Viswanathan K's Thoughts

As India nears the completion of Week 1 of a nationwide Coronavirus lockdown, in places like Bangalore, one can see folks cite what other countries are doing and suggesting we do the same in our apartment complexes. Are they justified? Or over-reacting? Are the countries being compared, well, comparable? First, let me call out my source for the analysis below. It’s this site that captures Coronavirus stats from all countries . It captures infection counts, recoveries, deaths and active cases on a daily basis and also plots graphs of the same over the last few weeks and months . On some topics, I do see patterns across countries. On others, hardly. And in yet others, patterns seem limited to race (Asians, Europeans etc), or to population size, or to climate. But the key is that one can’t be sure and no pattern is universal… yet I find most people talk as if there is certainty on all such matters. Take China and South Korea : only 4.2% and 2.9% of infected cases have res

Like adults, kids become pattern seekers. It’s a good evolutionary technique to try and understand what’s happening (or going to happen) in the world around us. Sure, it is not fool proof, but it works enough times to be considered useful. This kids’ book titled Why? used that pattern seeking tendency to amusing effect: 1)       Why do zebras have stripes? Camouflage. 2)      Why do leopards, jaguars and cheetahs have spots? Camouflage. 3)      Can animals change their spots? Yes, arctic fox (brown fur in summer to white fur in winter); octopus and squid (they can change to look like rocks or coral). Why? Camouflage. 4)      Why do polar bears have white fur? Camouflage. 5)      Why are flamingos pink? I am guessing you, like my daughter, answered with a weary get-on-with-it “Camouflage” to the last question. Unlike my daughter though, I am also guessing you did not say that they were pink to appear like lotuses to predators. Wrong, said the book triumphantly,

In response to my blog on the three generations of the Internet , my dad had commented: “Are we all stuffing ourselves with data and information, with very little time and inclination left for sharpening our innate, marvelous tool that evolution has led us to - the ability for digging meaning out of abundant data?...Will we have humankind reduced its ability to mind's ability for keen insights, failing to appropriately sharpening our grand mind potential?” Such questions have been asked and debated for years (ironically) on the Internet! Is correlation good enough? For example, Big Data would allow algorithms to tell you where the planet would be without ever discovering Kepler’s laws of planetary motion; but is that the same as knowledge? On the other hand, can laws only be found for the inanimate universe? And is Big Data the (only) way to go when it comes to predicting humans? Is George Box’s statement (“All models are wrong, but some are useful.” ) so true for humans th

“Literature is the opposite of data,” wrote the novelist Stephen Marche. Such a statement made sense even a few decades back, but today? Let’s take a look. Today, Dana Mackenzie’s article says, “the scientific method is tiptoeing into the English department”. Huge amounts of literature have been digitized, and once digitized, surely somebody will start hurling algorithms to find…well, something. In 2011, Google’s N-gram server allowed you to search Google Books for frequency of words or word combinations in the books in its database. There are, of course, obvious limitations to the significance of such raw counts (other than perhaps trending when words caught on or died). Enter topic modeling: “A topic-modeling algorithm infers, for each word in a document, what topic that word refers to.” Does the word “black” mean color? Race? Something bad? The algorithm “produces “bags” of words that belong together”, and leaves it to the human reader to decide the meaning from the c