Earlier this month we published some introductory material
on machine learning on this blog. This technology has a huge impact on people’s lives everyday. Examples include the way companies works to attract clients to the way that music engines like Spotify recommend new songs. Because of this value, 76% of the world’s most successful businesses
are using machine learning tools.
If you want to get a better understanding of how machine learning appears in your daily life, and how it powers some processes you really appreciate, check out the list below. These are the most popular applications of machine learning in the real world. These examples show just how much machine learning can do now, and this is just the start of what we may expect to see powered by it in the future.
Do you ever upload a photo to Facebook, only to be surprised that the platform already knows who’s in it? That recognition ability is powered by machine learning, which is the science behind all image recognition technology that we use today. You encounter machine learning-powered
image recognition all around you. Some of the most popular applications, are:
- Automated photo organization – photo albums that organize photos for your automatically, after you upload images to them.
- Image tagging on social networks: Like the Facebook example above, image recognition allows social networks to identify and auto-tag photos, saving people time and energy
- Image search using images (on search engines, etc.): Today, you can use search engines like google to search for an image using that image. This is powered by deep learning. Police can also scan the web for images that are illegal, like images of child pornography.
- Self-driving cars: While they haven’t become popular in terms of usage yet, talk of self-driving cars is all the range, and these cars us image recognition to ensure they make the right moves (and avoid hitting things).
- Medical imaging: Today doctors can use image recognition technology to look at an X-ray or ultrasound and better determine if something looks off.
How many times recently have you talked to Alexa, Siri, or Cortana? Voice search and voice assistants are powered by machine learning and a rapidly growing technology category. These assistants get better at understanding your words and preferences over time. They also improve on picking up on your voice, so you can be the sole controller of your assistant.
Real-Time Bidding in Advertising
Machine learning has had huge impact in the field of marketing. For example, marketing teams can harness the power of machine learning to create real-time bidding, which analyzes open ad spots. They then bid on those spots and place the right ad, all within a split second. Machine learning has made advertising online more effective and precise than ever.
Today, in addition to X-rays and other imaging tools, the medical field uses machine learning for computer-aided diagnoses. Doctors or nurses can input symptoms that a patient is experiencing into a database. They then get suggestions for what might be ailing a patient. Once diagnoses are confirmed and new symptoms are recorded, the algorithm gets better at understanding and detecting that particular condition.
Machine learning has been great for the entertainment industry. It is the technology that powers recommendation engines, which analyze and sort content. Examples of recommendation engines that you’ve probably encountered are:
- Netflix recommended movies and TV
- Hulu recommended shows
- Spotify song or playlist recommendations
- Amazon recommendations for books and products to purchase
- Facebook’s “People You May Know”
- YouTube’s Recommended VIdeos list
- Pandora’s “Music Genome Project”
- Waze’s route offerings
Customer Support Chatbots
Many companies have replaced traditional customer support teams with machine learning powered chatbots, which help customers with their concerns. These chatbots ask questions of customers and learn if they are offering effective answers as they go. Each time a consumer interacts with these chatbots, they get better at understanding how to help. This frees up employees, allowing them to focus on more human-centric tasks that require creativity or complex social skills.
These days machine learning is all around us. As a result, AI is only going to get better and better as time goes on and more data gathered. As machine learning becomes more advanced, you can expect to see even more incredible systems and processes powered by it.