AI has been growing for the past few decades, and it is actively enabling people and businesses alike to achieve the unthinkable. By giving machines the power to think and evaluate has been one of the most challenging steps forward in the computing world. Because of this adoption of Artificial Intelligence & Machine Learning, businesses have eliminated most of their repetitive tasks and focus on solving unique and critical problems. While Artificial Intelligence is in itself a broader term used for encapsulating a vast variety of sub-domains, Machine Learning is one of them. Throughout this article, we will discuss some of the best examples of Artificial Intelligence in everyday life.
Our intelligence is what makes us human, and AI is an extension of that quality.”
— Yann LeCun
Best Examples of Artificial Intelligence in Daily Life
If you think that the implementation of Artificial Intelligence and Machine Learning is restricted to a limited number of industries or a niche amount of applications, you are mistaken.
AI and ML have been deployed in a wide range of businesses and solutions, and we encounter them more frequently than you can imagine. In the following section, we will list some of the best examples of Artificial Intelligence in everyday life.
1. Open Your Phone With Face ID
With the launch of the iPhone X, Apple launched a radical way of unlocking your iPhone using just your face as a password.
The underlying technology behind Apple’s newest security FaceID uses Neural Engine and Facial Recognition on Apple’s A11 and onwards silicon by generating a 3-dimensional map of the user’s face, capturing and matching the facial map image during the unlocking procedure.
It even works when users are wearing accessories such as glasses, scarfs, makeup, and facial hair.
Other phone manufacturers also followed suit and introduced their take on Face Unlock technology using Facial Recognition software.
Even Microsoft Windows jumped aboard this trend and introduced Windows Hello that uses similar technology as Apple for unlocking computers.
How iPhone X Face ID Works –
With the onset of Artificial Intelligence and its implementation in our everyday use platforms and applications, enhancing our style of working. Google and a few other email providers gradually introduced intelligent features, such as smart email categorization, quickreplies, eliminating the hassle of unproductive tasks, simplifying our lives a bit more.
Smart Email Categorization
By applying Artificial Intelligence techniques on our mailbox, Google gave us a smarter inbox, categorizing all the emails on its own, into folders such as Primary, Social, Promotions, Updates and more.
Through the use of machine learning algorithms, Gmail successfully filters 99.9% of spam.
Smart Replies in Gmail
On the other hand, the Artificial Intelligence used behind smart email composition, and the quick reply feature on Gmail is based on Machine Learning algorithms and Natural Language Processing. Both of these features are just a tap away and are extremely helpful.
3. Entertainment and Social Apps
It’s not just the productivity applications that are getting the smart transformation. Entertainment and social media applications like Netflix and Facebook are also adding new features onto their platforms to offer an experience that isn’t just better but also smarter.
Ever noticed how Facebook suggests new friends to you?
Behind their suggestion system, rests a robust implementation of AI and ML that analyzes your usage patterns and drives features such as identifying friends from photos, newsfeed personalization.
Facebook even introduced a feature that scanned user’s posts to detect if they are planning to cause self-harm to get them the help they might require.
Whereas, Netflix uses a smart implementation of AI and ML to give you recommendations on what to watch next. By learning from the users’ past viewing activity and utilizing an effective content rating system together that factors hundreds of metrics, the underlying algorithms work its magic on the recommendation system.
Slack – A Collaborative Tool
Slack is a cloud-based collaboration tool and It has totally transfigured the way organizations communicate.
In Layman’s terms, it is a messaging app for businesses whose purpose is to connect people to the information they need.
In comparison to all its competitors, Slack has more advanced bots, integrations, and usability. As a result, you can interact with your team, share files with your colleagues in a more friendly and flexible way.
According to Slack, a user sends an average of 70 messages per day. Now, the question is how to differentiate which ones are a must-read and which ones can be skipped.
The answer to this question is Artificial Intelligence.
In 2016, the startup employed Noah Weiss developed a more effective and useful platform. To develop this, the group integrated ML to enable faster and accurate information searches in Slack and to identify which read messages hold more meaning to the consumer.
