A road named NoNameUno

These days, Artificial Intellegence > Natural Intellegence. The days of Frankenstien finally arrived. Every high-tech company is investing or at least broadcasting that they are using or very soon would be using AI. Sooooo, I started looking back of what we were doing 30 yrs back in Graduate school ! Back then AI was mostly natural language based expert systems or some Heuristics based expert systems. For example, computer based chase player. Robotics, Newral network etc., were in their dawn days. We did not have many branches like: ML, supervised learning, deep learning etc.  Took a class in AI, later in mid semister dropped out, did not make much sense.

Then came the Statistical / Baysian decision process, and now Ai is as pervasive as Cell Phone. I did a sampling of some of the books in AI, and got stuck with the book - Deep Learning! Looking at the book gave me an immense joy, and disappoint too. The book is wonderfully written, by my first glance of few chapters. Joy was that most of the topics are covered back then in different form and purpose. Like statistical methods, Probablity and Measure toward Discrete Martingale, Operations Research, Stochastic processes etc. Disapointment is there is really a Deep Learning again for me, if I need to look at them again...

Big question is -- How do we make a massivelly parallel machine to learn ? How could we make the machine available for almost all areas of scientific researches ?

There are many areas that needs to be covered before even I could start saying something ...

One such area is Dynamic Programming, that is essential for any optimization problem that has overlapping substructures. Finding such structures and using them needs key insights of the problem at hand.

So I will start with some dynamic programming next.