Some running thoughts on ANNs and AI—1

Go, see if you want to have fun with the attached write-up on ANNs [^] (but please also note the version time carefully—the write-up could change without any separate announcement).

The write-up is more in the nature of a very informal blabber of the kind that goes when people work out something on a research blackboard (or while mentioning something about their research to friends, or during brain-storming session, or while jotting things on the back of the envelop, or something similar).

 


A “song” I don’t like:

(Marathi) “aawaaj waaDaw DJ…”
“Credits”: Go, figure [^]. E.g., here [^]. Yes, the video too is (very strongly) recommended.


Update on 05 October 2018 10:31 IST:

Psychic attack on 05 October 2018 at around 00:40 IST (i.e. the night between 4th and 5th October, IST).

 

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Caste Brahmins, classification, and ANN

1. Caste Brahmins:

First, a clarification: No, I was not born in any one of the Brahmin castes, particularly, not at all in the Konkanastha Brahmins’ caste.

Second, a suggestion: Check out how many caste-Brahmins have made it to the top in the Indian and American IT industry, and what sort of money they have made—already.

No, really.

If you at all bother visiting this blog, then I do want you to take a very serious note of both these matters.

No. You don’t have to visit this blog. But, yes, if you are going to visit this blog, to repeat, I do want you to take  matters like these seriously.

Some time ago, perhaps a year ago or so, a certain caste-Brahmin in Pune from some place (but he didn’t reveal his shakha, sub-caste, gotra, pravar, etc.) had insulted me, while maintaining a perfectly cool demeanor for himself, saying how he had made so much more money than me. Point taken.

But my other caste-Brahmin “friends” kept quiet at that time; not a single soul from them interjected.

In my off-the-cuff replies, I didn’t raise this point (viz., why these other caste-Brahmins were keeping quiet), but I am sure that if I were to do that, then, their typical refrain would have been (Marathi) “tu kaa chiDatos evhaDa, to tar majene bolat hotaa.” … English translation: Why do you get so angry? He was just joking.

Note the usual caste-Brahmin trick: they skillfully insert an unjustified premise; here, that you are angry!

To be blind to the actual emotional states or reactions of the next person, if he comes from some other caste, is a caste-habit with the caste-Brahmins. The whole IT industry is full of them—whether here in India, or there in USA/UK/elsewhere.

And then, today, another Brahmin—a Konkanastha—insulted me. Knowing that I am single, he asked me if I for today had taken the charge of the kitchen, and then, proceeded to invite my father to a Ganesh Pooja—with all the outward signs of respect being duly shown to my father.


Well, coming back to the point which was really taken:

Why have caste-Brahmins made so much money—to the point that they in one generation have begun very casually insulting the “other” people, including people of my achievements?

Or has it been the case that the people of the Brahmin castes always were this third-class, in terms of their culturally induced convictions, but that we did not come to know of it from our childhood, because the elderly people around us kept such matters, such motivations, hidden from us? May be in the naive hope that we would thereby not get influenced in a bad manner? Possible.

And, of course, how come these caste-Brahmins have managed to attract as much money as they did (salaries in excess of Rs. 50 lakhs being averagely normal in Pune) even as I was consigned only to receive “attract” psychic attacks (mainly from abroad) and insults (mainly from those from this land) during the same time period?

Despite all my achievements?

Do take matters like these seriously, but, of course, as you must have gathered by now, that is not the only thing I would have, to talk about. And, the title of this post anyway makes this part amply clear.


2. The classification problem and the ANNs:

I have begun my studies of the artificial neural networks (ANNs for short). I have rapidly browsed through a lot of introductory articles (as also the beginning chapters of books) on the topic. (Yes, including those written by Indians who were born in the Brahmin castes.) I might have gone through 10+ such introductions. Many of these, I had browsed through a few years ago (I mean only the introductory parts). But this time round, of course, I picked them up for a more careful consideration.

And soon enough (i.e. over just the last 2–3 days), I realized that no one in the field (AI/ML) was talking about a good explanation of this question:

Why is it that the ANN really succeeds as well as it does, when it comes to the classification tasks, but not others?

If you are not familiar with Data Science, then let me note that it is known that ANN does not do well on all the AI tasks. It does well only on one kind of them, viz., the classification tasks. … Any time you mention the more general term Artificial Intelligence, the layman is likely to think of the ANN diagram. However, ANNs are just one type of a tool that the Data Scientist may use.

