The Ultimate Container Ship

How big can they build a container ship? Big enough so it can't dock in any U.S. port. Check out the video from the New York Times below. The Mary Maersk requires only 27 crewmen to operate the 1300-foot behemoth.  The automation on the bridge and in the engine room is a key part of why so there are so few crew. I can imagine a lot more unemployed seamen as ships of this size become more common. But as consumers, we love the low prices we get from cheap transportation of goods from the manufacturer to the market.

http://nyti.ms/1mZkgjM


Video: Behemoth at Sea

Machines and Nightmares

I recently finished reading a riveting memoir by Agnès Humbert entitled, Résistance, A Woman's Journal of Struggle and Defiance in Occupied France.  This book is a diary of Humbert's experiences from the time the Nazis invaded France in 1940 to the end of World War II. Humbert was an intelligent  woman who was employed at one of the museums in Paris at the time of the invasion. At the age of 43, she decided to work with some trusted friends to produce an underground newspaper of the same name as the book, Résistance.  The little group of a dozen friends lasted about a year until it was betrayed by an unknown informer. The Nazis executed the men involved by firing squad and Humbert and several other women were convicted to five years of slave labor working in Nazi factories in Germany.

What does any of this have to do with technology? Humbert was assigned to work under the most horrifying conditions at a rayon factory in Krefeld, Germany.  I will skip over the descriptions of the malnourishment, abuse, filth, and inhumane treatment at the hands of the Nazis to relate something she wrote while working at the factory. While pondering the inhumanity and total unpredictability of her situation at the hands of her captures, she remarked in August, 1942:

"I wonder - a worthy subject for meditation - what Descartes would have made of industrial machinery. What a subject for a philosopher! Not just the relationship between man and machine, and all the upheavals, material, moral and social that come in its wake, but simply the thoughts that sometimes come into your head when you are working at a machine. There's no tricking a machine; it's just not possible. A part out of alignment? Production immediately slows down. A loose screw? The whole machine seizes up. I like and admire the incorruptible integrity of the machine. With work done by hand there is always a little leeway, a margin of error, and any time lost can be made up with a little effort or improvisation; machinery, on the other hand, admits absolutely no possibility of inaccuracy or prevarication, is immune to all excuses, lies or flattery, Enduring, unswerving and fiercely tenacious, machines can teach men a marvelous lesson in integrity. The builders of the future, of our future, should take inspiration from man's handiwork, the Blessed Machine!"

I had to think about this for a bit because the machine she was describing was the spinning machine which extruded the viscous rayon pre-polymer through a very fine platinum minaret into an acid bath to form the thread. She had to work on this machine without any protection for her skin or eyes. The pre-polymer is extremely caustic to the skin. The acid is not only caustic but leads to blindness. The slave laborers were offered no protective clothing or gloves and had to work ten to twelve hour shifts even while Allied bombing raids were going on. She was a mass of sores and unable to even see for days at a time. How could she sing the praises of machinery? Because she desperately needed to experience something that had integrity.

Humboldt's countrymen in her opinion had totally lost their integrity in rolling over without fighting back against the Nazis. What kept her alive through her incarceration was a feeling of integrity - she would never bend or yield to her captors. She never cracked under interrogation by the Gestapo when they wanted information on her colleagues. She never once begged for mercy. She was one tough lady.

Humboldt survived the war. She was liberated by the U.S. Army while being held captive in April 1945. She stayed for a few months after her liberation and worked tirelessly, but fairly, to identify the true Nazis in the area that were trying to fade into the woodwork. She returned to France and lived for almost another twenty years, dying in 1963.

It still amazes me as I reread her words on machines that she could have been so lucid about such a subject in the middle of such horror.  Having never worked with machines, I would have thought she would have hated them. Yet, she found something positive in them even under the worst of circumstances. I stand in awe. I would love to have met her.

You can get the book on Amazon. There is also a Kindle edition.

The Automatic (Rail) Road Machine

As I wrote in my last blog, machines that can lay an entire road in one operation are now a reality. I just came across a video of such a machine.

The video below shows a multi-part machine which lays high-speed railroad tracks. The video was shot in Europe but a similar machine is being used to lay tracks on the high-speed rail line between St. Louis and Chicago.  According to the source that I saw, these are the only two such machines that exist in the world. It's quite an operation. Give it a look:

[A "Hat's Off" to my sister-in-law, Peggy, for bringing this to my attention.]

