Milkha Singh sold the script of 'Bhaag Milkha Bhaag' for 0.015$

​

In this fast paced world, there are somethings that just don't surface while other more irrelevant news makes the headline. 'The Flying Sikh', Milkha Singh sold the script of 'Bhaag Milkha Bhaag' for 1 rupee, that is about a fraction of a US dollar, 0.015$ to be mathematically correct. He refused a large offer for his life story to be made into a film. Here's the trailer in case you're wondering what this is about.


He believed that if the film could "inspire our young people and result in India's first Olympic track gold, that would be reward enough for him."

Milkha Singh also known as The Flying Sikh, is a former Indian track and field sprinter who was introduced to the sport while serving in the Indian Army. He was the only Indian athlete to win an individual athletics gold medal at a Commonwealth Games until Krishna Poonia won the discus gold medal at the 2010 Commonwealth Games. He also won gold medals in the 1958 and 1962 Asian Games.

Read my post about some ingenious slogans, punchlines and print ads. Just some amazing marketing. Read it here.

Gaussian Geek

Netflix's 'Stranger Things': The 80s are back

“It's(Stranger Things) really a mix of a few different genres. The basic premise is a boy goes missing in a small town in the early 80s and they are trying to solve the mystery as to what happened to him. What's cool is it blends the genres together in a really interesting way. It's almost like each character is in their own movie. The mother is in a psychological thriller, the sheriff is in a conspiracy theory movie, the boys are in a coming of age movie, the teenagers are in a monster movie, and the young girl is in a sci-fi movie. Then about six episodes in, the genres and story lines begin to merge together for a really dramatic finale. If you like stuff like Stand By Me, ET, The Goonies, The Thing, Firestarter, Carrie, or Poltergeist you'll almost certainly like this.” 
~ a user on reddit

The show brings back the nostalgia of the good old days when kids would bike around and there would be these amazing amateur ham radios to play around with. Set in Hawkins, Indiana the show begins with a mother who is searching for her missing child, Will. But the plot develops into something even more sinister than just what it initially seems to be. The story revolves around the seemingly crazy mother, Joyce doing everything to re-unite with her son, the Chief of Police Jim Hopper finds his own calling. Will’s friends’, Dustin, Mike and Lucas, too are on the quest to find their lost friend in their own eccentric ways, inspired by 80s fantasy and sci-fi. The first season, spanning across eight well-crafted episodes keeps you glued to the screen. Most people have binged on it in one long session.

There are moments when that make you ponder oh they can do this and that but then you realize, oh it’s the 80s. Also, Jonathan and the mother discussing how much is it going to cost to make photocopies of the “missing” posters is one of the 80s details, with technology as such being new. In one of the scenes, the kids’ science teacher is on a ‘Netflix and chill’ date of the 80s if you will, when the kids call him late at night to answer one of their questions. Initially, hesitant, he answers the question when provoked by Dustin that he’s ‘trying to close the curiosity door’ and then goes back to business. You know it’s the 80s when the kids call their teacher to know how a deprivation tank works and is prepared. No Google.

There were many throwbacks to the days of the past. With the 80s electronica and synth background score, among other things, it is a homage to the 1980s genre films. The fashion and apparel of the characters, kids and adolescents having their room walls covered with movie posters. Old fashioned Coca-Cola advertisement clearly produced without the technology we have now. Songs by various musicians (The Clash, Joy Division) especially David Bowie’s Heroes at the end of the episode was pretty dramatic. Chief Hopper sports a fedora that reminds of Indiana Jones and who can forget the ET-like shed at the Byers’ place. The kids playing Dungeons and Dragons. There is a Jaws poster alluding to the speculation that “the thing” can sense blood. The show also links Eleven, played by the charming little lady - Millie Bobbie Brown, to Project MKUltra, a series of experiments on human subjects.