But the question here is this: why does the ANN do so well on these tasks?

I formulated this question, and then found an answer too, and I would sure like to share it with you (whether the answer I found is correct or not). However, before sharing my answer, I want you to give it a try.

It would be OK by me if you answer this question in reference to just one or two concrete classification tasks—whichever you find convenient. For instance, if you pick up OCR (optical character recognition, e.g., as explained in Michael Nielson’s free online book [^]), then you have to explain why an ANN-based OCR algorithm works in classifying those MNIST digits / alphabets.


Hint: Studies of Vedic literature won’t help. [I should know!] OTOH, studies of good books on epistemology, or even just good accounts covering methods of science, should certainly come in handy.

I will give you all some time before I come back on that question.

In the meanwhile, have fun—if you wish to, and of course, if you are able to. With questions of this kind. (Translating the emphasis in the italics into chaste Marathi: “laayaki asali tar.” Got it?)


A song I like:
(Marathi) “ooncha nicha kaahi neNe bhagawant”
Lyrics: Sant Tukaram
Music and Singer: Snehal Bhatkar

 

Hushshshsh…

The title word of this post is Marathi for “phew!”—not for “hush hush.” (But, to me, the Marthi word is more expressive. [BTW, the “hu” is to be pronounced as “hoo”.])

The reason for this somewhat accentuated and prolonged exhalation is this: I am done with the version “0.1-beta” of my note on flux (see my last post). I need a break.

As of now, this note is about 27 pages, and with figures and some further (< 5%) additions, the final number of pages for the version 0.1 should easily go into the early 30s. … To be readable, it will have to brought down to about 15 pages or fewer, including diagrams. Preferably, < 10 pages. Some other day. For now, I find that I have grown plain sick and tired of working on that topic. I need to get away from it all. I am sure that I will return to it later on—may be after a month or so. But for the time being, I simply need a break—from it. I’ve had enough of this flux and vectors and tensors thing. … Which brings me to the next topic of this post.

There are also other announcements.


I think that I have also had enough of QM.

QM was interesting, very interesting, to me. It remained that way for some four decades. But now that I have cracked it (to my satisfaction), my interest in the topic has begun dwindling down very rapidly.

Sure I will conduct a few simulations, deliver the proposed seminar(s) I had mentioned in the past, and also write a paper or two about it. But I anticipate that I won’t go much farther than what I have already understood. The topic, now, simply has ceased to remain all that interesting.

But, yes, I have addressed all the essential QM riddles. That’s for certain.


And then, I was taking a stock of my current situation, and here are a few things that stood out:

  • I am not getting an academic job in Pune (because of the stupid / evil SPPU rules), and frankly, the time when a (full) Professor’s job could have meant something to me is already over. If I were to get such a job well in time—which means years ago—then I could have done some engineering research (especially in CFD), guided a few students (in general in computational science and engineering), taught courses, developed notes, etc. But after having lost a decade or so due to that stupid and/or evil Metallurgy-vs-Mechanical Branch Jumping issue, I don’t have the time to pursue all that sort of a thing, any more.
  • You would know this: All my savings are over; I am already in debts.
  • I do not wish to get into a typical IT job. It could be well paying, but it involves absolutely no creativity and originality—I mean creativity involving theoretical aspects. Deep down in my heart, I remain a “theoretician”—and a programmer. But not a manager. There is some scope for creativity in the Indian IT industry, but at my “seniority,” it is mostly limited, in one way or the other, only to “herd-management” (to use an expression I have often heard from my friends in the industry). And, I am least bothered about that. So, to say that by entering the typical Indian IT job, my best skills (even “gifts”) would go under-utilized, would be an understatement.
  • For someone like me, there is no more scope, in Pune, in the CFD field either. Consultants and others are already well established. I could keep my eyes and ears open. But it looks dicey to rely on this option. The best period for launching industrial careers in CFD here was, say, up to the early naughties. … I still could continue with some research in CFD. But guess it no longer is a viable career option for me. Not in Pune.
  • Etc.

However, all is not gloomy. Not at all. Au contraire.

I am excited that I am now entering a new field.

I will not ask you to take a guess. This career route for people with my background and skills is so well-established by now, that there aren’t any more surprises left in it. Even an ANN would be able to guess it right.

Yes, that’s right. From now on, I am going to pursue Data Science.