Automata

Have you seen the new Martin Scorsese movie, Hugo? I highly recommend it for multiple reasons - a great story, a love of silent films, wonderful cinematography (in 3D, no less), and the recreation of an automaton. The film is based loosely in real people and events. Georges Melies. the first creator of silent fictional films, is one of the central characters of the film - wonderfully portrayed by Ben Kingsley. The film is set in Paris's Montparnasse train station some time after the end of World War I. Melies is selling toys in a tiny stall in the train station where he meets the film's protagonist, Hugo.

Jacques de Vaucanson

Automata are what today we would call robots. They were an attempt by their builders to render a life-like creature from machine parts. The history of automata goes back millenia. Even Leonardo da Vinci drew designs for automata and built at least one in the shape of a lion. Various builders followed with increasingly sophisticated automata. One of the earliest masters was Jacques de Vaucanson who exhibited in 1738 the mechanical figure of a flute player which could actually play this difficult instrument through subtle recreations of the lips, palate, and facial muscles (not to mention the fingering of the keys). This automaton was a smash hit and other builders followed with their own mechanical recreations of life.  Much later, as we shall see, Georges Melies became fascinated with automata.

Georges Melies

Georges Melies was born in France in 1884 and trained to become a shoe maker, like his father. But while training in London, he became enthralled by the magic he saw performed in the Egyptian Hall.  When he returned to France he worked in his father's business until his father died. At that point, he sold his share of the business to his two brothers and used the money to buy the dilapidated Parisian theater of magician, Jean-Eugene Robert-Houdin (from whom Houdini took his stage name).

Robert-Houdin started life apprenticing as a watchmaker but was always fascinated by magic. While working in the Loire valley, he became seriously ill and was nursed back to life by a magician named Torrini. Torrini, it turns out, had several automata that he used in his magic shows. The automata were badly in need of repairs and Robert-Houdin used his mechanical skills to bring them back to working condition. He also immediately saw the link between magic and the seemingly life-like power of these mechanical androids.

Robert-Houdin

Robert-Houdin went back to Paris and began his work building clocks, astronomical instruments, and automata.  In 1844, he won a medal at the Paris Exposition for his writing automaton.  Robert-Houdin now started to devote all his energy to automata. His 1844 model was enhanced to where it could perfectly recreate Robert-Houdin's signature. Ironically, P.T. Barnum bought the automaton while on a tour of Europe with Tom Thumb. The automaton was exhibited in England and then sent back to America where it was displayed in Barnum's museum of oddities. It was eventually destroyed in a museum fire.

Robert-Houdin had opened a magic theater in Paris during this time period. He died in 1871 and his sons managed his theater for 17 years until one of the son's widows sold it to George Melies.  The theater came with all of the props including Robert-Houdin's remaining automata.  Melies immediately repaired the theater and the automata.  The movie would have us think that the writing automaton was still in Paris but this was not the case as mentioned before.

Soon after, Melies became fascinated with photography and moving pictures when he saw the early work of the Lumieres brothers.  He tried to buy one of their cameras and when they turned him down, he went on to build his own. Melies started making his own films and by 1897, the magic theater was mostly a movie theater. Below is his 1902 classic, A Trip to the Moon.

In the film, Hugo, the boy, must repair the writing automaton to try to retrieve a message he felt that his dead father had left encrypted in the automaton. When he finally did get the machine repaired, it drew pictures which lead Hugo to the secret past of Georges Melies, who had long ago  fallen out of favor as a film maker and was now a toy seller in the train station (Melies did, indeed, fall out of favor as a film maker and ended his working years selling toys from a tiny stall in Montparnasse Station).

In the film, the automaton is meant to cast a mysterious grip on us. But that's nothing new. Automata have always delighted and confounded people with a mechanical imitation of life.  We still find robots fascinating. The word "robot", by the way, comes from a 1921 play by Karel Capek entitled, Rossum's Universal Robots.  Today, robots are literally part of our everyday life - whether it is the GPS navigation system in our car or the Scooba that scrubs our floors. But we still want to instill life and personality into these machines (Disclosure: we have named our GPS systems in our cars Jeeves and Prudence and talk to them regularly).  Robots populate our films and stories (who can forget HAL in 2001?). Robots might seem like our future.

