Three Ways Machine Learning Impacts the World

Machine learning algorithms have quietly taken over the world. You’ll find this artificial intelligence (AI) building block in almost every consumer application today, from the Google search engine to the Alexa in your home. CIO reports that businesses are spending inordinate amounts of R&D cash on these tools, up to $97.9 billion in the next three years. But what’s in it for humans? Here are three examples of how machine learning is used today.

Big Technology News—Machine Learning

Business leadership has made big technology news lately with machine learning algorithms. Machine learning is software code that allows computers to “learn” from human behaviors to improve their response. It’s a core capability behind AI, the truly sentient, learning computer that isn’t here yet. When technology news talks about AI, they are really describing machine learning.

MIT researched the impact of AI and found that seven of 10 in business leaders say they haven’t felt the effects of the technology yet. However, machine learning is all around us in the tools we use each day. Some of the latest examples include:

  • Honeywell uses a virtual assistant from Tact.ai to cull data from Salesforce, a sales CRM database, and Microsoft Office 365 to help their sales executives improve their performance. Sales reps use their smartphones to interact with the Tact.ai assistant to see if they’re meeting sales goals.

    The tool uses several AI-related tools to communicate with sales teams:

    • Predictive learning, which looks at prior human responses to suggest the best computer response
    • Natural language processing, which listens and interprets human speech and then responds
    • Machine learning, which allows the computer to correct itself with each successive response
  • Office Depot uses machine learning to generate better insights into customer behaviors. The company spent $11 billion on expanding its services division while improving technology innovations. Business leadership empowered IT teams with these tools, and they’re using them to better understand their customers. Their e-commerce platforms use deep-dive analytics to understand past consumer behavior, then recommend new products using machine learning algorithms. They also use machine learning to detect possible fraudulent activity online.
  • Dartmouth College also jumped on the machine learning bandwagon by using an AI-based wireless local area network (LAN) to power Wi-Fi. The CIO of the college reports this has had a positive effect on the school’s 22,000 students, who can use their phones as personal assistants when on campus. Machine learning algorithms also work behind the scenes to automate network administration and cybersecurity. CIO reports that this network collects 150 pieces of information from each user every two seconds, collates that data, and “learns” from it by adjusting the response at the individual level.

The innovations in the next decade will make today’s machine learning look rudimentary.

While these are just three examples, machine learning is clearly worming its way into almost every aspect of our daily lives, starting with your smartphone, which has been bringing many of the elements of AI to your fingertips every day for years.

While this innovation is astonishing, it’s also important to realize the truth—tools like machine learning are really in their infancy. Where we’ll be in another decade will make today’s innovations look rudimentary.

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