some of your papers manually. Nevertheless, ML offers great promise in how to improve the educational system by developing custom-tailored tutorials and independent study syllabus.

The way we make purchases and payments

Lucky we are that today we can do all necessary financial transactions with just one click of a button on our phones. The banking system worldwide has been rapidly progressing to make our daily financial operations much easier and faster. With the help of the smartphone app, you can instantly check your deposits. Most prominent banks use the technology made by Mitek, which is a perfect combo of AI and ML.

The more transactions we make the more frauds occur. That is why it is so crucial to determine a fraudulent transaction in time. For instance FICO, a major analytics software company, resort to neural networks to detect fraudulent transactions.

You might have not used FICO services directly, but you may have applied for a loan or credit card before. So how do financial institutions determine whether you are creditworthy or not, which interest rate or credit line amount to provide you with? By a reasonable use of ML, FICO determines your FICO score, which lenders use to assess a borrower’s creditworthiness and credit risk. Moreover, ML in this situation can reduce a bank’s losses on delinquent customers by up to 25%.

Just imagine that in the not-too-distant future you will consult a robot about your investments rather than a fund manager. At present the already existing technologies such as Wealthfront since 2011 and Betterment since 2008 optimize your finances and take the work out of banking, investing, borrowing, and planning. What is more, they will soon offer you more relevant and personalized financial advice than ever before.

Now is the right time to look at some AI daily applications used at home.

Social networks like Facebook, Instagram, Snapchat, and Pinterest are the biggest fun and evil of our reality. Do not even dare to ask me why as the answer is obvious, all of them are just misleading tools of a delusive life. Alright, I will not be lecturing you at this point as it is already another topic to be discussed and one more article to be written. Anyways, I must note that networking has already become a part of our daily routines if not a lifestyle.

Every time when you take a new fucking cool selfie and upload it on FB, the service immediately identifies faces on the photo and suggests friends. FB not only easily recognizes your face, but personalizes your newsfeed, and ensures that you see posts and ads that are an interest for you. It is not a secret that the more you get interested in an advertised product or service, the more FB earns by its advertising and promotion. In 2016 Facebook and Google cornered the market of online advertising and secured 85% of it mostly thanks to deeply-targeted ads.

Deep Text was introduced in the same year and was applied to Facebook Messenger to recognize a user’s intent to do something e.g. to call a taxi. In response to this signal, it could offer to call a taxi. Deep Text intent recognition can also understand a FB user’s intent to sell or buy something with a post to his or her newsfeed. In response to this signal, the option to use FB tools that make buying and selling easier could be presented. Besides that, it automatically removes spam and helps celebrities to sort out millions of comments on their posts to find the most relevant. 

AI daily

ML that identifies the contextual meaning of emoji is the main feature on Instagram, so it replaces slang such as ROFL with a rolling on the floor laughing smiley. By the same principle, Instagram creates and auto-suggests emojis and emoji hashtags. Even if it seems to be a rather primitive example of AI usage, still it is highly used by Instagram users in communication with each other.

In 2015, Snapchat made a splash worldwide by introducing facial filters aka Lenses. The technology came from Ukrainian startup Looksery, which is an application that allows users to modify their facial features during video chats and for photos. Snapchat acquired this startup for $150 million, which was the largest tech acquisition in Ukrainian history at that time.

In its turn, Pinterest uses one of AI apps that lets computers automatically identify objects in images aka pins, and then recommend visually similar pictures and searches. Perhaps, this app is the least harmful and most time-investing from the previous ones. People actually use what they discover on Pinterest. Whether for a costume party or on a road trip, they make use of what they find.

FB also assures us that soon we will be mostly talking and texting to AI chatbots in case we need to do shopping, errands, and many other day-to-day tasks. It all started in early 2015 when FB acquired that could create bots to interact with humans on the messaging platform. Bots are constantly learning, becoming smarter every time they are being spoken to. However, we should not forget about the immature usage of such AI applications, which are likely to raise doubts about their benefits to humanity.