This field—Data Science—has a lot of attractive features, as far as I am concerned. The way I see it, the following two stand out:

  1. There is a very wide variety of application contexts; and
  2. There is a fairly wide range of mathematical skills that you have to bring to bear on these problems.

Notice, the emphasis is on the width, not on the depth.

The above-mentioned two features, in turn, lead to or help explain many other features, like:

  1. A certain open ended-ness of solutions—pretty much like what you have in engineering research and design. In particular, one size doesn’t fit all.
  2. A relatively higher premium on the individual thinking skills—unlike what your run-of-the-mill BE in CS does, these days [^].

Yes, Data Science, as a field, will come to mature, too. The first sign that it is reaching the first stage of maturity would be an appearance of a book like “Design Patterns.”

However, even this first stage is, I anticipate, distant in future. All in all, I anticipate that the field will not come to mature before some 7–10 years pass by. And that’s long enough a time for me to find some steady career option in the meanwhile.


There are also some other plus points that this field holds from my point of view.

I have coded extensively—more than 1 lakh (100,000) lines of C++ code in all, before I came to stop using C++, which happened especially after I entered academia. I am already well familiar with Python and its eco-system, though am not an expert when it comes to writing the fastest possible numerical code in Python.

I have handled a great variety of maths. The list of equations mentioned in my recent post [^] is not even nearly exhaustive. (For instance, it does not even mention whole topics like probability and statistics, stereology, and many such matters.) When it comes to Data Science, a prior experience with a wide variety of maths is a plus point.

I have not directly worked with topics like artificial neural networks, deep learning, the more advanced regression analysis, etc.

However, realize that for someone like me, i.e., someone who taught FEM, and had thought of accelerating solvers via stochastic means, the topic of constrained optimization would not be an entirely unknown animal. Some acquaintance has already been made with the conjugate gradient (though I can’t claim mastery of it). Martingales theory—the basic idea—is not a complete unknown. (I had mentioned a basic comparison of my approach vis-a-vis the simplest or the most basic martingales theory, in my PhD thesis.)

Other minor points are these. This field also (i) involves visualization abilities, (ii) encourages good model building at the right level of abstraction, and (iii) places premium on presentation. I am not sure if I am good on the third count, but I sure am confident that I do pretty well on the first two. The roots of all my new research ideas, in fact, can be traced back to having to understand physical principles in 3+1 D settings.


Conclusion 1: I should be very much comfortable with Data Science. (Not sure if Data Science itself (i.e., Data Scientists themselves) would be comfortable with me or not. But that’s something I could deal later on.)

Conclusion 2: Expect blogging here going towards Data Science in the future.


A Song I Like:

(Marathi) “uff, teri adaa…”
Music: Shankar-Ahsaan-Loy
Singer: Shankar Mahadevan
Lyrics: Javed Akhtar

[By any chance, was this tune at least inspired (if not plagiarized) from some Western song? Or is it through and through original? …In any case, I like it a lot. I find it wonderful. It’s upbeat, but not at all banging on the ears. (For contrast, attend any Ganapati procession, whether on the first day, the last day, or any other day in between. You will have ample opportunities to know what having your ears banged out to deafness means. Nay, these opportunities will be thrust upon you, whether you like it or not. It’s our “culture.”)]

 

 

Links…

Here are a few interesting links I browsed recently, listed in no particular order:


“Mathematicians Tame Turbulence in Flattened Fluids” [^].

The operative word here, of course, is: “flattened.” But even then, it’s an interesting read. Another thing: though the essay is pop-sci, the author gives the Navier-Stokes equations, complete with fairly OK explanatory remarks about each term in the equation.

(But I don’t understand why every pop-sci write-up gives the NS equations only in the Lagrangian form, never Eulerian.)


“A Twisted Path to Equation-Free Prediction” [^]. …

“Empirical dynamic modeling.” Hmmm….


“Machine Learning’s `Amazing’ Ability to Predict Chaos” [^].

Click-bait: They use data science ideas to predict chaos!

8 Lyapunov times is impressive. But ignore the other, usual kind of hype: “…the computer tunes its own formulas in response to data until the formulas replicate the system’s dynamics. ” [italics added.]


“Your Simple (Yes, Simple) Guide to Quantum Entanglement” [^].

Click-bait: “Entanglement is often regarded as a uniquely quantum-mechanical phenomenon, but it is not. In fact, it is enlightening, though somewhat unconventional, to consider a simple non-quantum (or “classical”) version of entanglement first. This enables us to pry the subtlety of entanglement itself apart from the general oddity of quantum theory.”