In addition, the company continues to employ emerging updates in NLP and ML to make their app more friendly and easy to use for the consumers.
4. Google Navigation
Going back a couple of years ago, commuting used to be an extremely unpredictable activity, but now thanks to Google and Artificial Intelligence, everything has changed significantly.
The connected nature of navigation elements such as traffic, vehicles, transportation systems makes it so much easier to identify slowdowns and replan commuting.
Google Maps, for instance, with the help of Machine Learning, learns about your everyday work commute and alerts you of traffic slowdowns when it’s time to leave.
It can also identify delays in transportation systems such as flights, trains, and even buses by factoring in traffic status, weather conditions, and more.
Photo by Ingo Joseph from Pexels
5. Ridesharing Apps Like Uber and Lyft
We are so amazed by the ease of use and the utility that we forget to know the specific thing that runs these apps.
We never pay attention to questions like-
- How do these ride-sharing companies set a price for every journey we’re about to take?
- How do they minimize the time taken by the car to reach your specific location?
The magic behind all this is Artificial Intelligence. All this is possible because of AI and ML.
These prominent companies utilize GPS navigation which in turn runs on AI and ML.
With the various advanced algorithms, it is possible to determine the situations of traffic and arrival time. By analyzing huge chunks of data in just minimal time, these apps can determine the shortest route possible for the ride.
Keeping in mind user preferences, Uber and Lyft provide a list of previously searched destinations for quick booking; this is one amazing feature.
Jeff Schneider, the Engineering Lead for Uber, disclosed in an interview how the company indulges ML to forecast the rider demand to ensure that “surge pricig” will soon no longer exist and the head of Machine Learning Danny Lange confirmed the use of ML by Uber for rides, delivery time for meals on UberEATS, optimal pickup locations, etc.
The sole purpose of these two apps is to revolutionize the world of transportation and to make journeys for passengers as smooth as possible.
6. Smart Cars/Self Driving Cars
Among the various artificial intelligence examples in daily life, one is Autonomous Vehicles. Autonomous vehicles have always been in the limelight; recently, Elon Musk’s TESLA dominates tech talks.
Autonomous Vehicles (AV) are well equipped with multiple sensors that help them better understand their surroundings.
These sensors generate a huge amount of data that needs to be processed to make sense of the complicated data. Companies involved in manufacturing these sensors depend heavily upon AI and its algorithms to process huge amounts of data and validate the driving systems.
AI has been paving the way for more advanced development in the autonomous driving industry.
AI provides all the power that is required for self-driving cars to operate. Developers process many complex data using Machine Learning, neural networks, and image recognition technology to develop self-driving cars.
The neural networks are supposed to identify the patterns in data and transfer them to ML algorithms. The transferred data includes images from cameras on self-driving analyzing which the neural networks are able to trace out traffic lights, pedestrians, etc., of the current environment.
Some well-renowned examples of autonomous cars are-
- Optimus Ride
- Rethink Robotics
7. Banking and Finance
In the banking sector, AI has provided amazing analytical technologies that simply improve the whole ecosystem of payment for the banks and the end consumers.
In sort, Artificial Intelligence and Machine Learning play a vital role in the banking industry by providing security features as well as convenience to its customers.
There are countless examples of artificial intelligence in financial services but this one is a major one.
When AI and Ml first came into the picture, financial services were reluctant to employ these technologies in their operations, but considering the benefits, these two technologies add to the business models, even banks got ready to incorporate AI and ML in their functioning.
Now, artificial intelligence is widely used in the development of banking apps. The benefits that it offers are endless;
- Fast and correct assessment of borrowers at lower costs.
- Automated routine processes.
- Dip in the costs to solve standard tasks.
- Efficient and effective processing of huge amounts of data.
- Improved client support system.
Among all the benefits that AI offers, AI-based credit scoring is probably the best one.
Credit Score basically refers to a number between 300 – 850; the number signifies the level of creditworthiness. The higher the number, the better are the chances for a potential borrower to get a loan from a lender.
