How To Read More

Yesterday, I bought Rs. 1000 worth of books, and also spent Rs. 1000 on a family movie night. Somehow, my psychology is weird enough that the money spent on books seemed like an extravagance to me, whereas the dinner was no big deal – something I do regularly. But, when I think about it, I’ll spend weeks reading the books, then my wife will read them, and later I’ll lend those books to other people. In terms of value/entertainment-per-person-per-hour, books are easily 10 to 100x cheaper than any other thing I spend money on.

In other words, I should be spending much more on books.

Buying, Borrowing, and Lending Books

  • Maybe buying: So, I’ve started buying books. And, I often buy even those books where there is only a small chance of me reading it. Because if I buy 10 books, and end up reading only 1 of them, that’s still a good investment. My mother comes from the generation where buying a book is a big decision – she reads reviews in newspapers, asks her friends if any of them have read the book, goes to the store and spends 10 minutes browsing the book, and only then considers buying it. I am slowly converting her to the philosophy that if she even thought “maybe I should check out this book” I will go ahead and buy it on Flipkart/Amazon.
  • Indiscriminate Lending: One of the biggest problems with lending books, is the fear that they’ll not get returned. Trying to keep track of who borrowed which book, and asking for it back is too much work. I stopped worrying about this long ago. I lend books indiscriminately, and don’t worry about whether it will come back. There have been 2 or 3 cases where I ended up buying a second copy of a book because I needed the book, and couldn’t figure out whom I’d lent it to. This is a small price to pay for being able to spread good books.
    • The one thing I do to increase chances of getting books back, is that on the book, I write “KABRA” in really large block letters using a thick marker pen. This ensures that the borrower never forgets whom they borrowed a book from, and eventually they return it.
  • Buying Second Hand Books: There’s a raddi-paper shop on Baner Road that keeps a stack of second hand books, and sells them at really low prices – Rs. 10 or 20 or 30 depending on the size of the book. I go there once every few months, and end up buying 5 to 10 books on each visit. Being able to buy books so cheaply really helps with making it easier to do the maybe buying and the indiscriminate lending described above.

How my reading increased in the last few years

I used to read a lot in my childhood. And this significantly reduced after I started working. Only in the last few years, I’ve managed to again pick up a habit of reading regularly. I think this is because of 3 major things I did: setting up the Kindle app on my smartphone, subscribing to an online library which delivers physical books to my door with just a click of the mouse, and setting up reading queues as described below.

  • Reading Queues: One of the problems I used to have earlier is that when I heard about a book, I was usually too busy to even think about reading, and later when I was less busy, I wouldn’t have appropriate books handy. This might be a problem specific to my and how I function, but I’ve managed to get around it by having reading queues.
    • Reading Queue #1: The online library that I use, BigBooks, allows me to create a queue of books that I want to someday borrow from the library. Whenever I hear about some book that I want to read (usually through social media, or my friends), I check if BigBooks has a copy of that book, and add it to my queue. So, when I am done with the current book, I simply go to the BigBooks website, and ask them to deliver the next book. They randomly pick one book from my queue and send it across.
      Note the important thing here: A book get added to the queue when I hear about it; and I get it in my hand when I have time to read it. This separation has significantly increased my reading.
    • Reading Queue #2: For books that are not available with the library, I usually buy a kindle version and have it delivered to my phone. This book now sits on my phone, ready for me whenever I have some free time – this can be while commuting, while waiting for a meeting to start, while standing in some line somewhere. I read in small chunks of time. It’s amazing how much reading you can get done this way. I finished all of Crime and Punishment by just reading it during the interstitial gaps in my days.
    • Reading Queue #3: Whenever I find an article online that seems interesting, but is too long for me to read right away, I use Amazon’s “Send to Kindle” feature to send that article to my Kindle App on my smartphone. This article now sits on my Kindle app until I read it – either in the next few days, or even weeks later, depending upon how busy I am. In this age of 140-character updates, being able to read long, well thought out articles is a superpower.

Books and Children

  • Reading is one of the most important habits you can inculcate in a child.
  • Many parents have strong feelings that children should read good books, or useful books, for some definition of good/useful. I don’t agree with this thinking. It doesn’t matter what the child reads. Anything is fine. Even if the parents think it is trash. Juvenile stuff like Captain Underpants, shallow romances like Twilight Series or Mills and Boon, is all fine. Any kind of reading helps the child in the long run.
  • It’s not easy to get a child to take up reading. With TV and computer games competing for their attention, books suffer, and parents exhortations don’t really work. In the last few years, I’ve seen that the more I and meetu read in their presence, the more the kids have started reading. And of course, limiting the amount of “screen” based activities they’re allowed in a day.
  • Buy and keep appropriate books around the house. You never know when a child will get interested in which book. I’ve had cases of my kids suddenly pick up and read a book years after I bought it and asked them to read it.

As evaluation capabilities of employers improves, importance of conventional degrees will decline -DB Phatak, IIT Bombay

Recently, I heard Prof D.B. Phatak of IIT Bombay speak at ACM India’s Workshop on Computing Curricula. He talked about various ways in which MOOCs and technology will (should?) transform higher education in India.

Here are a few points I found interesting:

  • Current universities in India have a rigid course structure. This leads to problems like: Smarter students cannot learn fast. Slower students cannot learn slower, unless they fail the course, in which case, they get exactly double the amount of time. If you already know the material of a course, you cannot prove this and skip the course.

  • This is arrogance from the Universities. In any other industry, this kind of behavior would not be accepted by the customers. Why do students still flock to universities?

  • Employers currently recognize only conventional degrees from ‘reputed’ universities, and hence, to get jobs, students submit to the unjustified arrogance of universities.