Don’t dismiss the description in the essay as being too simplistic; the author is Frank Wilczek.


“A theoretical physics FAQ” [^].

Click-bait: Check your answers with those given by an expert! … Do spend some time here…


Tensor product versus Cartesian product.

If you are engineer and if you get interested in quantum entanglement, beware of the easily confusing terms: The tensor product and the Cartesian product.

The tensor product, you might think, is like the Cartesian product. But it is not. See mathematicians’ explanations. Essentially, the basis sets (and the operations) are different. [^] [^].

But what the mathematicians don’t do is to take some simple but non-trivial examples, and actually work everything out in detail. Instead, they just jump from this definition to that definition. For example, see: “How to conquer tensorphobia” [^] and “Tensorphobia and the outer product”[^]. Read any of these last two articles. Any one is sufficient to give you tensorphobia even if you never had it!

You will never run into a mathematician who explains the difference between the two concepts by first directly giving you a vague feel: by directly giving you a good worked out example in the context of finite sets (including enumeration of all the set elements) that illustrates the key difference, i.e. the addition vs. the multiplication of the unit vectors (aka members of basis sets).

A third-class epistemology when it comes to explaining, mathematicians typically have.


A Song I Like:

(Marathi) “he gard niLe megha…”
Singers: Shailendra Singh, Anuradha Paudwal
Music: Rushiraj
Lyrics: Muralidhar Gode

[As usual, a little streamlining may occur later on.]

Machine “Learning”—An Entertainment [Industry] Edition

Yes, “Machine ‘Learning’,” too, has been one of my “research” interests for some time by now. … Machine learning, esp. ANN (Artificial Neural Networks), esp. Deep Learning. …

Yesterday, I wrote a comment about it at iMechanica. Though it was made in a certain technical context, today I thought that the comment could, perhaps, make sense to many of my general readers, too, if I supply a bit of context to it. So, let me report it here (after a bit of editing). But before coming to my comment, let me first give you the context in which it was made:


Context for my iMechanica comment:

It all began with a fellow iMechanician, one Mingchuan Wang, writing a post of the title “Is machine learning a research priority now in mechanics?” at iMechanica [^]. Biswajit Banerjee responded by pointing out that

“Machine learning includes a large set of techniques that can be summarized as curve fitting in high dimensional spaces. [snip] The usefulness of the new techniques [in machine learning] should not be underestimated.” [Emphasis mine.]

Then Biswajit had pointed out an arXiv paper [^] in which machine learning was reported as having produced some good DFT-like simulations for quantum mechanical simulations, too.

A word about DFT for those who (still) don’t know about it:

DFT, i.e. Density Functional Theory, is “formally exact description of a many-body quantum system through the density alone. In practice, approximations are necessary” [^]. DFT thus is a computational technique; it is used for simulating the electronic structure in quantum mechanical systems involving several hundreds of electrons (i.e. hundreds of atoms). Here is the obligatory link to the Wiki [^], though a better introduction perhaps appears here [(.PDF) ^]. Here is a StackExchange on its limitations [^].

Trivia: Kohn and Sham received a Physics Nobel for inventing DFT. It was a very, very rare instance of a Physics Nobel being awarded for an invention—not a discovery. But the Nobel committee, once again, turned out to have put old Nobel’s money in the right place. Even if the work itself was only an invention, it did directly led to a lot of discoveries in condensed matter physics! That was because DFT was fast—it was fast enough that it could bring the physics of the larger quantum systems within the scope of (any) study at all!

And now, it seems, Machine Learning has advanced enough to be able to produce results that are similar to DFT, but without using any QM theory at all! The computer does have to “learn” its “art” (i.e. “skill”), but it does so from the results of previous DFT-based simulations, not from the theory at the base of DFT. But once the computer does that—“learning”—and the paper shows that it is possible for computer to do that—it is able to compute very similar-looking simulations much, much faster than even the rather fast technique of DFT itself.

OK. Context over. Now here in the next section is my yesterday’s comment at iMechanica. (Also note that the previous exchange on this thread at iMechanica had occurred almost a year ago.) Since it has been edited quite a bit, I will not format it using a quotation block.


[An edited version of my comment begins]

A very late comment, but still, just because something struck me only this late… May as well share it….

I think that, as Biswajit points out, it’s a question of matching a technique to an application area where it is likely to be of “good enough” a fit.

