Fashion enthusiast | Posted on | Science-Technology
Entrepreneur | Posted on
Many people use terms Artificial Intelligence (AI) and machine learning interchangeably. But in reality, these two phrases have a very different meaning.
Basically put, machine learning is just one of the ways we achieve artificial intelligence. Meaning, machine learning is a subsidiary or (major) part of AI. Let’s get the definition first:
AI are machines that can perform smart tasks just like humans. Now to make machines work like humans, we can (and do) use various programs to make that happen. One of the common things we do is write a set of instructions and tell the machines how to respond to certain kinds of inputs. For example, if we have designed a talking robot, we can program it to answer thequestion“how are you” with “I am fine”. We write codes and tell that machine how to respond to other commands.
Another thing we do to make AI perform smart andhuman-liketasksis to implementMachine Learning.
Machine Learning is an application in AI. We provide it with a large pool of data and let its algorithm organize this data to answer questions like why, how, what and when. When it understands the data fed to it, it learns and then responds accordingly.
Artificial Intelligence can function without machine learning. However, to make that happen, one would need to write millions of lines of codes, establish complex rules, design multifaceted decision-trees. Think of it, for every command, we would need to write auniqueresponse for the AI to work properly. Meaning, for every question, we would require to feed it pre-programmed answers. Instead of this, we simply let Machine Learning write codes and establish rules for itself. All we do is throw some data to it and let the algorithm do the rest.
Hopefully, now, it’s clear to you what the difference between AI and Machine Learning is.
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