Artificial intelligence (AI), specifically machine learning, is now considered to be one of the biggest innovations since the microchip. AI used to be a fanciful concept from science fiction, but now it’s becoming a daily reality. Neural networks (imitating the process of real neurons in the brain) are paving the way toward breakthroughs in machine learning, called “deep learning.”
Machine learning can help us live happier, healthier, and more productive lives… if we know how to harness its power.
Some say that AI is ushering in another “industrial revolution.” Whereas the previous Industrial Revolution harnessed physical and mechanical strength, this new revolution will harness mental and cognitive ability. One day, computers will not only replace manual labor, but also mental labor. But how exactly will this happen? And is it already happening?
Here are 15 ways artificial intelligence and machine learning will impact your everyday life.
1. Intelligent Gaming
Some of you may remember 1997 when IBM’s Deep Blue defeated Gary Kasparov in chess. But if you weren’t old enough then, you might remember when another computer program, Google DeepMind’s AlphaGo, defeated Lee Sedol, the Go world champion, in 2016.
Go is an ancient Chinese game, much more difficult for computers to master than chess. But AlphaGo was specifically trained to play Go, not by simply analyzing the moves of the very best players, but by learning how to play the game better from practicing against itself millions of times.
2. Self-Driving Cars and Automated Transportation
Have you flown on an airplane lately? If so, then you’ve already experienced transportation automation at work. These modern commercial aircraft use FMS (Flight Management System), a combination of GPS, motion sensors, and computer systems to track its position during flight. So an average Boeing 777 pilot spends just seven minutes actually flying the plane manually, and many of those minutes are spent during takeoff and landing.
The leap into self-driving cars is more complicated. There are more cars on the road, obstacles to avoid, and limitations to account for in terms of traffic patterns and rules. Even so, self-driving cars are already a reality. These AI-powered cars have even surpassed human-driven cars in safety, according to a study with 55 Google vehicles that have driven over 1.3 million miles altogether.
The navigation question has already been solved long ago. Google Maps already sources location data from your smartphone. By comparing the location of a device from one point in time to another, it can determine how fast the device is traveling. Put simply, it can determine how slow traffic is in real time. It can combine that data with incidents reported by users to build a picture of the traffic at any given moment. Maps can recommend the fastest route for you based on traffic jams, construction work or accidents between you and your destination.
But what about the skill of actually driving a car? Well, machine learning allows self-driving cars to instantaneously adapt to changing road conditions, while at the same time learning from new road situations. By continuously parsing through a stream of visual and sensor data, onboard computers can make split-second decisions even faster than well-trained drivers.
It’s not magic. It’s based on the exact same fundamentals of machine learning used in other industries. You have input features (i.e. the real-time visual and sensor data) and an output (i.e. a decision among the universe of possible next “actions” for a car).
So, sure these self-driving cars already exist, but are they ready for prime-time? Perhaps not yet, since the vehicles are currently required to have a driver present for safety. So despite exciting developments in this new field of automated transportation, the technology isn’t perfect yet. But give it a few months or years, and you’ll probably want to have one of these cars yourself.
3. Cyborg Technology
Obviously, our bodies and our brains have built in limitations and weaknesses. According to Oxford C.S. professor Shimon Whiteson, technology will improve to to such an extent that we will be able to augment some of our weaknesses and limitations with computers, thereby enhancing many of our natural abilities.
But wait – before you start picturing dystopian worlds of steel and flesh, consider for a moment that most people walking around are already “cyborgs” in a sense. How many people do you know who could survive the day without their trusty smartphone? We already rely on these handheld computers for communication, navigation, acquiring knowledge, receiving important news, and a host of other activities.
Yoky Matsuoka of Nest also believes that AI will become useful for people with amputated limbs. One day, the brain will be able to communicate with a robotic limb. This technology will give amputees more control and reduce the daily limitations they deal with.
4. Taking Over Dangerous Jobs
One of the most dangerous jobs is bomb disposal. Today, robots (or more more technically, drones) are taking over these risky jobs, among others. Right now, most of these drones require a human to control them. But as machine learning technology improves in the future, these tasks would be done completely by robots with AI. This technology alone has already saved thousands of lives.