I mean to say, consider fluid dynamics, and contrast it to QM.

In (C)FD, the nonlinearity present in the advective term is a major headache. As far as I can gather, this nonlinearity has all but been “proved” as the basic cause behind the phenomenon of turbulence. If so, using machine learning in CFD would be, by the simple-minded “analysis”, a basically hopeless endeavour. The very idea of using a potential presupposes differential linearity. Therefore, machine learning may be thought as viable in computational Quantum Mechanics (viz. DFT), but not in the more mundane, classical mechanical, CFD.

But then, consider the role of the BCs and the ICs in any simulation. It is true that if you don’t handle nonlinearities right, then as the simulation time progresses, errors are soon enough going to multiply (sort of), and lead to a blowup—or at least a dramatic departure from a realistic simulation.

But then, also notice that there still is some small but nonzero interval of time which has to pass before a really bad amplification of the errors actually begins to occur. Now what if a new “BC-IC” gets imposed right within that time-interval—the one which does show “good enough” an accuracy? In this case, you can expect the simulation to remain “sufficiently” realistic-looking for a long, very long time!

Something like that seems to have been the line of thought implicit in the results reported by this paper: [(.PDF) ^].

Machine learning seems to work even in CFD, because in an interactive session, a new “modified BC-IC” is every now and then is manually being introduced by none other than the end-user himself! And, the location of the modification is precisely the region from where the flow in the rest of the domain would get most dominantly affected during the subsequent, small, time evolution.

It’s somewhat like an electron rushing through a cloud chamber. By the uncertainty principle, the electron “path” sure begins to get hazy immediately after it is “measured” (i.e. absorbed and re-emitted) by a vapor molecule at a definite point in space. The uncertainty in the position grows quite rapidly. However, what actually happens in a cloud chamber is that, before this cone of haziness becomes too big, comes along another vapor molecule, and “zaps” i.e. “measures” the electron back on to a classical position. … After a rapid succession of such going-hazy-getting-zapped process, the end result turns out to be a very, very classical-looking (line-like) path—as if the electron always were only a particle, never a wave.

Conclusion? Be realistic about how smart the “dumb” “curve-fitting” involved in machine learning can at all get. Yet, at the same time, also remain open to all the application areas where it can be made it work—even including those areas where, “intuitively”, you wouldn’t expect it to have any chance to work!

[An edited version of my comment is over. Original here at iMechanica [^]]


 

“Boy, we seem to have covered a lot of STEM territory here… Mechanics, DFT, QM, CFD, nonlinearity. … But where is either the entertainment or the industry you had promised us in the title?”

You might be saying that….

Well, the CFD paper I cited above was about the entertainment industry. It was, in particular, about the computer games industry. Go check out SoHyeon Jeong’s Web site for more cool videos and graphics [^], all using machine learning.


And, here is another instance connected with entertainment, even though now I am going to make it (mostly) explanation-free.

Check out the following piece of art—a watercolor landscape of a monsoon-time but placid sea-side, in fact. Let me just say that a certain famous artist produced it; in any case, the style is plain unmistakable. … Can you name the artist simply by looking at it? See the picture below:

A sea beach in the monsoons. Watercolor.

If you are unable to name the artist, then check out this story here [^], and a previous story here [^].


A Song I Like:

And finally, to those who have always loved Beatles’ songs…

Here is one song which, I am sure, most of you had never heard before. In any case, it came to be distributed only recently. When and where was it recorded? For both the song and its recording details, check out this site: [^]. Here is another story about it: [^]. And, if you liked what you read (and heard), here is some more stuff of the same kind [^].


Endgame:

I am of the Opinion that 99% of the “modern” “artists” and “music composers” ought to be replaced by computers/robots/machines. Whaddya think?

[Credits: “Endgame” used to be the way Mukul Sharma would end his weekly Mindsport column in the yesteryears’ Sunday Times of India. (The column perhaps also used to appear in The Illustrated Weekly of India before ToI began running it; at least I have a vague recollection of something of that sort, though can’t be quite sure. … I would be a school-boy back then, when the Weekly perhaps ran it.)]

 

Miscellaneous: my job situation, the Tatas, and taking a break…

The Diwali is here, already!

This year’s Diwali isn’t going great for me. I am still jobless—without reason or rhyme. It is difficult to enjoy Diwali against that backdrop.