The series is shot in an excellent 80s backdrop and there is agonizing attention to detail in the cinematography. The actors have done a great job, especially the kids and the frustrated, angry and grieving mother played by Winona Ryder. Millie Bobby Brown reminds of a young Natalie Portman from V for Vendetta. Even without many dialogues her expressions and acting was top-notch, able to perfectly convey El’s emotions.  I would recommend Duffer Brothers' 'Stranger Things' and would deem it as a really well produced and directed show with the cast fitting in the roles perfectly. It smells like something older and gives a nostalgic feel in a refreshing new way.

Read my post about how Pixar's Toy Story animated film almost got deleted not once but twice.

Post content and figures featured on Brown University CS145: Probability and Computing course

What better than being referenced by one of the prestigious university's Probability course. My post that talks about The King's sibling and explaining the Bayes' rule was featured on one of the course material slideshows of the CS145: Probability and Computing, Lecture 2 that can be found here (http://cs.brown.edu/courses/cs145/lectures/lec02_conditional.pdf).

Here's the link to the King's Sibling post I had written. Until next time!

Top Amazingly Ingenious Print Ads

I believe that creativity springs from humanity and is one of the ways of expressing thoughts and ideas. Innovation makes things more intuitive so below are some brands with taglines that speak a lot about the brands and their consumers.

Nike: This brand never fails to surprise me. From the way they advertise their products and the advertisements they shoot, it's all done to perfection. The company started by a track athlete and his coach in 1964 controls a huge chunk of the market today. The tagline is really catches the eye of every passer-by.

Apple: Jobs and Wozniak started their company to deliver home brew computing machines. Decades later the company is pushing boundaries in innovation and creativity. With simplicity and a different train of thought as their mantra the tech giant has proven what thinking differently can result in.

Adidas: The mere quality of the brand speaks for itself. The definition of impossible has changed since the advent of the company's tagline. The picture says it all.

MastedCard: The advertisements of this brand and the way they portray how some moments in life are just priceless and can't be actually equated with money, is what I really love.

And finally an Indian brand that deserves a mention is Amul. It's not merely for the taglines but also for the manner in which these posters are made to be visually appealing to everyone from a boy of 6 to an octogenarian. The company keeps updating its billboards and the newspaper sections, keeping us updated with the world in a fun way.

Read my post about Netflix's latest hit series that everyone's going gaga over. Yes, I am talking about Stranger Things. Check my post here and don't forget to share it if you like the read.

The real Wolverine: Tsutomu Yamaguchi, the man who survived not one but two nuclear bombs

​ ​

This man, Tsutomu Yamaguchi, survived both the Hiroshima and Nagasaki bombing atrocities.

Yamaguchi lived in Nagasaki but had gone for a business related trip to Hiroshima. On August 6, 1945 as he was returning home with colleagues when he had forgotten a stamp required for travelling. After collecting it as he was returning the bomber Enola Gay dropped" Little Boy". Yamaguchi was in a 3 kilometer radius of the bombing site. The explosion impaired his hearing ability and temporarily blinded him. He suffered burns which were treated on his return to Nagasaki. Despite of this he still went to work on August 9.

Ironically, as Yamaguchi was describing the bombing to his supervisor at work bomber plane Bockscar dropped the "Fat Man". This time, again, Yamaguchi was within a 3 kilometer radius of the explosion but again survived with minimal damage.

Yamaguchi died at the age of 93 in January, 2010 of stomach cancer.

He was a legend. The way destiny took him from one bomb site to another and still made him a survivor is hard to believe, yet it's true.

Going for hiking and having difficulty packing your rucksack? Optimizaton and Search: The branch and bound algorithm

A branch and bound is an algorithm paradigm. It basically relies on a combinatorial approach and is hence used for combinatorial optimization like the knapsack problem.

