Machine “IRL” Learning:¶
Anytime you want to find out something like how do I make Pav Bhaji? You can do a web search on Google, Bing or Baidu to find out. And that works so well because their machine learning software has figured out how to rank web pages.
When you upload pictures to Instagram or Snapchat and think to yourself, I want to tag my friends so they can see their pictures. Well these apps can recognize your friends in your pictures and label them as well.
If you’ve just finished watching a Star Wars movie (btw I am a huge fan of Star Wars!) on the video streaming service and you think what other similar movies can I watch? Well the streaming service will likely use machine learning to recommend something that you might like.
Each time you use voice to text on your phone to write a text message - “Hey Grogu, how’s it going?” Or tell your phone “Hey Siri play a song by Lisa Gerrard”, or ask your other phone “okay Google show me Indian restaurants near me.” That’s also machine learning.
Each time you receive an email titled, Congratulations! You’ve won a million dollars. Well maybe you’re rich, congratulations. Or more likely your email service will probably flag it as spam. That too is an application of machine learning.
I’m deeply concerned about climate change, and I’m glad to see that machine learning is already hoping to optimize power generation.
Or in healthcare, AI is starting to make its way into hospitals to help doctors make accurate diagnosis.
That’s machine learning. It’s the science of getting computer to learn without being explicitly programmed.
Applications of Machine Learning¶
Machine Learning had grown up as a sub-field of AI or artificial intelligence. We wanted to build intelligent machines. It turns out that there are a few basic things that we could program a machine to do, such as how to find the shortest path from a to b, like in your GPS. But for the most part, we just did not know how to write an explicit program to do many of the more interesting things, such as perform web search, recognize human speech, diagnose diseases from X-rays or build a self-driving car. The only way we knew how to do these things was to have a machine learn to do it by itself.
Looking even further into the future, many people, including me, are excited about the AI dream of someday building machines as intelligent as you or me. This is sometimes called Artificial General Intelligence (AGI). I think AGI has been overhyped and we’re still a long way away from that goal. I don’t know. It’ll take 50 years or 500 years or longer to get there. But mostly AI researchers believe that the best way to get closer toward that goal is by using learning algorithms. Maybe we should take inspiration from how brain works (mainly how human brain works)!