Another job being outsourced to robots is welding. This kind of work produces noise, intense heat, and toxic substances found in the fumes. Without machine learning, these robot welders would need to be pre-programmed to weld in a certain location. However, advancements in computer vision and deep learning have enabled more flexibility and greater accuracy.
5. Environmental Protection
Machines can store and access more data than any one person could—including mind-boggling statistics. Using big data, AI could one day identify trends and use that information to arrive at h solutions to previously untenable problems.
For example, IBM’s Climate & Sustainability Program uses AI to analyze environmental data from thousands of sensors and sources to discover climate mitigation solutions. Their products also allow city planners to run “what-if” scenarios and model ways to mitigate environmental impact.
And that’s just beginning. Exciting environment-oriented innovations are entering the market every day, from self-adjusting smart thermostats to distributed energy grids.
6. Digital Empathy and Robots as Friends
Most robots are still emotionless. But a company in Japan has made the first big steps toward a robot companion—one that can understand and feel emotions. Introduced in 2014, Pepper the companion robot went on sale in 2015, with all 1,000 initial units selling out within a minute. The robot was programmed to read human emotions, develop its own, and help its human friends stay happy.
“I believe practical advancements in artificial intelligence will start to enable a more contextual form of computing with some of our devices, particularly smartphones and smart speakers… part of the way this development will likely occur is by learning more about people and how they think—essentially building a form of digital empathy.”— Bob O’Donnell, President of TECHnalysis Research
As funny as it sounds, the day that one can literally “buy a friend” is not too far away.
7. Improved Elder Care
For many seniors, everyday tasks can be a struggle. Many have to hire outside help or rely on family members. Elder care is a growing concern for many families.
AI is at a stage where replacing this need isn’t too far off, says Matthew Taylor, computer scientist at Washington State University. Elderly relatives who don’t want to leave their homes could be assisted by in-home robots. That solution offers family members more flexibility in managing a loved one’s care. These robots could help seniors with everyday tasks and allow them to stay independent and living in their homes for as long as possible, improving their overall well-being.
Medical and AI researchers have even piloted systems based on infrared cameras that can detect when an elderly person falls. Researchers and medical specialists can also monitor alcohol and food consumption, fevers, restlessness, urinary frequency, chair and bed comfort, fluid intake, eating, sleeping, declining mobility, and more.
8. Enhanced Health Care
Hospitals may soon put your wellbeing in the hands of an AI, and that’s good news. Hospitals that utilize machine learning to aid in treating patients see fewer accidents and fewer cases of hospital-related illnesses, like sepsis. AI is also tackling some of medicine’s most intractable problems, such as allowing researchers to better understand genetic diseases through the use of predictive models.
Previously, health professionals must review reams of data manually before they diagnose or treat a patient. Today, high-performance computing GPUs have become key tools for deep learning and AI platforms. Deep learning models quickly provide real-time insights and, combined with the explosion of computing power, are helping healthcare professionals diagnose patients faster and more accurately, develop innovative new drugs and treatments, reduce medical and diagnostic errors, predict adverse reactions, and lower the costs of healthcare for providers and patients.
9. Innovations in Banking
Consider how many people have a bank account. Now, on top of that, consider the number of credit cards that are in circulation. How many man hours would it take for employees to sift through the thousands of transactions that take place every day? By the time they noticed an anomaly, your bank account could be empty or your credit card maxed out.
Using location data and purchase patterns, AI can also help banks and credit issuers identify fraudulent behavior while it is happening. These machine learning based anomaly detection models monitor transaction requests. They can spot patterns in your transactions and alert users to suspicious activity.
They can even confirm with you that the purchase was indeed yours before they process the payment. It may seem inconvenient if it was just you eating at a restaurant while traveling on holiday, but it could end up saving you thousands of dollars someday.
10. Personalized Digital Media
Machine learning has massive potential in the entertainment industry, and the technology has already found a home in streaming services such as Netflix, Amazon Prime, Spotify, and Google Play. Some algorithms are already being used to eliminate buffering and low-quality playback, getting you the best quality from your internet service provider.
ML algorithms are also making use of the almost endless stream of data about consumers’ viewing habits, helping streaming services offer more useful recommendations.
