On the 30 Year Anniversary of the Chernobyl Disaster

Today marks the 30th anniversary since the Chernobyl nuclear power plant explosion on April 26, 1986 in Ukraine.

Over the last couple of weeks, I’ve watched a few documentaries that do an excellent job summarizing how the disaster unfolded, the impact the disaster has had on the population of Ukraine and Belarus (as well as other world regions impacted by the nuclear fallout), and the still-ongoing efforts to contain the spread of the radioactivity.

The three documentaries I recommend are below. First, The Battle of Chernobyl (incorrectly titled as “Chernobyl Uncensored” in one YouTube video) is a 2006 documentary (approximately one and a half hours in length) that stars Mikhail Gorbachev, former president of the U.S.S.R., providing excellent commentary throughout:

Second, the documentary Zero Hour creates a minute-by-minute breakdown of the accident at Reactor #4 at Chernobyl (from about an hour before the accident to approximately 48 hours after the accident):

 

Finally, the documentary Chernobyl 3828 is perhaps the most poignant of the documentaries, profiling the 3828 human workers (who came to be known as liquidators or “bio-robots”) that were sent into the most radioactive zone—the roof of the reactor #4—in September 1986 to finish cleaning up the radioactive waste before the sarcophagus over the reactor could be built. There was such high levels of radioactivity in this area that robots sent from Western Europe had their electronics fried in less than 48 hours. The clean-up effort, nevertheless, had to go on—and these bio-robots would sacrifice themselves for the greater cause. These workers received the most lethal doses of the radiation (background radiation of ~8,000 Roentgens), and what is agonizing to watch is the struggle the commander of the operation has to face, knowing that he is ultimately sending these men to their early deaths. The narrator of the documentary, Valeriy Starodumov, worked as a dosimeter scout at the Chernobyl clean-up site; in the documentary, he trains and takes the soldiers to the zone of the highest contamination. And so, a conveyor of bio-robots begins, and Starodumov narrates:

I will take a few hundred people through the zone. I will not know who they are, I will not see their faces behind protective masks and I will never know what is going to happen to them afterwards. It was not me who had made a decision to send these men to the zones of mortal danger, but each night some inexplicable feeling of guilt brings me back to the past. To that first two-minute shift, which has been continues for me for a quarter of century…

 

 

The NFL Schedule is a Massive Optimization Problem

This is a fascinating Los Angeles Times piece that profiles the computing power that is required to generate the NFL schedule. A team of four members and hundreds of computers are used to sift through 26,000+ conditions, with trillions of possible permutations, to generate the 2016 NFL schedule:

With 256 games, 17 weeks, six time slots, five networks and four possible game days — Sunday, Monday, Thursday and Saturday — there are hundreds of trillions of potential schedule combinations. Katz and his team are searching for the single best, and they have as many as 255 computers around the world running 24/7 to find the closest possible match to the ideal slate of games.

The schedules that have come out in the last couple of years are much more sophisticated:

Among the scheduling elements that are factored in now, but were not deeply considered in the old days: How much is a team traveling, and how far? Is someone playing a road game against a team coming off its bye week? Is anyone playing a road game six days after being on the road on a Monday night? Is a club overloaded with consecutive opponents who made the playoffs the previous season? Has a team gone multiple seasons with its bye at Week 5 or earlier?

An incredible optimization problem. The ultimate schedule that was selected was hand-judged against 333 other schedules generated by the computers to make sure it was the most optimal schedule.

Read the rest here. Here is the 2016 NFL schedule.

On the Minecraft Phenomenon

Clive Thompson, writing in The New York Times, profiles the gaming phenomenon that is Minecraft. It’s a really interesting read on the appeal of the game for both children and adults:

Minecraft is thus an almost perfect game for our current educational moment, in which policy makers are eager to increase kids’ interest in the “STEM” disciplines — science, technology, engineering and math. Schools and governments have spent millions on “let’s get kids coding” initiatives, yet it may well be that Minecraft’s impact will be greater. This is particularly striking given that the game was not designed with any educational purpose in mind.

 On how the game teaches kids autonomy, negotiation, and empathy:

But Minecraft is unusual because Microsoft doesn’t control all the servers where players gather online. There is no single Minecraft server that everyone around the world logs onto. Sometimes kids log onto a for-­profit server to play mini­games; sometimes they rent a server for themselves and their friends. (Microsoft and Mojang run one such rental service.) Or sometimes they do it free at home: If you and I are in the same room and we both have tablets running Minecraft, I can invite you into my Minecraft world through Wi-Fi.

What this means is that kids are constantly negotiating what are, at heart, questions of governance. Will their world be a free-for-all, in which everyone can create and destroy everything? What happens if someone breaks the rules? Should they, like London, employ plug-ins to prevent damage, in effect using software to enforce property rights? There are now hundreds of such governance plug-ins.

