Demystifying AI, Machine Learning and Deep Learning

Demystifying AI, Machine Learning and Deep Learning


Demystifying key buzzwords like Artificial intelligence, machine learning, artificial neural networks and deep learning is simple and complex task at the same time.

Lets Undertand a Bit
Let us attempt to melt down the thick confusion of how all-encompassing terms like artificial intelligence, machine learning, and deep learning speaks to each other. Machine learning, Blockchain and Artificial Intelligence are all the golden words these days. Almost every technology (now even non technology) company on this planet is claiming the share of extra revenue by putting these buzz words on display.
What is getting lost here is with all the buzzwords swirling around, it’s easy to get lost and not see the difference between hype and reality.

Key buzzwords of today’s technology !
Demystifying key buzzwords like Artificial intelligence, machine learning, artificial neural networks and deep learning is simple and complex task at the same time. All these terms are representative of the future of analytics. Sometimes it is good to un-develop something existing to uncover the hidden gems underneath. May be its like un-develop to Innovate?
In the past Alan Turing published “Turing Test” that speculates the possibility of creating machines that think. Where in order to pass the test, a computer must be able to carry on a conversation that was indistinctive from a conversation with a human being.
AI definition also includes things like planning, understanding language, recognizing objects and sounds, learning, and problem solving.

Confusing Jargons – AI, ML and many more
Demystifying confusing jargons like AI, ML, Data Science, DL and ANN with no scientific reasoning and meaning can create huge understanding gaps.
“Artificial neural systems, or neural networks, are physical cellular systems which can acquire, store, and utilize experiential knowledge” – Zurada (1992). Like this each one has their own meaning and use cases. One needs to be careful on when to use what for what reasons.
 
Algorithm – The set of instructions !
In an Algorithm set of rules gets followed to solve problems so in short an algorithm is a set of rules or instructions. In machine learning; algorithms are key elements which takes on the data and process all the rules to get some responses. This processing which makes algorithm complex or easy. One thing is clear here more the data more stronger algorithm gets over period of time.

Conclusion – Artificial intelligence is a broad and active area of research, but it’s no longer the sole province of academics; increasingly, companies are incorporating AI into their products. For now AI is controlled by humans and I wish in long term it should remain the same i.e. should never starts or think to control us or should not turns out uncontrollable. Baidu’s speech-to-text services are outperforming humans in similar tasks. Amazon is also applying deep learning for best-in-class product recommendations.
 

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