Things I like- Articles

  • El Capitan, my El Cpaitan
  • A math teachers life summed up by the gifted students he mentored
  • The mundanity of excellence : An ethnographic report on stratification and olympic swimmers
  • The Ivy league, Mental illness, and the meaning of life
  • A new way of voting that makes zealotry expensive
  • Not all developing nations are created equal
  • No miracle people
  • Affording ascendancy
  • 2013: Doing something with my life
  • You don’t need to be brilliant to do brilliant work
  • Value of information
  • How to make life
  • The Secret Oral History of Bennington: The 1980s’ Most Decadent College
  • The long game of research
  • Yukio Mishima on the beautiful death of James Dean
  • The radical plan to change how Harvard teaches economics
  • Violence and the Sacred: College as an incubator of Girardian terror

Keeping tab of things

The abundance of commodities has given us choices-a dizzying number of choices- when it comes to any commodities. That includes soaps, food, written articles, podcasts, books etc. I happen to spend a lot of time reading things online and sometime offline. I think it will be worthwhile to keep track of what I consume. It will give me a perspective on how I am spending my time, what I am listening to and watching etc. Previously, I thought I will keep track of every article, movies and papers I come across and add them with a rating on this page. Now that I think about it, that doesn’t seem too useful. I do not need to know what I really thought was mediocre. It is probably useful to know if I am reading too many mediocre articles. But the realization that something may be mediocre may not be always revealed prior to consumption-except when it is highly reviewed by reliable consumers, those with ‘good taste’ . So instead of tracking everything I am gonna only list those things I really liked here. May be I will keep list of all research articles I read- primarily for professional reasons.

Summary of September 2019

Articles

  1. How to make life (4.5/5)
  2. Analysis: A moment of reckoning for Indian Americans (3/5)
  3. Emory university professor canned after her ‘extremist’ blog is revealed (1/5)
  4. Hippos poop so much that sometimes all the fish die (3/5)
  5. First hint that body’s biological age can be reversed (4/5)
  6. The Secret Oral History of Bennington: The 1980s’ Most Decadent College (4/5)
  7. It Will Happen Again and Again (1/5)
  8. A Famous Argument Against Free Will Has Been Debunked (4/5)
  9. Failed GM mosquito control experiment may have strengthened wild bugs (3/5)
  10. The long game of research (4/5)
  11. Stop Blaming America’s Poor for Their Poverty (3.5/5)
  12. Was Richard Feynman a great teacher? (2.5/5)
  13. Make Iceland great again! The return of Trapped, 2019’s most timely show (2.5/5)
  14. Small Trial Reverses a Year of Alzheimer’s Cognitive Decline in Just Two Months (3/5)
  15. How the White Nationalists Who Love Trump Found Inspiration in the Group That Gave Us Narendra Modi (2/5)
  16. Scientific breakthrough may eventually allow many blind people to see (3.5/5)
  17. The Problem With Sugar-Daddy Science (3/5)
  18. Great Ideas Are Growing Scarce. That’s Not So Great. (3.5/5)
  19. Undaunted by cancer, she wrote 11 international papers before passing away (3/5)

Academic Papers

  1. First hint that body’s biological age can be reversed

Movies

TV

  1. Trapped (season 2): (4/5)

What is significant?

For a while, I have been wondering what are some of the most significant inventions of humanity? The primary criterion for evaluation must be the impact. I plan to update this list whenever I come across an invention or discover that I missed.

  • Electricity
  • Vaccination
  • Printing press
  • Haber process
  • Internet
  • Flight
  • Antibiotics
  • Satellites
  • Seafaring
  • IC engines
  • Surgery
  • Computers
  • Clock
  • Steel
  • Concrete
  • Birth Control
  • High yield rice
  • Polymerase chain reaction

Summary of August 2019

Articles

  1. Tonsillectomy appears to protect against tonsil cancer (4/5)
  2. Most tonsillectomies performed on children no benefit on health (3/5)
  3. Tonsil, adenoid removal may increase risk of respiratory infections (3/5)
  4. HPV16 antibodies strongly increase throat cancer risk, can develop decades before diagnosis (3/5)
  5. Cancer scans reduce risky operations (4/5)
  6. Florida girl’s death brings to light tonsillectomy risks (3/5)
  7. India’s culture of toxic masculinity (2.5/5)
  8. Dating while dying (3.5/5)
  9. China’s spies are on the offensive (2/5)
  10. America the beautiful(3/5)
  11. Biohackers are pirating a cheap version of a million dollar gene therapy

Hash Tables

I do not exactly remember when I had first heard about hash tables. It must have been around the time I graduated from college. Someone was talking about a CS interview question on Quora about how to implement a hash table. I quickly inferred that this was one of those weird data structures that you are expected to learn in CS. Needless to say, I never felt compelled to read more into it.

