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.

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

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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.

Mind-blowing optical Illusions explained: What is anamorphism?

Given that you've made it this far, first have a look at what this article is all about.

Anamorphosis is a way of projecting an image in a distorted manner so as to convey the actual image by making the viewer take a specific vantage point or in some cases with special optical devices (like a mirror).

The word "anamorphosis" is derived from the Greek prefix ana-, meaning back or again, and the word morphe, meaning shape or form.

There are two main types of anamorphosis:

1.Perspective (oblique)

2.Mirror (catoptric)

Perspectival anamorphosis date to the early Renaissance and are now a major part of various industries, especially advertisement. Mirror anamorphosis were first created in the later. A mirror is placed in proximity of the painting or illustration and if viewed from specific angles it transforms the distortion into an image.

This occurs mainly due to the difference in perspective we get from viewing it from a vantage point compared to a normal place.

The main calculations are done by adjusting the perspective of the image in various software. Various techniques of projection are used to estimate the position and the size of the actual graphic ( illustration). The the angle and the distance from the viewing point are some of the things taken into consideration.

The system of anamorphic projection can be seen quite commonly on text written at a very flat angle on roadways, such as "Bus Lane" or "Children Crossing", which is easily read by drivers who otherwise would have difficulty reading as the vehicle approaches the text; when the vehicle is nearly above the text, its true abnormally elongated shape can be seen.

Also a lot of sports have their fields painted or a printed mat is used instead. It is used to promote brands and when viewed from a specific angle i.e. usually the point-of-view of the camera the image is seen in its undistorted form.

Much writing on shop windows is in origin anamorphic, as it was written mirror-reversed on the inside of the window glass. Ambulances with AMBULANCE written as a mirror image is one of the most common forms of anamorphism.

An anamorphic fresco by Andrea Pozzo at the Church of St.Ignazio.

We like to think of viewing as perception or reality. Our eyes provide continuous raw input to the brain. Since we are accustomed to viewing objects as normal entities and quickly search for familiar patterns like rectangles, squares, circles and try to make something out of what we see. These distortions force our brain to interpret the way we see the actual world and hence the illusion.

We possess something called the "binocular vision" and it's unlike a camera. We fundamentally receive information from a pair of eyes and this creates a alternated view of reality which helps in analysing depth and distance and also anamorphic illusions. The "Ames Room" illusion brilliantly exposes the kind of expectations that we automatically apply to what we see.

Algorithms and Computer Science

Why is computer science a science?

What is the difference between say Physics or Biology and Computer Science? Is there a difference at all?

Well for starters science constitutes of experimentation which makes if fundamentally difference from other subjects that may seem similar at first glance. The field of computer science is a machine science. It deals with a particular type of machine that we colloquially refer to as a PC or a personal computer. So why don't we have something like a tube-light science or a pressure cooker science?

That is something debatable but computers unlike a tube-light or a pressure cooker doesn't inherently have a singular purpose such as glowing or boiling your favourite veggies. If you can encode your thoughts in a precise and particular manner, the personal computer can function based on that. These may vary from solving problems that occur while studying particle physics and trying to make sense of the humongous amount of variegated data or as inconsequential as calculating the amount you spent on groceries at the market.

Alan Turing, the father of theoretical computer science wrote a scientific paper in which he described "computers" as people (mostly women at that time, primarily due to their patience while performing arduous calculations) who did math on pen and paper according to the whims of a set of sequential instructions also known as an algorithm.

Let's go back to the pressure cooker. 

Could there be a microwave oven science, since we already have one that caters to a pressure cooker? What cooks faster in a pressure cooker: a chicken or some potatoes? Potatoes or rice? Rice or wood? Wood or Iron? That escalated quickly.

On closer observation, there seems to be some sort of classification. Things that cook slow, other food items that cook quicker and some others, even quicker. And then there's this class of items that are so stubborn that they won't boil in a pressure cooker, like a piece of metal. Every science begins with classification and so does the one that deals with theoretical computer science.

Absurd as it may sound, in this context, we are dealing with the contents or what we can actually come up with, rather than the tool itself. We are worried about the chicken or the rice or perhaps the potatoes in the cooker rather than the humble pressure cooker itself. Similarly theoretical computer science at it's heart doesn't believe in discriminating based on the tool we use, whether it's a microwave oven or an old school pressure cooker, all we are worried about is getting nice boiled potatoes in the end. It doesn't really matter whether you have a super computer of this generation or a quantum technology powered device of the next era. This is what is computational complexity.

Things cooking at various speeds can be compared analogously to the various complexity classes in computer science, that instead of rating food items classify algorithms on their efficiency for easy comparison and deciding what maybe difficult for a computer to solve.