Worth clicking through to see the illustrations done by Christoph Niemann.

The Difference between Affluent, Rich, and Super-Rich

One of the best things I’ve read this week is Ben Casnocha’s blog post titled “The Goldilocks Theory of Being Rich” on what it means to be rich. In the post, Ben correctly posits that today there’s a very small difference between the rich and the American middle class in terms of quality of life. In the post, Ben differentiates among affluent, rich, and the super-rich…

The actual best part about being super rich, as far as I can tell, is this: You’re more likely to feel like you led a life of meaning. You might not be happy all the time or most of the time, but you will feel like your time on this earth counted for something. One way to distinguish happiness from meaning is that happiness is the day to day bounce of emotions while meaning is what you feel when you step back, take a minute, and reflect on what will go in your obituary. (Here’s my post on meaning vs. happiness.)

How so? The feeling of meaning and making a difference manifests in real, concrete ways. Someone like Meg Whitman can walk the HP campus and see thousands of employees who support their families thanks to employment at HP; she can read stories about the millions of people who use HP products every day to be better at their job. That imbues her life with a sense that her life matters. If you don’t have a corporate campus to walk around—if, for example, you’re an options trader and not a builder of things—fear not. With a supple bank account, you can still take actions that generate meaning. Write big checks to charity and you’ll get thank you notes from the children at the public school you helped. You’ll get enough feel-good ooze from your charitable giving to last you a lifetime. Entrepreneur and billionaire Marc Benioff has said, “Nothing is going to make you feel better. Philanthropy is absolutely the best drug I’ve ever taken.”

I liked this analogy posited by Tim O’Reilly:

…money is like gasoline while driving. You never want to run out, but the point of life is not to go on a tour of gas stations.

The distinction between affluent, rich, and super-rich:

Maybe wealth needs its own Goldilocks porridge story: you want not too much, not too little. And I think that ideal middle ground is the “Rich” category in the hierarchy I opened with. More crudely, this ideal amount of money is termed “fuck-you money.” With fuck you money, you can’t fly around the world on a private jet (so you’re not as rich as the Super Rich) but do you have the power to say fuck you to essentially anyone or anything that doesn’t interest you (which means you’re richer than the merely affluent).

Put another way, if you work on stuff that doesn’t excite you for more than one day a week, in my estimation you do not have fuck-you money. You’re still working for the man. At the other end of the spectrum, if you find yourself being invited to more than a few charity galas a year, worrying about physical and cyber security at your home, and asking a PR person to review your public statements, you have a lot more than fuck-you money and all the corresponding drawbacks.

Definitely worth reading this thought-provoking post in its entirety.

Pablo Picasso’s Multi-Billion Dollar Empire

I enjoyed this piece in Vanity Fair on Pablo Picasso’s multi-billion dollar empire.

Picasso did not leave a will. The division of his holdings took six years, with often bitter negotiations among the heirs. (There were seven then.) The settlement cost $30 million and produced what has been described as a saga worthy of Balzac. The family, writer Deborah Trustman noted at the time, “resembles one of Picasso’s Cubist constructions—wives, mistresses, legitimate and illegitimate children (his youngest born 28 years after his oldest), and grandchildren—all strung on an axis like the backbone of a figure with unmatched parts.”

It is unbelievable how prolific Picasso was:

When Picasso died, 43 years ago at the age of 91, he left an astounding number of works—more than 45,000 in all. (“We’d have to rent the Empire State Building to house all the works,” Claude Picasso said when the inventory was completed.) There were 1,885 paintings, 1,228 sculptures, 7,089 drawings, 30,000 prints, 150 sketchbooks, and 3,222 ceramic works.

Much more here.

The Elements of Effective Teamwork: A Google Experiment

This is a fascinating piece by Charles Duhigg (author of the excellent The Power of Habit) which outlines the steps Google took to understand what made some teams at the company effective, while other teams–though composed of very intelligent members–tended to underperform. The code name for the internal project at Google was Project Aristotle:

Five years ago, Google — one of the most public proselytizers of how studying workers can transform productivity — became focused on building the perfect team. In the last decade, the tech giant has spent untold millions of dollars measuring nearly every aspect of its employees’ lives. Google’s People Operations department has scrutinized everything from how frequently particular people eat together (the most productive employees tend to build larger networks by rotating dining companions) to which traits the best managers share (unsurprisingly, good communication and avoiding micromanaging is critical; more shocking, this was news to many Google managers).