Recently, I realized that I have become old enough to learn at least one skill that will make me employable. Programming and data science were the two most obvious options. Given that I have some idea about probabilities, I picked a career in data science. However, due to circumstances, I realize that learning to program will turn out to be quite useful for me in the future. My relatively short stint as a data scientist had given me some experience in Python programming. However, my codes were never optimized for speed or memory usage. In fact, when I code I am often thinking that “Well, I’m sure there is a more elegant way to do this. If only I could come back and clean this mess up”. Except, that never happens.

As I was looking through the jobs section on LinkedIn, I found that the vast majority of programming jobs I am interested in require significant experience in C++. This was backed up by some folks I consider reliable on the matter. Normally in a scenario like this, I would go out and purchase a book or two on C++. Quickly then I would proceed to open the first one and read deeply about the biography of the author and his friends and his sociopolitical views. I may even read more about the history of C++ programming. Luckily, I didn’t do that this time. Instead I assembled some C++ programming courses online. Impressively, before watching even a single lecture either on C++ or on Algorithms and Data Structures, I started to try my coding skills on Leetcode.

The first programming problem I came across concerned with array processing. Given an array A containing a sequence of numbers and a constant k, find the indices of the elements in A that will sum up to k. For example if A=[1,2,4,6,3] and k=9 then the program should return [3,4] since A[3]+A[4]=9. It is also given that only one such pair exists in the array. I quickly wrote a function in Python. It looked something like below.

def twosum(A,K):
for i in range(len(A)-1):
for j in range(i+1,len(A)):
if A[i]+A[j]==k:
return(i,j)

This worked and it gave the correct solution. But it was slow. In the worst case scenario, it will have to search through and perform n*(n-1)/2 addition operations when the array A has length n. For this reason, the above approach is said to have a time complexity of O(n^2). An alternate solution I came across looked like this

def twosum(A,K):
dict={}
for i in range(len(A)):
ncomp=k-A[i]
if ncomp in dict:
return(dict[ncomp],i)
else:
dict[A[i]]=i

When I saw this, I couldn’t understand why this code may be more efficient than what I wrote. It surely has to search through the entire dictionary (dict) to perform the ‘if’ operation? That must get more and more expensive as the size of dict grows? Except, it doesn’t. Behind the scenes, the dictionary type in Python is implemented as a hash table. The cost of searching through a hash table does not increase with size. In fact it is of O(1). How does this work?

In a typical array of strings e.g.: A=[‘cats’,’mice’,’dogs’,’rabbits’]. The index of the word ‘mice’ is 1. It became 1 only because we entered the word ‘mice’ as the second element of the array A. There is no relationship between ‘mice’ and its index. Imagine a scenario where you have a data structure A*. Except this time the index of each entry exhibits a functional relationship with the entry itself. Lets call this function hash. That is A*[hash(‘mice’)]=’mice’. Now, if we were to search for ‘mice’ in this array, we can use the hash function to quickly convert it into the index and see if that location is empty. Which means that searching for mice in A* doesn’t depends on the size of A*. This is the principle behind hashing. Its the functional relationship between an element and its index + the ease of moving to a given index regardless of the size of an array (presumably due to indices being always appearing in sorted order) that makes hash tables powerful.

Surely, next time I write a code that involves look up tables or array processing, I will think about using a hash table. I have a few references that I read up on the internet below.

[1] https://www.hackerearth.com/practice/data-structures/hash-tables/basics-of-hash-tables/tutorial/
[2] PyCon 2010: The mighty dictionary – https://www.youtube.com/watch?v=C4Kc8xzcA68
[3] https://mail.python.org/pipermail/python-list/2000-March/048085.html


Summary of June 2019

QnD Reading

  1. The changing structure of American innovation: Some cautionary remarks for economic growth: Arora, Belenzon, Patacconi, Suh. The focus of R&D in the US has moved away from the outcome oriented industrial research labs to curiosity driven university research forming a new pipeline where industries focus mostly on product development and less on basic research. This correlates well with a slow down in productivity growth despite a net increase in R&D expenditure.

Articles

  1. The radical plan to change how Harvard teaches economics (5/5)
  2. What Alan Krueger taught the world about the minimum wage, education, and inequality-(4/5)
  3. Stephen Marglin– The only radical economist at Harvard
  4. Mexico is not a poor country-(2/5)
  5. Japan begins experiment of opening to immigration (3/5)
  6. Yukio Mishima on the beautiful death of James Dean (4/5)

TV

  1. Dark :Season 2 (3/5) – More time travel, less compelling plot.

Easy distinction

I quickly came to understand that there are two types of people in this world: There are the type of people who are going to live up to what they said they were going to do yesterday, and then there are people who are full of shit. And that’s all you really need to know

Anthony Bourdain