Difficulty is relative. Someone may find talking to a girl really difficult while another one may deem waking up early in the morning a difficult task. Many may also find it laborious to prove the Pigeon-hole principle. Computer science calls problems difficult that require at least exponential number of steps in the size of an input to an algorithm. But a database scientist may treat anything worse than a logN or a linear algorithm as inefficient. Depending on the context the definition of hardness may vary. The algorithms are compared in terms of the number of instructions required, space occupied (as a scratchpad), etc. These metrics are technology independent and that's where the universality lies. You'd compare them in the next century as you would in this. Doesn't matter what kind of specification the system has. The tool is just a means, it's the method that we bother about.

While mathematics has this puzzle kind of perspective to it. If you have solved a jigsaw puzzle or say a Rubik's cube, which you most certainly have, for the first time it may seem more of a challenge. But once you know how a jigsaw puzzle works and understand the concept behind it, you can solve any puzzle with the same technique. If you know how to computer 33+12, you can surely compute 132144+39427438 with little difficulty. Once a mathematical problem is solved, it is like you've become aware of the great magician's secret. Any local fair you visit and you see a person performing the trick you'll be aware of how it's done, irrespective of whether it's happening.

A solution for the travelling salesman problem for the cities in Germany.

On the other hand, computer science deals with skewing the problem. Let's say that now you take a 4x4 Rubik's cube to solve. What happens to your step-wise procedure? Does it work as expected or fails miserably? What happens to the number of steps when you consider a cube of an arbitrary size NxN? How much space does the computer need as a scratch pad to find a conclusive solution? Here, as soon as you fish out an algorithm it is then that you have even more questions to answer than you had to begin with in the first place.

P.S.: I attended a talk on algorithms and this is what it was all about. Really simple stuff but made a lot of sense. I thought I'd share it with my readers. :)

Of Predictions and Prophecies: Visions that will boggle your mind

Mark Twain known for 'The Adventures of Tom Sawyer' and 'The Great American Novel'.

This world has seen oracles come and go. With the likes of Nostradamus who would peek into the future using his water-filled tripod under the moonlight, George Orwell talks about "telescreens [that] received and transmitted simultaneously" and CCTVs in his dystopian sci-fi novel 1984. Mark Twain is known for his writings but he had predicted his own death on the arrival of Halley’s Comet and unfortunately had envisioned the death of his brother. When he arrived at the place his brother lay between two chairs and even the wreath was arranged as he had dreamt.

A Serbian born American scientist, futurist, engineer and inventor, after whom an electric car-company is named is another of the oracles the world heard from. Nikola Tesla worked as an apprentice to Thomas Edison credited for the light bulb, one of many inventions he’s known for.

Nikola Tesla claimed to sleep at most two hours and supposedly possessed an eidetic memory.

Tesla went on to pursue his ideas of wireless lighting and electricity distribution in his dangerous experiments, and made predictions on the possibility of wireless communication. He had registered about 300 patents under his name and the inventions he made still influences modern day life.

Many of his ideas were way ahead of time and technology at that time. It was difficult for the folks to digest his ideas and often invited ridicule from the scientists. Many consider Edison had stolen Tesla’s ideas.

Wireless communication and the internet

"When wireless is perfectly applied the whole earth will be converted into a huge brain, which in fact it is, all things being particles of a real and rhythmic whole. We shall be able to communicate with one another instantly, irrespective of distance. Not only this, but through television and telephony we shall see and hear one another as perfectly as though we were face to face, despite intervening distances of thousands of miles; and the instruments through which we shall be able to do his will be amazingly simple compared with our present telephone. A man will be able to carry one in his vest pocket."

"We shall be able to witness the inauguration of a president, the playing of a World's Series baseball game, the havoc of an earthquake, or a battle just as though we were present."

"It will soon be possible to transmit wireless messages all over the world so simply that any individual can own and operate his own apparatus."

"…the household's daily newspaper will be printed wirelessly in the home during the night."

When Tesla was working on the trans-Atlantic radio, he proposed to his funder, J.P. Morgan. The idea was to create a plan for a "World Telegraphy System”. He planned to provide instant communications between individuals. Such predictions and ideas would prove to be true decades later.

Dream on

Another scientist by the name of Dmitri Mendeleev had predicted something. But this time it wasn’t about smart phones or CCTVs. Mendeleev had designed a periodic table using his scientific prowess so perfectly that even till date his version of the Periodic Table is used with a few minor changes. Mendeleev predicted future elements and where why would be placed with the properties they exhibited.