“Given the rapid pace of research, I expect AI to be able to create new personalized media, such as music according to your taste. Imagine a future music service that doesn’t just play existing songs you might like, but continually generates new songs just for you.”— Jan Kautz, Senior Director of Visual Computing and Machine Learning Research, NVIDIA
They will help more and more with the production of media too. NLP (Natural Language Processing) algorithms help write trending news stories to decrease production time, and an MIT-developed AI named Shelley helped users write horror stories through deep learning algorithms and a bank of user-generated fiction. At this rate, the next great content creators may not be human at all.
11. Home Security and Smart Homes
For the best tech in home security, many homeowners look toward AI-integrated cameras and alarm systems. These cutting-edge systems use facial recognition software and machine learning to build a catalog of your home’s frequent visitors, allowing these systems to detect uninvited guests in an instant.
AI-powered smart homes also provide many other useful features, like tracking when you last walked the dog or notifying you when your kids come home from school. The newest systems can even call for emergency services autonomously, making it an attractive alternative to subscription-based services that provide similar benefits.
Consumer AI will enable wave after wave of convenient automations in the home. When combined with appliances, AI could make housework and household management seamless.
AI-powered apps which allow the oven to communicate with the refrigerator and the pantry robot would act like home chefs. Instant replenishment of food and supplies would mean never running out of anything again. Cleaning could be schedule through sensor-to-appliance connections, after which robotic cleaners would work almost completely independently of humans.
Another advantage of smart homes would be a reduction of household waste and automated recycling, putting the household in better balance with the ecosystem. Releasing humans from housework could deliver major benefits in terms of improving sustainability, saving time, and reducing stress.
12. Streamlined Logistics and Distribution
Imagine getting a package in just a few hours and at a very low shipping cost. That’s the promise of AI in logistics and distribution, with its promise to tame the massive amounts of data and decisions in the trillion-dollar shipping and logistics industry. Amazon has already started experimenting with autonomous drones that blow their already-quite-fast two-day shipping out of the water.
Currently, shipping costs are still quite expensive. Improving efficiency through AI integration and automation will mean big reductions in shipping costs and increases in delivery speed. Optimization opportunities in supply chain management, vehicle maintenance, and inventory will also make shipping faster, easier, and more environmentally friendly.
13. Digital Personal Assistants
Imagine never needing to worry about preparing dinner, because your personal assistant knows what you like, what you have in your pantry, and which days of the week you like to cook at home. Imagine that when you get back from work, all your groceries are waiting at your doorstep, ready for you to prepare that delicious meal you’ve been craving. You even have a bonus recipe for a new dessert you’ve been meaning to try.
Digital assistants are getting smarter by the year. Companies such as Amazon and Google are pouring billions of dollars into making digital assistants even better at speech recognition and learning about our daily routines, opening the door to more and more complex tasks.
14. Brick and Mortar and AI
Georges Nahon, CEO of Orange Silicon Valley, foresees a time when people will no longer need to wait in line at a store. Observing how tech and retail are merging, like Amazon and Whole Foods, he says: “Thanks to AI, the face will be the new credit card, the new driver’s license and the new barcode. Facial recognition is already completely transforming security with biometric capabilities being adopted…”
While some people claim that e-commerce and the Internet will completely eat away the traditional retail market, the more likely scenario is that they will arrive at some sort of equilibrium. However, it’s undeniable that even the biggest traditional retail giants are starting to adopt AI-powered technologies to gain a competitive edge.
15. Customized News and Market Reports
According to Reg Chua, COO of Reuters News, technologies are close to providing customized news and market reports, and newsrooms are starting to embrace the possibilities. Can you imagine getting market reports that were written on demand for you and not just when the market closed?
Instead of a generic recap of market performance, your customized report compares how your portfolio performed against the broader market, citing key reasons why. For example: “It’s 3:14 pm. The market is currently up 2%, but your portfolio is down 3%. This is attributed in part to the purchase of XYZ stock last week, which has fallen sharply since …”
While the most obvious application of this technology would be in the finance and investing space, there are plenty of other domains that would benefit as well, including ad tech, agriculture, sports, and more.
The Bottom Line
As many people have wisely observed, the dream of artificial intelligence is not new. It has been around since the very earliest days of computing. Pioneers have always imagined ways to build intelligent learning machines.
Currently, most promising approach of AI is the use of applied machine learning. Rather than trying to encode machines with everything they need to know up front (which is impossible), we want to enable them to learn, and then to learn how to learn.
Machine learning’s time has come, and it is in the process of revolutionizing all of our lives.