Have you ever watered and maintained your garden? Going around removing weeds around trees and removing unwanted branches growing from your plants to keep them in the best possible symmetry, so that your neighbor envies your garden for the perfect shape it's always in. Removing over-ripe fruits so that they don't spoil the other around them. Cutting and pruning at each step so that you don't have to deal with a huge jungle later on.

Well, this is the basic principle for B&B. Below is a more detailed explanation.

It usually of the form of a decision tree where each decision is represented by an edge. The leaves of this tree is the set of all possible solutions. To find the most optimized solution(i.e. one of the leaves) the following is the basis of evaluation.

The intuition is that you start from the root and calculate an upper bound if the problem asks the function to be maximized (or lower bound for function minimization in case of TSP where distance is to be minimized) for a function you want to optimize. This bound describes the best you can get from the sub-tree below the node. It is to be kept in mind that this bound is re-calculated every time a decision is made in the tree. This bound describes the most optimistic solution you can find in one of the leaves of the sub-tree rooted at this particular node.

Make a series of decisions and find the first solution. Now this is your benchmark. Compare this solution obtained with the optimized evaluation of the function at each level (i.e. after every decision). As the root of a sub-tree bounds the best you can achieve from any of the leaves of that sub-tree; if the root of the sub-tree in question has a higher optimized evaluation then you can search that sub-tree in hope for a better solution you already have else discard the whole sub-tree below (called pruning).

If a better solution is found it's updated as the benchmark.

Keep searching the main tree for solutions better than what you have (benchmark) and prune the sub-trees which have a lower optimized evaluation than the benchmark.

Pruning reduces the search space by an amount depending on where the pruning of the tree occurs. Generally, it helps in reducing it by a large factor.

The above is an instance of the knapsack (max weight is 16) using Branch and Bound. The weight and the value of the item is enlisted on the left.

Each node has current value, space occupied and optimistic evaluation of the value of its sub-tree. 

1. The root shows that currently no items have been selected and the best one can do is 115$.(or less)

2. A decision is made to accept the Item 1.

3. If Item 1 is accepted then we go to left of root else right of root.

4. Going left the value of the knapsack is increased and the weight is also updated. An optimistic evaluation is calculated for the results under this node.(i.e. all possible ways of selecting remaining items after selecting Item 1)

5. Going right the value of the knapsack and the weight is unchanged (since nothing was chosen). An optimistic evaluation is calculated for the results under this node.(i.e. results with all possible ways of selecting remaining items after discarding Item 1)

6. If a node has optimistic evaluation less than the best we have found then the sub-tree is discarded. If a node occurs such that the weight surpasses the max allowed weight by the knapsack then again the sub-tree under the node is discarded.

The first solution is found and set as the benchmark and the above steps are repeated until the whole search space has been exhausted.

This is the basic idea of Branch and Bound.

Optimization and Graphs: The travelling salesman problem

The Travelling salesman problem was introduced by William Hamilton. The problem states that you require a Hamiltonian path (a path with no vertices repeated) in a graph so as to minimize the cost/distance function. It is a NP hard problem.

TSP on the major cities in Germany

You may want to keep in mind that using brute force for such problems may take infinite time to run to completion since there are at least N! possibilities for traversing the graph with N nodes (the cities). So you can use some searching informed techniques.

An approach that could prove helpful is start from a node, keep traversing the next closest/cheapest node until you have traversed all the nodes. Then use stimulated annealing with different temperature changing functions (linear, exponential and so on) to get an improved version of your initial feasible solution. This method first finds a feasible solution (in accordance with the problem statement) and then constantly improving the solution and finding an approximated solution in case of very large number of nodes.

You could also attack the problem by constructing solutions which are minimized during the construction itself, but that may prevent you from getting a feasible solution if the conditions aren't checked.

Also you can use techniques such as k-opt or a pairwise swap of edges in the graph genetic algorithms, simulated annealing, Tabu search or ant colony optimization. Hybrid techniques that use more than one of the above techniques usually proves to be more efficient and accurate.