The way we do shopping

Online shopping is one of the easiest ways you can save more time, money, and personal energy resources. How come is that? First of all, you do not have to waste your time on an endless search for necessary items. Amazon tries to find relevant, informative, and trustworthy content for you just in a few seconds by analyzing your search queries for keywords, so they match your desires with proper goods.

Recommendations shown to you are always based on your interests. Amazon examines the items you have bought, rated, and already own. Your activity on the site is compared with other customers, and by using this comparison, Amazon recommends other articles that you may be interested in. Stats prove that recommenders have increased sales by up to 30% so far.

As it was already mentioned before ML is highly used for fraud prevention in online financial transactions, especially in credit card transactions, as well as for minimizing the number of legitimate transactions declined due to being falsely identified as fraudulent. Fraud is the main reason why online payment procedures are more costly for merchants rather than in-person transactions. Thereby, a third-party payment processor like Square comes in handy. It is just perfect for companies that are new or don’t process that many card payments on a monthly basis. Square also offers competitive pricing when it comes to the online credit card.

As a result, the consumer shopping experience would be as smooth as possible. And we have to thank such platforms as Liftlgniter that personalizes content and product recommendations in real-time to optimize conversions without compromising the end user’s privacy, or Optimizely that enables businesses to experiment deeply into their technology stack and broadly across the entire customer experience.

The way we use mobiles

I bet you are no longer surprised about such a standard feature on smartphones as voice-to-text, which is a type of program that converts spoken to written language. It was originally developed as an assistive technology for the hearing impaired. Its applications were limited primarily because older voice-to-text programs had to be trained to recognize a specific person’s speech before attaining an acceptable level of accuracy. Newer programs can decipher the average person’s speech without training, opening up possibilities for new applications of the technology, including interactive smartphone functions, such as voice-to-text message delivery and voice-to-text search, as well as the conversion of audio content such as podcasts. While Google is using artificial neural networks to power voice search, Microsoft is developing a speech recognition system that can transcribe conversation slightly more accurately than humans.

In the crazy rhythm of modern life, we face with multiple tasks, which require additional efforts and time. At a time like this, we can rely on smart personal assistants like Google Assistant, Bixby, Siri, or Alexa. Their main functions are to control all apps on your device, play videos, and music from streaming services, find information online, run timers and reminders, make appointments, and send messages. If you are curious about which one is better among them, recent research shows that Google Assistant’s abilities dominate the rest. So far, Google has released a real smart assistant. And a lot of users who have tried different virtual assistants claim it is the “smartest” one, especially when it deals with the recognition of voice commands.

On the whole, smart assistants will be the key tool for bridging the gap between humans and their “smart” homes. In 2016, Google released Google Home, which became the main competitor to Amazon Echo. It features deep integration with other Google products like YouTube, Google Play Music, Nest, and Google Assistant.

Facebook CEO Mark Zuckerberg’s personal project for 2016 was to build an artificially intelligent, voiced controlled assistant for his home. Being inspired by Tony Stark’s voice assistant Jarvis from Iron Man movies, Zuckerberg created his own version of Jarvis that could control his main appliances, including his lights and toaster. Some other functions also include playing music based on his and his wife’s preferences, scanning the faces of his visitors and letting them in through the front door, chatting through the Messenger app, and a dedicated voice-recognition iPhone app, making small talk and even telling jokes!

Let me ask you a question, have you ever wanted to sneak secretly into Tony Stark’s mansion and steal away Jarvis? If so you will not have to do it as with the help of Google or Amazon, home AI will be available to anyone in the next five years. No one really knows what AI will turn our lives into within the next five years. But one thing I know for sure is that we are on the edge of a completely new industrial revolution. 

Related Articles   Related Articles    Related Articles   Related Articles    Related Articles   Related Articles    Related Articles   Related Articles