AI and ML: What Everyone Needs to Know

If you were to draw a Venn diagram with Artificial Intelligence (AI) and Machine Learning (ML), you would see that machine learning is actually a subset of artificial intelligence. The two technologies have been buzzwords for quite some time now and there is no product, website, tech blog or an app that does not talk about these two technologies and the difference they bring to the table. However, if you take a closer look, they are intricately intertwined. Now most of us who are interested in these techs are those who grew up watching the best science fiction films of our times. We are all influenced by an era that quite defined artificial intelligence and paved the way for our basic understanding of the subject. From Back to the Future to iRobot, we have been shown the way of the machines and how AI is all about machine dominance and apocalypse.

The truth is, we are nowhere close to such instances. Today, researchers and scientists are working on what is called general artificial intelligence, which is nothing but what we see in our everyday lives. Your voice assistant, for instance, is one of the best examples of artificial intelligence at work. If you had seen the videos on Amazon’s voice assistant, Alexa, you would know that these machines are designed to think, react, respond and behave like how we as humans would do. Though the gap between a human and a robot is too massive at the moment to be filled in, we are on the right track.

For those of you living under a rock, the best progress we have made so far in artificial intelligence is coming up with Sophia – world’s first robot to be given a citizenship in Dubai. She is smart and talks autonomously and even cracks sarcastic comments when out on a date with Will Smith. However, that is how far we have gone. Other instances of narrow artificial include the activities of systems such as playing chess (Deep Blue), coming up with purchase recommendations, face and fingerprint detection on smartphones, speech recognition and translation and more.

What we are trying to build, at least in the near future, is general AI. This is the part that the sci-fi movies showed us, where robots reach a certain stage they don’t need a human to give instructions. This involves refining thought processes and neurons at the finest levels to give the ability to a machine to think like humans. This comes with the use of technologies like machine learning, deep learning and neural networks. For the best comprehension, we will quickly see what machine learning is all about.

Machine Learning

Machine learning is a subset of AI, where we make use of algorithms and technologies like sensors and connected devices to teach the system to learn autonomously. Instead of feeding hundreds of instances to make a decision, we give machines the ability to filter out wrong decisions and choose the most appropriate ones (again like humans). But that is not as easy as it sounds. The working behind virtual voice assistants and any other technology we have talked about earlier are based on machine learning. To give the right response, Alexa has to understand if your question is genuine or sarcastic, filter out on replies that sound dumb and respond in a way that matches the tone of your question.

That is exactly why such assistants and tools take a little while to get used to you, your questions and get better at delivering better and appropriate results. On the coming articles, we are going to delve deeper into this topic. As of now, this distinction is what you need to get started and the video of Will Smith dating Sophia.

P.S. A quick trivia, Facebook shut down it’s AI wing when the machines started developing and learning a new and bizarre language autonomously.

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