Dmitri Mendeleev, chemist and inventor.

At that time, in 1863, only 56 elements were discovered but by the ingenious way of arranging elements based on atomic weight that he had apparently seen in his dream helped him predict positions of elements that would be discovered. [Mendeleev's table and the modern periodic table].

"I saw in a dream a table where all elements fell into place as required. Awakening, I immediately wrote it down on a piece of paper, only in one place did a correction later seem necessary."

—Mendeleev, as quoted by Inostrantzev

Inventing the electricity that we use in our homes, pioneering research about the X-rays and the neon lights in your favorite pub, are a small fraction of the contributions these men made. With such remarkable visions and spot-on predictions, these men contributed to the science and technology, paving way for the luxuries we enjoy today. 

Did you know that Toy Story 2 was almost deleted? Read the whole story here.

The King's Sibling: How well do you understand probability?

The king comes from a family of 2 children. Assuming that there is an equal probability of a child being a boy or a girl. What is the probability that the other child is his sister? 

Hey folks, figures in this article have been featured on Brown University's slide show on Conditional Probability CS145: Probability and Computing (link to lecture 2)

Well this may seem a very simple question on the surface but it manages to capture a very important concept in probability, the famed Bayes' Theorem. In fact, it is a variant of a very controversial question dating back to 1959.

Before we see how this is related to one of the most celebrated theorems in probability and mathematics, what would be you guess?

If you guessed that there was a 2/3 chance that the other child would be a girl then you are right and I assume you understand Bayes' theorem. But if you thought that 1/2 was the correct answer I'm afraid that you might want to look at the drawing board again.

You may have concluded quickly that since the chance of a boy or a girl are equally likely knowing that there is a king in the family doesn't really affect the gender of the other child. How can the gender of one sibling affect that of the other? Or can it?

This is the curious case of conditional probability. "The king comes from a family of 2 children", this statement holds the key. Again, it seems unlikely that this could hold extra information, but actually, it does. The statement gives us two very important pieces of information as you might have guessed already:

1.     There are two children in the royal family.

2.     There is a king i.e. there is at least one boy in the family.

The pieces seem very obvious but there's nothing extraordinary about them. But if we combine the two pieces something emerges that makes us want to change our belief about the probability of the other sibling being a girl.

Since, here we have a small sample space let's try to enumerate them. Let's assume that we don't have any information as of now. We just know that the royal family has two children. Let's first try to visualize the distribution of the possibilities.

Fig. Sample space S = {BB, BG, GB, GG} without any extra information

For convenience let's denote a Boy with a B and a girl with a G. Our sample space, 

S = {BB, BG, GB, GG}

and the chance of any of these four cases of two boys, a boy and a girl, a girl and a boy and two girls is equally likely with probability 1/4.

But when we know that one of the siblings is a boy the sample space changes. We no more have the possibility of having 2 girls in the royal family and we are just left with 3 possibilities in the sample space,

S' = {BB, BG, GB}

Fig. Sample space S' = {BB, BG, GB} given that at least one of the children in a boy

Now we want to know what is the chance of the other sibling being a sister given that we have a king (boy) in the family and this is where the Bayes' theorem comes into play.

The Bayes’ theorem describes the probability of an event occurring given some conditions. This is what the Bayes’ theorem looks like in notation,

 P(A|B)=P(AB)P(B)

P(A|B) denotes the probability of event A occurring given event B has occurred. While P(AB) denotes the probability of both event A and B occurring together.

Here, event A is the other sibling being a girl and event B is that at least one of the children is a boy.

Then,

P(other sibling being a girl|there is a boy in the family of 2 children)

=P(other child being a girl and there is at least one boy in the family of 2 children)/P(there is at least one boy in the family of 2 children)

=(2/4)/(3/4)

=2/3

Looking at it from the perspective of cardinality of the new sample space S' = {BB, BG, GB} that captures the 2 pieces of information that one of the children is a boy. Now, we want to find the probability of the other child being a girl we have 2 possibilities ({BG, GB}) out of the 3 ({BB, BG, GB}) and gives the same result as we got before. Note that this answer is only valid in countries with male-preference primogeniture. In countries such as Sweden with absolute primogeniture, the king can't have an older sister: that is, (g,b) is not a possible outcome, so then the probability is 1/2.

So the next time someone asks you a seemingly straightforward question, there is a chance that Bayes' theorem may help you understand conditioning and come up with the correct solution. Such questions go on to show that there might be more information out there, than we expect. Hopefully, it may help you win Let's Make a Deal, solve some Artificial intelligence problems, make a fortune by predicting the stock market or at least make understanding conditional probability relatively easy.

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