Sword and Shield: How Machine Learning Is Changing Our Lives
Article by Bettina Warburg
Due to pervasive use of internet-equipped devices, today we have the ability to easily gather huge volumes of data. However, data without the ability to understand them is useless. Machine learning tools help us analyze large reams of data and dissect what they mean.
One of the key features of machine learning is the ability to learn and improve as it works. And it doesn’t require the intervention of a human in order to function. It learns and improves, which makes it a tool to free up human time and energy. Machine learning tools allows a firm’s employees to focus on complex, higher level tasks that require creativity, compassion or empathy.
This technology can make the difference between a company figuring out how to get ahead of competition, or failing. In our Animal Ventures Asset Chains report, we cover this and more. But if you don’t work in business or are not focused on growth or sales, that doesn’t mean that machine learning is irrelevant to you. In fact, it probably already affects your life daily, often in ways you may find surprising.
Personalized Recommendation Engines
These days there’s a high likelihood you watch your favorite shows or movies through a streaming service. Similarly, there’s a solid chance you listen to music through a mobile app and order books from the web. As a result, you probably take advantage of recommendations that apps and websites offer you based on your previous behavior. These are chosen by recommendation engines. Recommendation engines rely on machine learning to analyze data about your behavior and tastes, then identify similar media you’ll probably enjoy. They show up everywhere from retail sites like Amazon to media platforms like Hulu and Netflix.
Voice Search or Voice Assistants
If you have ever taken advantage of a voice assistant like Siri or Alexa, then you’ve used machine learning. Machine learning is being used to power voice search so that devices can recognize your voice and understand what you’re saying. It powers speech recognition, which allows voice search tools to understand sounds, words, phrases, and sentences (and to continuously get better at this the more that you speak to it.) Machine learning and speech recognition technology continue to get more complex and powerful as more people interact with them.
No one wants a bunch of junk filling their inbox and distracting from the important emails, like messages from your boss or cute kitten photos from your best friend. Firms use machine learning to create email filters that can sort your mail and help eliminate spam. The longer a detection system works the better it gets at learning what is junk and what is real, so you can get all of the messages you need delivered right to you, and all of the ones you don’t want to see filed away.
Digital Advertising and Keywords
Do you have a website that you use to promote a business or service? If so, and you’re using Adwords to optimize that site or to create PPC ads for it, then you’re relying on machine learning. Google uses machine learning to predict the best keywords for your business, so you can ensure that you’re creating a site that draws in the right potential customers.
Your banks and credit card companies use machine learning tools to keep your money safe. Algorithms understand your spending habits over time. If something seems out of the ordinary, they’ll block it or question it. This ensures that if your card is stolen or fraudulently use, they are able to detect it quickly.
Machine learning tools help companies analyze customer behavior to make better sales and marketing decisions. It can detect behavioral patterns and identify situations that might be risky or undesirable. Crucially, machine learning can make certain software or platforms more exact and precise, since it allows computers to learn when they’re effective and avoid the actions that do not serve users. This technology will make businesses able to understand their own operations and customers better than ever before.