As you know, engineering colleges affiliated to the Savitribai Phule Pune University (SPPU for short) have been telling me that my Metallurgy+Mechanical background isn’t acceptable, even though the rules have changed to the contrary, and say that I now qualify (in my interpretation).

Recently I attended an interview, and it seems like I may be able to obtain a clear-cut answer on my eligibility (i.e. the equivalence of Metallurgy and Mechanical) from SPPU.

The thing is, SPPU has been having no Dean for its Engineering faculty for about a year or more by now, because the Maharashtra state government hasn’t so far undertaken the procedure to elect (or select) the next Dean.

This recent interview which I mentioned above, was for a Principal’s post, and I was short-listed. As is the common practice here, the short-listed candidates were all invited at the same time, and thus, I had an opportunity to interact with these other, senior-level professors.

These senior professors (some of them already active as Principals at other colleges) told me that it isn’t just SPPU, but all the universities in Maharashtra. They all are currently having only an in-charge or acting Dean for their engineering faculties, because the procedure to appoint the next set of Deans, which was due to occur this month (October) has once again been postponed by yet another year.

Policy decisions such as the Metallurgy and Mechanical equivalence at SPPU have been pending, they told me, because the acting Dean can easily say that he has no powers to do that. Though the other universities are clear that I would qualify, if a genius running an engineering college under SPPU thinks that I don’t, then the matter normally goes to the Dean. If the Dean is not official, if he is only acting, he doesn’t want to take “risk,” so he takes no decision at all. Not just the equivalence issues, there are certain other policy decisions too, which have been pending, they told me. The in-charge Deans have been processing only the routine work, and not taking any policy decisions. The next set of Deans were expected to get appointed by June 2016, and then, after postponement, by October 2016. (“achhchhe din!”)

Now that the appointments have been officially postponed by one whole year (“achhchhe din,” again!), the colleges themselves have begun going to the universities for obtaining the professor’s approvals, arguing that faculty approvals is a routine matter, and that they cannot properly function without having approved faculty.

Thus, the university (SPPU) has begun appointing panels for faculty interviews. There has been a spate of faculty recruitment ads after the current semester got going (“achhchhe din!”).

The particular interview which I attended, these other candidates informed me, was with a University-appointed panel—i.e., of the kind which allows approvals. (Otherwise, the appointments are made by the affiliating colleges on their own, but only on a temporary, ad-hoc basis, and therefore, for a limited time.)

Please note, all the above is what I gathered from their talk. I do not know what the situation is exactly like. (Comments concerning “achhchhe din!,” however, are strictly mine.)

But yes, it did turn out that the interview panel here was from the university. Being a senior post (Principal), the panel included both the immediately past Dean (Prof. G. K. Kharate) and the new, in-charge Dean (Prof. Dr. Nerkar, of PVG College, Pune).

During my interview, if the manner in which Prof. Kharate (the past Dean) now said things is any indication, it means that I should now qualify even in the SPPU. This would be according to the new GR about which I had written a few months ago, here [^]. Essentially, Prof. Kharate wondered aloud as to why there was any more confusion because the government had already clarified the situation with the new rules.

I took that to mean that I qualify.

Of course, these SPPU geniuses are what they are, and therefore, they—these same two SPPU Deans—could very well say, in future, that I don’t qualify. After all, I didn’t ask them the unambiguous question “With my Metallurgy background, do I qualify for a Mechanical Engineering (full) Professor’s job or not? Yes, or no?;”  and they didn’t then answer in yes or no terms.

Of course, right in the middle of an on-going job interview couldn’t possibly have been the best time and place to get them to positively confirm that I do qualify. (Their informal indications, however, were clearly along the lines that I do qualify.)

Now that the Diwali break has arrived, the colleges are closed, and so, I would be able to approach Prof. Dr. Nerkar (the currently acting/in-charge Dean) only after a week or so. I intend to do that and have him pin down the issue in clear-cut terms.

At the conclusion of my interview, I told the interview committee exactly the same thing which I told you at the beginning of this post, viz., that this Diwali means darkness to me.

But yes, we can hope that Prof. Dr. Nerkar would issue the clarification at least after the Diwali. If not, I intend to approach Prof. Dr. Gade, the Vice-Chancellor of SPPU. … I could easily do that. I am very social, that way.

And, the other reason is, at the university next door—the Shivaji University—they did answer my email asking them to clarify these branch-equivalence issues. The SPPU is the worst university among the three in the Western Maharashtra region (the other two being, the University of Mumbai and the Shivaji University Kolhapur). [I want to teach in Pune only because it’s my home-town, and thus convenient to me and my family, not because SPPU’s standards are high.]