Generally, a credit score depends on the credit history, levels of debt, history of repayment, and many other factors.
But the AI credit scoring is dependent on a variety of data; work experience, total income, transaction analysis, etc. This scoring is done by a mathematical model that is how AI has been employed more and more in financial industries as it provides real-time factors, giving people with more income the potential to access finance.
Machine Learning can prevent fraud by regularly monitoring your spending habits, taking into account various factors such as intervals between transactions, it’s location, value, and more. The technology can help pinpoint whether the transaction is a legitimate one or a fraud.
Artificial Intelligence can help safeguard your payments by using facial and speech recognition, allowing only authorized payments to go through. Alerting for various payments such as bills, loans, transfers can also be managed by AI.
Photo by Roberto Cortese on Unsplash
By using Artificial Intelligence in daily life, banks have gone entirely digital. Opening a bank account has never been easier, thanks to the paperless process. They now provide personalized mobile banking experiences to their customers with special offers on their services.
8. Google Predictive Search Algorithms
Whenever you try to search on Google, you must’ve noticed a few search terms auto-populate the search field. Behind this is Google’s Autocomplete feature that shows predictions as you type your search term character-by-character.
The algorithm for Artificial Intelligence used behind Google’s Predictive Search is called RankBrain, and its task is to fetch the results based on queried data. With each search, it improves the search results, bringing in more relevant results to the user.
Google uses a combination of technologies behind its leading search engine, including Neural Networks, Deep Learning, Machine Learning, and Artificial Intelligence. With how efficient Google’s search algorithms are, it would be difficult to imagine a world without it.
eCommerce has encountered a major overhaul over the past couple of years with the introduction of Artificial Intelligence and Machine Learning. It is considered one of the best examples of AI in everyday life with improvements that increase the quality of the platform as well as the customer experience.
Notice how you can type in “Red Bags” and get a list of red-colored bags instantly? It is made possible by the underlying AI algorithms, regularly categorizing product searches for efficient indexing.
Enhancements to product recommendations use Machine Learning, taking in your usage patterns to suggest products and help you with your searches. These improvements can be found in practically every online marketplace such as Amazon, Flipkart, AliExpress, and many more, as they are highly popular and offer relatively better shopping experience.
10. AI in Healthcare
The uses of AI in healthcare are immense. It’s obvious AI can simplify the lives of patients and doctors by doing tasks that humans do but with minimal cost and time usage.
AI industry is considered the highest growth industry, with an estimated $150 billion by 2026. As a result, there are countless opportunities to employ technology for effective, accurate, and timely treatment in a patient’s care.
AI undoubtedly offers an endless number of advantages over the traditional clinical process of decision-making. The ever-evolving algorithms help to gain deeper insights into diagnostics, treatment strategies, etc.
Some of the examples of artificial intelligence in healthcare where AI has assisted phenomenally are:-
In the past few years, data digitalization in the pharmaceutical industry has seen a dramatic surge. This digitalization generates huge leaps of data that need to be processed to make sense out of them; here, AI comes into play.
It is the technology that can mimic human intelligence. By using these advanced technologies, we can hunt for new pharmaceutical products in a quicker time and at a lower cost. Just for instance –
- Pfizer is deploying IBM Watson (a system that incorporates ML to run its quest for immune-oncology drugs).
- Sanofi has sealed a deal to utilize UK startup Exscientia’s artificial intelligence platform to search for metabolic-disease therapies.
- Roche subsidiary Genentech uses an Artificial Intelligence system from GNS Healthcare to help the company search for cancer treatments.
Cancer Diagnosis with AI
Cancer, a chronic disease, has haunted scientists for so long and is still doing the same. However, the integration of AI in cancer care has assured doctors improved diagnostics and speedy clinical aid decision-making, ultimately leading to better health results.
Scientists are leveraging AI technology to improve cancer screening in cases of prostate and cervical cancer. In addition, continuous efforts are going on by deploying AI technologies to develop new treatments of cancer.
Seeing this example shows that AI applications in the health care industry hold a promising future.
