How far are we from creating real life Jarvis?

All those who have watched at least one movie of Iron Man surely know about Jarvis, the trustworthy assistant of Iron Man. Jarvis controls the entire operation of Stark Industries, helps Tony Stark while operating his suit, hacks into machines, and all kinds of cool stuff. It gives weather predictions, calculates flight data, analyzes almost every object, and gets details about it. So, with the evolution of machine learning, the internet of things, and artificial intelligence, the question comes to many minds: How far are we from creating real-life Jarvis?

To get the answer to this question, we need to have a look at the beginning of machine learning. In 1950, Alan Turing published a paper “Computing Machinery and Intelligence” in which he asked the revolutionary question — “Can machines think?” Thus started the era of machine learning. The first glimpses of NLP (Natural Language Processing) were seen in the 1940s. Now, NLP is a part of artificial intelligence concerned with the interaction between computer and human languages. It is a way of programming computers to understand human languages. NLP is most widely used in speech recognition and machine learning. It is like a gateway between the computer and human languages. Most of the virtual assistants that we have today like Google assistant, Alexa, Siri employ the use of NLP and CNN (Convolutional Neural Networks) to use machine learning and interact with us. These assistants are pre-trained for basic tasks and then learn to help us according to our preferences by using Machine Learning and Artificial Intelligence.

Back to Jarvis. Right now, we are nowhere close to making a real-life Jarvis. One of the best AI programs we have is IBM’s Watson, a highly intelligent system capable of high-level program implementation and planning. Watson uses a cluster of 90 IBM Power 750 servers, each with a 3.5 GHz processor and 16 terabytes of RAM! This seems crazy right, but making a system that can process human language, give suggestions, analyze complex data, and automate any work requires all these resources. Also, machine learning is not as easy as it seems. Even with such heavy requirements, the AI programs we have now can’t compare to Jarvis. Jarvis has an insane amount of computing power. And one cool feature about Jarvis is that it talks and humanly understands the language, not like the machine way. It can understand sarcasm, jokes, it’s almost a human being. The AI systems available now fall short when it comes to unsupervised learning. Supervised learning is like common sense, you go into a new environment, learn about it and then make your decisions. Our AI systems are outstanding at supervised learning but not that good at unsupervised learning.

Considering the technological advancements in the field of Artificial Intelligence, and the introduction of quantum computing, there are still hopes that we can recreate Jarvis. So, fingers crossed!!

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Originally published at https://techquickiesp.blogspot.com.