A boomer’s guide to Machine Learning
Introduction: AI is everywhere
Back in the days of analog, if you wanted to watch TV, you had to manually flip through every channel to find something you might like. But now, you have streaming services like Netflix, which now seem to know exactly what movie you’d want to watch next. How does it do that? Through machine learning (ML)—a neat way computers learn from data and make predictions based on that data (in this case, your data would be previous movies you’ve watched on Netflix). Let’s break it down in simple terms - like the way your millennial children explained WiFi to you.
What is Machine Learning?
Machine Learning is when computers learn patterns from data instead of following step-by-step instructions. For example, imagine you’re curious about the current price of that palatial 4-bedroom home you bought 45 years ago. Instead of guessing, machine learning looks through tons of data—such as, similar home prices in your area, school zones, market trends—and just like that, you’ll find out that $15,000 investment you made in 1980 is worth $2 million today.
How does Machine Learning work?
At its core, ML follows three simple steps:
Training: The computer is given lots of examples to study - like going through tons of pictures of rotary telephones.
Learning: It looks for patterns in the data - like recognizing every photo of a rotary phone contains a dial, handset, and cord.
Predicting: Once it has learned enough, it can make smart guesses on new data - such as being able to tell you that for certain that a photo of someone’s living room contains a rotary phone simply based on how much it’s learned about what one looks like. It can scan a photo and point it out. Just like “Where’s Waldo”.
Real-world examples of Machine Learning
Machine Learning is already part of your daily life, even if you don’t realize it:
Netflix recommendations: Netflix learns what shows you like and suggests similar ones - much like your neighbor, Jim, who always recommends “MASH” or “Cheers”.
Voice assistants: Siri and Alexa understand your speech using ML - even when you’re yelling at them to speak with their manager.
Spam filters: Your e-mail learns which messages are junk and keeps them out of your inbox, just like how you learned to ignore phone calls from ‘UNKNOWN CALLER.’
Fraud detection: Banks use ML to recognize unusual activity on your accounts—like that one time you accidentally charged that new hip to your credit card rather than your insurance company.
Why is Machine Learning important?
Machine Learning helps businesses and people by:
Automating repetitive tasks (like sorting emails or reminding you for the tenth time that your car’s extended warranty is expired).
Personalizing experiences (like targeted ads that somehow know you’ve been thinking about buying a new recliner).
Improving decision-making (like predicting the best route home—although nothing beats your secret shortcut through the neighborhood backstreets to avoid “rush hour”!).
The future of Machine Learning
Machine Learning is growing rapidly, helping industries like healthcare, finance, and entertainment innovate. But don’t worry—robots aren’t taking over the world just yet! ML is simply a tool that helps make all our lives easier.
Conclusion: You already use Machine Learning!
Whether you’re watching YouTube, unlocking your phone with Face ID, or wondering how Facebook knows your old high school crush’s birthday, Machine Learning is quietly working behind the scenes on your behalf. Now that you understand the basics, go impress your grandkids.