Anyway, I now do have something in hand to show Prof. Dr. Gade when I see him—the letter from the Shivaji University staff. … At the Shivaji University, I didn’t have to go and see anyone in person there—not even the administrative staff let alone the acting Dean or the Vice-Chancellor. The matter got clarified just via a routine email. There is a simple lesson that SPPU may learn from the Shivaji and Mumbai universities, and under Prof. Dr. Gade, I hope they do.

… Of course, I do also hope that I don’t have to see Prof. Dr. Gade (the Vice-Chancellor). I do hope that meeting just Prof. Dr. Nerkar (the in-charge Dean) should be sufficient.

If they refuse me an appointment, I will get even more social than my usual self—I will approach certain eminent retired people from Pune such as Dr. Bhatkar (the founder of C-DAC) or Dr. Mashelkar (the former Director General of CSIR, India).

Here is a hoping that I don’t have to turn into a social butterfly, and that soon after Diwali, the matters would get moving smoothly. Let’s hope so.

And with that hope in my heart, let me wish you all a very happy and prosperous Diwali. … As to me, I will try to make as much good of a bad situation that I can.


Still, I don’t find myself to be too enthusiastic. I don’t feel like doing much anything. [In a way, I feel tired.] Therefore, I am going to take a break from blogging.

I have managed to write something more on the concept of space. I found that I should be able to finish this series now. I had begun it in 2013; see here [^].

Concepts like space and time are very deep matters, and I still have to get enough clarity on a few issues, though all such remaining issues are relatively quite minor. I should be able to get through them in almost no time.

From the new material which I have written recently, I guess it would be enough to write just one or two posts, and then the series would get over. What then will remain would be mostly polemics, and that part can be taken on the fly whenever the need to do so arises.

I may also think of giving some indications on the concept of time, but, as I said, I find myself too lacking in enthusiasm these days. Being jobless—despite having the kind of resume I have—does have a way of generating a certain amount of boredom in you, a certain degree of disintegration at least to your energy and enthusiasm, even if not to your soul.


So, let’s see. Let the Diwali vacations get over, and I should come back and resume my blogging, telling you what all transpired in my meeting/interaction with the in-charge Dean, and the related matters.


Since I am not going to be blogging for some time, let me note a couple of notable things.

One, the US Presidential elections. I am not at all interested in that. So let me leave it aside.

Two, the Tata Sons issue. It does interest me a bit, so let me write down a bit on it.


I was not as surprised as some of the newspaper editorials and columns say they were. The days of JRD are long gone. The Tatas already were a changed company when Cyrus Mistry took over from Ratan Tata.

Once I returned from the USA in 2001, despite my resume, I never got a chance with the new Tatas (either at TRDDC or at TCS). Such a thing would have been unthinkable during JRD’s times. … Even keeping it aside, what all I observed about the Tatas over the past 1.5 decades was enough for me not to be at all surprised by something like the current fiasco.

No, Prof. Pratap Bhanu Mehta, reading things from where I sit, the Tata fiasco doesn’t do any significant harm to the social legitimacy of Capitalism in India. People—common people—have long ago observed and concluded what had to be. If what the common people think were to be caricatured, it would look like the position you ascribe to the “cynics”. But no, IMO, this position isn’t cynical. To carry realistic impressions about hallowed icons is not quite the same as being a cynic.

Yes, as Harsh Goenka astutely pointed out in his comment in today’s ToI, Ratan Tata’s tenure coincided with the semi-liberalization era: 1991–2012. Whenever you come to compare Ratan Tata with Cyrus Mistry, you cannot overlook that broad context.

I have always thought that JRD left too big shoes for any one to fill in. But, with due respect to Ratan Tata, I still would have to say that no one could possibly entertain thinking in similar terms, when it comes to Ratan Tata’s retirement.

Looking at the facts and figures reported this week, I don’t think Mistry was doing a lousy job. Reading through his letter, I in fact marvel at how well he understood his job—and for this reason, I speculate that he must have been doing his job pretty well. …

Realize, the letter was written within a day or two after an unceremonious removal from the top post of a 100+ years old Indian icon, a $100 billion behemoth. Seen against this backdrop, the letter is extraordinarily restrained; it shows an unusual level of maturity. To expect any more “restraint” is to actually confess ignorance of such basic things as human nature and character. (Sadhus, let me remind you, are known to kill each other in their fights at the Kumbh Mela, just for the priority in taking the Shahi Snaan. Keep that in mind the next time you utter something on nobility of character and culture.)