  • This will change. A degree from a university is just a first filter. Employers really care only about your capabilities, and as they get better at evaluating the capabilities of students reliably and scalably, especially through the use of technology, the reliance on conventional degrees from conventional universities will reduce.

I take this to mean that more and more employers will start using automated evaluation technology like Reliscore (which DBP mentioned in his talk!) to evaluate the capabilities of students instead of relying on conventional degrees, and we will see the rise of self-taught students who learn from MOOCs.

IBM’s Watson supercomputer tackles the problem of creativity in cooking

IBM’s supercomputer research team has been pushing the boundaries of what computers are capable of. Their Deep Blue first beat Kasparov at chess almost 20 years ago. Later, IBM’s Watson beat Ken Jennings at Jeopardy. And now the same Watson is tackling the most difficult problem yet – cooking and creativity.

IBM Research has begun work on an unnamed cyberchef, an AI system designed to create new dishes that can delight our palates at their theoretical peaks of enjoyment.

Why bother teaching a computer how to cook? Of course, the first reason is that it advances computer science. But there is another interesting angle. The supercomputer could cook up recipes that have never been seen by man, because there are some things that computer are just better than humans at:

For example:

In the case of the flavorbot, these “new things” IBM is after range from spotting underrated, highly flavorful ingredients (like black tea, bantu beer and cooked apples), strange-but-tasty flavor pairings (like white chocolate and caviar, jamaican rum and blue cheese, or even bell pepper and black tea), and even whole recipes, complete with basic preparation steps.

And how does Watson do this? Unsurprisingly, this is rather difficult. More interestingly, lots of science and maths comes into play here.

This is a high level description of what the AI needs to do:

To generate these food leads, if you will, AI cross references three databases of information:

  • A recipe index containing tens of thousands of existing dishes that allows the system to infer basics like “what makes a quiche a quiche”
  • Hedonic psychophysics, which is essentially a quantification of whether people like certain flavor compounds at the molecular level
  • Chemoinformatics, which sort of marries these two other databases, as it connects molecular flavor compounds to actual foods they’re in

And here is a journalist’s article about the results; he was sent a bottle of Watson’s Bengali Butternut Barbeque Sauce and this is what he found:

When I unwrapped the brightly colored box and found the bottle inside, I immediately flipped to the back label. Most BBQ sauces start with ingredients like vinegar, tomatoes, or even water, but IBM’s stands out from the get go. Ingredient one: White wine. Ingredient two: Butternut squash.

The list contains more Eastern influences, such as rice vinegar, dates, cilantro, tamarind (a sour fruit you may know best from Pad Thai), cardamom (a floral seed integral to South Asian cuisine) and turmeric (the yellow powder that stained the skull-laden sets of True Detective) alongside American BBQ sauce mainstays molasses, garlic, and mustard.

I pour a bit of the bottle onto a plate of roasted tofu and broccoli–even a pork lover has gotta watch his cholesterol–and tentatively took a bite. Watson’s golden sauce may have the pulpy consistency of baby food, but it packs a surprising amount of unique flavor.

Immediately, you can taste the sweet warmth of the wine and the squash. The tamarind blends seamlessly, backed by a duo of vinegars, to tickle your tongue with just the right amount of tartness. The other flavors combine to leave an indefinable, warm aftertaste that, as you have a few more bites, actually heats your mouth–thanks to Thai chiles

This resulted in a reddit discussion, and one of the people working on this project showed up to share details of how exactly it works:

In a nutshell, however, Watson consumes massive amounts of recipes from different sources and then parses out the ingredients and steps. It also takes in information about the basic flavor compounds in ingredients, the general nature of ingredients, and, perhaps most interesting, a database of the “pleasantness” of flavor compounds, and a few other things that really make up Watson’s “secret sauce”.

From there it’s a collaborative creative process between chef and watson. It typically starts with an ingredient. Let’s say “cardamom”. Watson then searches the database, which is a pretty straight forward process, for the types of cuisine that have that ingredient. For cardamom there are about 100 different cuisines from Indian to Swedish to Bhutani and Barbadian that have a recipe somewhere that uses cardamom. Next it searches through the recipe database to pick out recipes that have cardamom in it. Cardamom is most often found in soups and cake, but it also can be found in things like fudge, baklava, and kebabs.

In the next step Watson starts to create a template of what it thinks might go in Swedish/Barbadian fudge with cardamom. Here’s where you can go crazy with Watson. The most common elements are automatically selected, but there’s lots of other options. For example, most fudge has a sweetener, chocolate, dairy, oil, and some nuts. Because we wanted cardamom, Watson recommends some spices too. You can go crazy and add in things like meat, alcohol, cheese, and a variety of other things at this step. You can’t just add in anything you want because there are some things that Watson has a hunch will just turn out to be nasty.

In the final step Watson generates a number of recipes that meet the guidelines provided. It tries to ensure that the ingredients selected match up with the various cuisines and also with the dish selected. In addition, using some of the “secret sauce” it makes sure that the ingredients will taste good together too. At the end it presents a number of recipes rated on scales such as “surprise”, or how rare is recipe like this compared to the database, “pairing”, or how well do the flavors pair or contrast with each other, and “pleasantness” which is based on the science of hedonic psychophysics. From there the chef works with Watson to find the best recipe.

That final paragraph sounds so cool. You randomly suggest a bunch of ingredients to a supercomputer and it comes up with interesting recipes based around your rough guidelines, while all the time preventing you from totally screwing up and ensuring that the resultant dish will taste good. (But, this is also reminding me of Arthur in the Hitchhiker’s Guide to the Galaxy and his struggles to get Eddie, the shipboard computer, to make him some tea.