Project Aristotle’s researchers began by reviewing a half-century of academic studies looking at how teams worked. Were the best teams made up of people with similar interests? Or did it matter more whether everyone was motivated by the same kinds of rewards? Based on those studies, the researchers scrutinized the composition of groups inside Google: How often did teammates socialize outside the office? Did they have the same hobbies? Were their educational backgrounds similar? Was it better for all teammates to be outgoing or for all of them to be shy? They drew diagrams showing which teams had overlapping memberships and which groups had exceeded their departments’ goals. They studied how long teams stuck together and if gender balance seemed to have an impact on a team’s success.

It’s worth reading the piece in its entirety, but it comes down to the fact that teams where individuals have a chance to speak their minds, engage in mild chit-chat, and share their personal stories and vulnerabilities end up as more cohesive, stronger performing teams compared to the ones that simply get down to business and attempt to get work done.

From the concluding portion of the piece:

Project Aristotle is a reminder that when companies try to optimize everything, it’s sometimes easy to forget that success is often built on experiences — like emotional interactions and complicated conversations and discussions of who we want to be and how our teammates make us feel — that can’t really be optimized.

And this:

What Project Aristotle has taught people within Google is that no one wants to put on a ‘‘work face’’ when they get to the office. No one wants to leave part of their personality and inner life at home. But to be fully present at work, to feel ‘‘psychologically safe,’’ we must know that we can be free enough, sometimes, to share the things that scare us without fear of recriminations. We must be able to talk about what is messy or sad, to have hard conversations with colleagues who are driving us crazy. We can’t be focused just on efficiency. Rather, when we start the morning by collaborating with a team of engineers and then send emails to our marketing colleagues and then jump on a conference call, we want to know that those people really hear us. We want to know that work is more than just labor.

From my own personal experience, I can relate to the findings. I’ve tended to perform better in work groups where the managers or my colleagues tended to take an interest in my personal life, either by asking questions or offering advice.

Physicists Detect Gravitational Waves

Today’s major story in the scientific world is an announcement from Laser Interferometer Gravitational Wave Observatory (LIGO) on the detection of gravitational waves, long hypothesized by Albert Einstein. The New York Times has the most comprehensive coverage that I’ve seen:

The discovery is a great triumph for three physicists — Kip Thorne of the California Institute of Technology, Rainer Weiss of the Massachusetts Institute of Technology and Ronald Drever, formerly of Caltech and now retired in Scotland — who bet their careers on the dream of measuring the most ineffable of Einstein’s notions.

Dr. Thorne of Caltech and Dr. Weiss of M.I.T. first met in 1975, Dr. Weiss said, when they had to share a hotel room during a meeting in Washington. Dr. Thorne was already a renowned black-hole theorist, but he was looking for new experimental territory to conquer. They stayed up all night talking about how to test general relativity and debating how best to search for gravitational waves.

Dr. Thorne then recruited Dr. Drever, a gifted experimentalist from the University of Glasgow, to start a gravitational wave program at Caltech. Dr. Drever wanted to use light — laser beams bouncing between precisely positioned mirrors — to detect the squeeze and stretch of a passing wave.

The two LIGO observatories (one in Washington State and the other in Louisiana) showed a similar response to the gravitational waves from two colliding black holes, as seen in the below graphic:

LIGO_gravitational_waves

The sensitivity to detect these gravitational waves is extraordinary:

Lost in the transformation was three solar masses’ worth of energy, vaporized into gravitational waves in an unseen and barely felt apocalypse. As visible light, that energy would be equivalent to a billion trillion suns.

And yet it moved the LIGO mirrors only four one-thousandths of the diameter of a proton.

The actual abstract LIGO is below. The full paper is here (with author citations at the end of the paper that number ~1,000 scientists!).

On September 14, 2015 at 09:50:45 UTC the two detectors of the Laser Interferometer Gravitational-Wave Observatory simultaneously observed a transient gravitational-wave signal. The signal sweeps upwards in frequency from 35 to 250 Hz with a peak gravitational-wave strain of 1.0 × 10-21. It matches the waveform predicted by general relativity for the inspiral and merger of a pair of black holes and the ringdown of the resulting single black hole. The signal was observed with a matched-filter signal-to-noise ratio of 24 and a false alarm rate estimated to be less than 1 event per 203 000 years, equivalent to a significance greater than 5.1σ. The source lies at a luminosity distance of 410+160-180 Mpc corresponding to a redshift z = 0.09+0.03−0.04. In the source frame, the initial black hole masses are 36+5-4 M and 29+4-4 M, and the final black hole mass is 62+4-4 M, with 3.0+0.5-0.5 Mc2 radiated in gravitational waves. All uncertainties define 90% credible intervals. These observations demonstrate the existence of binary stellar-mass black hole systems. This is the first direct detection of gravitational waves and the first observation of a binary black hole merger.

Incredible. Don’t miss the video at the top of The New York  Times article. It’s worth ten minutes of your time.