And yes, I also had come to think that the Nano project was doomed—I just didn’t have the sales and profitability figures, which got reported only today. My reasons were simple; they were purely from an ordinary consumer’s point of view. If you are selling the Nano at around Rs. 2.5 lakhs, just think of the alternatives that the consumer has today: you could get a used car in a “good enough” condition, not just Maruti Alto but even a somewhat more used Toyota Innova, at roughly the same price.

Anyway, I don’t understand these corporate matters much, so let me shut up.


But, yes, knowing the house of Tatas and their brand managers, I can predict right away that in the near future, you are going to see the Tatas announce a product like “Tata Quantum Dot,” or “Tata Silicon Dot,” or something like that. … Why do I think so?

I started writing on quantum mechanics, and roughly around the same time, the cable-less Internet, based on the electromagnetic waves (mobile, Wi-Fi) was getting going in India. So, the Tatas came out with the Tata Photon. Yes, “Photon”. The Tata Photon. … It meant nothing more than the usual Internet dongle (2G, and then 3G) that everybody else was already supplying anyway. (And the Tata Photon never worked too well in areas other than in the Mumbai city.)

Then, the USA was abuzz with the catch-words like nano-technology, and the Tata brand managers decided to do something with that name, and thus came the Tata “Nano.” By now, every one knows what it means.

Today, the USA and other countries are abuzz with words like “Quantum Supremacy” and things like that. You can only expect some Tata brand managers to latch on to this buzzword, and launch a product like, say, Tata Quantum Dot or Tata Silicon Dot—or both!

Tata Silicon Dot, I predict, would signal the arrival of the house of Tatas into the business of supplying the sand required for civil engineering construction.

Tata Quantum Dot, on the other hand, would mean that the house of Tatas had taken an entry into the business of plastic dart toys. Or, the business of the “bindi”s that ladies wear. That is what the house of Tatas would mean by the name Tata Quantum Dot.

And here our policy analysts think that something happening to the house of Tatas is going to affect the credibility or social legitimacy of Capitalism itself in India! Oh wow!!

Ummm…. Does any policy research center in India have any data on the proportion of the private business in the overall Indian economy (including both the organized and the unorganized sectors) over the years, say starting from 1930s? Also, the quantum of the government expenditure in the Indian economy, and its proportion in the national GDP over the same period? Would they care to share it, please? Or is it that they don’t have to look at such data for their policy research purposes? … As to me, I have been on the lookout for data like that for quite some time now, but never could see it compiled anywhere. That’s why the request. Please drop me a line if you spot a reliable source.

OK, bye for now.


A Song I Like:

Since I won’t be blogging for a while, let me give away the “other” song right away, I mean the song which had somehow happened to strike me as being similar to the song “too laali hai savere waali”; see the Song I Like section here [^]. This other song is:

(Hindi) “bhigee bhigee raaton mein…”
Music: R. D. Burman
Singers: Kishore Kumar, Lata Mangeshkar
Lyrics: Anand Bakshi

I take the “raaga” of the earlier song (“too laali hai”) as “pahaaDee”—or at least that’s what I got from an Internet search. The “raaga” of the current song (“bhigee…”) isn’t listed at any Web site. Assuming it’s not “pahaaDee” (or a variant on that), the question becomes, why the two songs might have struck at least somewhat similar to me—why, humming one song, I very naturally and casually happened to remember the other song.

It would be interesting to see if Data Science can be used to spot (and quantify) similarities in songs. The traditional music theory puts too much emphasis, IMO, on “raaga” alone. But there can be other bases for similarities, too. The sound patterns of musical pieces, I think, don’t get exhaustively (and at times not even essentially) characterized by the idea of the “raaga” alone. Talking of these two songs in particular, the similarity I caught might have been connected with certain ups and downs in notes with a somehow similarly sounding tempo. The style of the tunes sounds similar. Guess Data Science might be able to shed some light on things like that…. It would be interesting, to look into that, no? That’s what I had thought…

I mean, I had thought. … But then, these days, as I said, I am unable to work on this topic, too…  I just don’t have any enthusiasm left. Honest. I somehow finished this post, only because I won’t be posting for a while…

So, there. Bye for now, take care, and best!


[E&OE]