Machine learning has developed into one of the most thrilling technologies worldwide and is considered a subset of artificial intelligence in computer science. This technology provides cognitive abilities to coding algorithms by giving it the ability to recognize patterns in data through various training techniques similar to the way a human would learn.
Today, machine learning is used widely in a set of platforms no one would’ve anticipated years ago. In today’s modern world people use a machine learning algorithm countless times without even realizing it. Machine Learning has dozens of applications in various aspects of technology. They include:
Self Driving Cars
This is one of the most exciting areas of Machine learning in my opinion and has the potential to completely revolutionize people’s day to day lives and is brought on by the advancements in processing speed and reductions in hardware costs such as camera sensors and CPUs. Gone would be days of mindlessly driving in traffic for 30 – 90 minutes everyday and instead you could use that time to read your emails earlier, work on something productive, or better catch up with your family.
To enable a car to be self driving a central computer system in the car needs to be able to recognize millions of patterns from the input sensor to safely determine what the car should do in any situation. To do this involves several of the technologies mentioned below such as image processing, speech recognition for a person to interact with the car, and even traffic projection data for the car to reroute itself or change driving modes.
Currently Tesla is making great strides in self driving technology and even has a version of Auto Pilot that people can use today for their car to self drive with you monitoring the Cars behavior. Within the next 10 years we could see cars become fully autonomous and even serving as driverless taxis so your car can work for you while you are working for it.
Email Spam and Malware Filtering
There are a handful of spam filtering techniques that email users utilize. Machine learning is applied to ensure all the spam filters are updated from time to time. The ordinary rule-based spam filtering is not necessarily enough to trace the current techniques embraced by spammers. However, the use of C 4.5 Decision Tree Induction and Multi-Layer Perceptron techniques, all powered by machine learning, have been shown to be effective.
Nearly 350,000 types of malware are discovered daily, and every piece of code resembles its former versions. A vast majority of the system security programs supported by machine learning unearth this coding pattern. Hence, they discover new malware within 10 percent similarity ranges and below variation with ease and render the necessary remedies to contain them.
Online Fraud Detection
Machine learning is enhancing the safety of online transactions and securing them by spotting deceptive transactions. Every time an online transaction is performed there are multiple ways that a deceptive transaction can occur; such as account forgery, counterfeit ids, and money disappearances in the course of a transaction. Hence, to guarantee a safe transaction, machine learning helps to validate authentic transactions from fraudulent ones my comparing a purchase against a persons previous spending habits and cross analyzing that data against people with similar spending habits.
For every authentic transaction, the output is transformed into a multi-dimensional set of hash values, and these values are used as the input for the machine learning model such as a neural network which has been trained on previous valid and fraudulent transactions. The model is then able to output a label for the transaction of valid/fraudulent as well as a confidence posterior which can be used to notify you and your bank of potential wrong doings.
Speech recognition gives the machine the capacity to convert digital audio signals into a text based sentence through a complicated process of audio processing pipeline. Computer systems can also do analysis on the text output to simulate natural language understanding to provide answers to questions or take actions on a request.
Search engines like Google have embraced machine learning to make it more convenient to their users. Google specifically offers the “Search by voice” option under speech recognition, a fashionable machine learning application.
Other popular platforms that have adopted speech recognition as an application of machine learning include Siri and Alexa. All these applications are intended to help users find information when inquired over voice and can interact in a human like way such that they almost pass the Turing Test.
You can use Alexa by buying a speaker or headphone product with Alexa on it or on your phone by downloading the Alexa app and changing the settings to start listening for the “Alexa” wakeword, which will then do more advanced speech recognition on anything you say afterwards. With the feature enabled, you can ask any question over the voice like “What is the date today?”, “What are the best valentine gifts,” and so on. To provide answers to your questions, your virtual assistant gathers information, remembers your correlated questions, then conveys a command to other resources to gather the necessary details.
The desire to keep up with the ever raging voice instructions has prompted many applications to adopt speech recognition technology. Decades back, nobody thought that this technology would be as accurate as it is today such that millions of people worldwide are using digital virtual assistants in their home daily.
Medical Diagnosis Assistance
Machine Learning integrates various techniques and tools to handle diagnostic and prognostic cases in varying medical fields. Machine Learning algorithms are widely used to analyze medical data to identify consistencies in data, deal with improper data, justifying data obtained from various medical units, and proper monitoring of the patients.
Previously doctors and lab specialists would analyze results of blood tests, x-rays, CT scans, EKG results, and other various tests manually on a case by case basis. Today results can be put into a global database, where machine learning can find correlations between test results and underlying causes across millions of tests to help guide a Doctor to a conclusion and treatment plan much sooner than before.
Additionally, machine learning is being used in approximating disease advances, planning and assisting therapy, as well as inclusive patient management.
Image classification/recognition is one of the most popular applications of machine learning and allows for a computer to automatically label the photo above as a Tiger and not a lion by training a machine learning algorithm on thousands of pictures of Tigers. This would be useful if a natural wildlife conservationists set up a camera somewhere to take photos every few minutes and then the person wanted to run a program that would separate out the photos where a Tiger passed by to monitor their behavior. Looking at all the pictures by hand would take hours, where the program could do it in seconds and give back more time to the worker for analyzing the photos.
This technology is what allows you to easily tag friends in pictures that you upload on social media. When the picture is uploaded a machine learning program is run that compared the people in the photo to your friends photos as well as their friends photos to automatically classify them in your photo and provide the ability to tag them.
Automatic Language Translation
Nowadays, it’s no longer worrisome to tour a place you’re unfamiliar with the language since machine learning will come to your rescue. Machine learning aids in converting text into a language you’re familiar with. Google Neural Machine Translation offers this feature, which is a Neural Machine Learning that converts the text into a language that is understandable to you. It’s often referred to as automated translation.
The automated translation concept is a series to a series learning algorithm, which is also applied in image recognition and translates chunks of text from one language to the other.
Most people make use of Google Maps when traveling to new places. This is because Google Maps shows us the right direction with the shortest route and projects the traffic conditions.
It projects the traffic situation such as immense congestion, slow-moving congestion, and so on with the aid of the following ways:
- Real-Time location of cars from Google Map application and sensors
- Standard time that is taken for the vehicles to move from one point to another in previous days simultaneously.
In one way or the other, those using Google Map are unknowingly helping to make this app better. It captures information from the user and conveys it back to its database to enhance the performance over time as the Google team works on more advanced prediction models.
Think of an individual keeping an eye on several video cameras! Definitely, a strenuous task to tackle and somewhat boring and even more so as the number of cameras and monitors increases. This is why the concept of training computers to perform this role is much welcome.
Nowadays, video surveillance systems use AI to enhance their effectiveness in unearthing crime before it happens. They are capable of detecting weird behavior patterns of people who seem to be planning to engage in crime. An example of such behavior is standing motionless for quite long and even napping on benches. Once the system detects such a behavior, it notifies the attendants of an anomaly in an area so they can check for themselves and send people to investigate the situation further. This is more efficient in keeping the crime levels at bay.
These systems are especially useful in Casinos where some people may constantly be trying to swipe chips and manipulate bets to their benefit. With the help of machine learning you can feel comfortable your stack of chips on a blackjack table are much safer!
Machine learning has plenty of applications in the world of technology. The role of machine learning can’t be underrated, considering the numerous benefits it offers. Such technology is critical, especially in today’s world, where the rate of crime is continuously raging.