As the name suggests, Robot-assisted surgeries are the surgeries that are conducted with the help of robots. These have come into the picture to overcome the limitation of pre-existing minimally invasive surgical procedures and to assist doctors while performing open surgeries.
These robots have helped doctors immensely to carry out operations with greater precision and accuracy.
The force behind these amazing working robots is AI. To this date, robots are still being deployed to perform surgeries because of their amazing cooperative technology.
11. Speech Recognition
With the combination of Speech Recognition with Natural Language Processing, smartphones began to offer natural communication between computers and humans. When it comes to smartphones, some of the widespread examples of AI in everyday life include chatbots, voice-to-text converters, and digital assistants.
Voice-to-Text converters convert your speech into text using a Speech Recognition system. Its applications include voice typing, opening applications, and has now become a standard feature among smartphones and computers.
Whereas, Advanced chatbots utilizing Natural Language Processing can effortlessly impersonate a real person and provide a more natural-sounding conversation by even answering complex conversational questions.
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12. Video Games
AI and ML have been used in video games for a long time to provide a self-improving and challenging experience to gamers. Regarded as one of the best examples of Artificial Intelligence in everyday life, these can be easily experienced by players in the form of:
- AI-controlled Non-Playable Characters (NPCs) that react dynamically to player actions
- Procedural Content Generation for generating automated newer game environment when combined with Machine Learning
- Player-experience modeling for dynamically balancing gameplay difficulty based on player skills
Machine Learning, on the other hand, is often used in video games to generate background music by using Artificial Neural Networks. DOTA 2, a famous MOBA game, uses Deep Learning in the form of OpenAI Five.
Photo by Sean Do on Unsplash
13. Smart Personal Assistants
With the improvements in speech recognition systems, we can now have a complete conversation with digital assistants with the technology being close to perfection. Voice assistants are the best AI examples in real life such as, Google Assistant, Alexa, or Siri.
They take your question via voice, and process it using the Speech Recognition and Natural Language Processing systems on your phone and output the results via speech or text.
The Artificial Intelligence used behind these smart digital assistants enables them to manage our digital lives as their role becomes ever critical. They assist with a variety of tasks varying from simpler ones to complex ones. Some of the activities they most commonly help manage are listed below
- Online shopping
- Controlling lights and other internet-enabled equipment
- Setting reminders and alarms
- Booking cabs, flights and trains
- Playing music and videos and many more
Photo by John Tekeridis from Pexels
With the abundance of real data from users, Machine Learning models can be trained efficiently to perform better, ultimately improving Artificial Intelligence with it. Mentioned above are the few best examples of Artificial Intelligence in everyday life that are omnipresent and simplify the vast majority of our daily lives. This is proof enough that AI is truly changing our lives by making us better and more productive to focus on the real challenges.
- Manufacturing robots.
- Self-driving cars.
- Smart assistants.
- Healthcare management.
- Automated financial investing.
- Virtual travel booking agent.
- Social media monitoring.
- Marketing chatbots.
Prominent examples of AI software used in everyday life include voice assistants, image recognition for face unlock in mobile phones, and ML-based financial fraud detection. AI software usually involves just downloading software with AI capabilities from an online store and requires no peripheral devices.
AI backs up the voice assistants like Google Home, Siri, Cortona, and Alexa to decode the voice commands of their masters. AI also helps these applications to take up the databases from the cloud storage platforms to give back the tailored search engine results.
Perhaps the most popular use of A.I. comes in the form of digital smart assistants, such as Siri, Alexa and Google Assistant. These A.I. -powered personal assistants are able to take in your voice commands and translate them into actions, such as adding items to your shopping list or calling a friend.
Artificial Intelligence is a technique that enables machines to mimic human behavior. Whereas, Machine Learning is a subset of Artificial Intelligence. It is the science of getting computers to act by feeding them data and letting them learn a few tricks on their own, without being explicitly programmed to do so.
Common uses of AI. Some of the most standard uses of AI are machine learning, cybersecurity, customer relationship management, internet searches and personal assistants.