Maybe someday these machines will become so sophisticated we might not be able to tell them apart from human beings. Personally, I doubt that it will happen. Even if we could create such creatures, our sensibilities would demand some form of visual recognition that tells us that this creature is not human. We are fascinated by machine life but we are very wary of losing the boundaries of our own humanity.  Robots will become ubiquitous but not invisible.  The line between man and machine is not easily transgressed.

[For a much more in depth treatment of automata, mechanical life, and Georges Melies,  I would recommend Gaby Woods 2002 book entitled (in the U.S.), Edison's Eve, and in Britain, Living Dolls.}

Thinking Machines: For Better and For Worse

Our machines get ever more intelligent, or at least capable of doing more and more complex tasks. Whether this should be considered intelligence is a separate question.  Last night, I saw two programs that brought this clearly into focus.

The first was the IBM Watson Challenge on Jeopardy. If you haven't been tracking this story, IBM has created a new computing system for its latest corporate Grand Challenge: a machine smart enough to understand Natural Language Processing (NLP).  In past Grand Challenges, IBM created a chess-playing computer it named Big Blue which was able to beat Grand Chessmaster, Garry Kasparov, and another computer dubbed Blue Gene (Big Blue + Genome) which was used to sequence DNA. For the current challenge, the IBM team named their computer Watson after IBM founder Tom Watson whose standing directive to his employees was "Think".  IBM's R&D lab wanted to take on a tough challenge and they felt that hardly anything could be tougher for a computer than being able to compete successfully on the television quiz-show, Jeopardy.  Who isn't familiar with the opening line, "This is Jeopardy!" with host, Alex Trebek (Disclosure Alert: we once sat in the studio audience of a filming of the show in LA. Our daughter chatted up Alex during the commercial break).

Watson was positioned at the center podium and competed against the two all-time high scoring contestants, Ken Jennings and Brad Rutter. Poor Ken and Brad. Watson's winnings over the three days of the tournament were $77,147 compared to Jennings' $24,000 and Rutter's $21,600.  Watching the show, I was impressed with how adept Watson was at answering questions filled with the usual twists on topics and language that are part of the Jeopardy game. But it was also clear that Watson got some things wildly wrong. His answer to a question about U.S. Cities was Toronto.  That seems like something that would have been easily ruled out in the programming of his logic circuits.  Nonetheless, Watson is an impressive advance in NLP and IBM now hopes to perfect the technology for many other fields including medical diagnostics.

The second program that I saw last night was Nova's "The Crash of Flight 447", which described in harrowing detail the final minutes of the Air France flight that disappeared over the Atlantic on the night of May 31, 2009.

Watch the full episode. See more NOVA.

Nova assembled its own team of investigators to look into what might have caused one of the most modern aircraft in the skies, the Airbus A330, to  tumble out of the sky. The official investigation is still ongoing and the Black Box and flight recorder have yet to be found in 15,000 feet of water in the mid-Atlantic. My short summary to the longer description given during the program is that the computer flying the plane was instrumental in the crash.

How could that be? The longer sequence of events was that Flight 447 encountered a very turbulent thunderstorm in the mid-Atlantic that caused all three of its airspeed sensors (called pitot tubes) to ice up and fail.  The flight computer was in control of the aircraft and airspeed is a key parameter for the computer to perform its tasks. The lack of airspeed data caused the flight computer to start to go into a sequence of failure modes, starting with disengaging the autopilot and throttling back the engines.  The pilots were instantly thrust into an extremely challenging situation with multiple cascading computer warnings coming at them as they manually tried to control the plane in heavy turbulence.  Without accurate airspeed information, they were flying in an even more dangerous situation.  Modern jets have very narrow windows of acceptable airspeed at cruising altitude.  Changes in airspeed of as little as 10 knots either up or down can cause the plane's wings to stall (lose lift).  When an aircraft stalls, the plane not only begins to rapidly descend, it also can go into a roll that can make recovery even more difficult.

The Nova team did a good job of demonstrating how pilots are supposed to avoid this problem.  The Nova investigators recreated the conditions that the pilots of Flight 447 encountered that night in a flight simulator. The two pilots who "flew" the rerun did not know in advance what they were going to be facing in the simulator.  The rerun began with the thunderstorm suddenly showing up on their radar and progressed to the loss of airspeed data and the flight computer issuing failure warnings. The standard procedure for pilots in such a situation is to increase engine power to 85 percent and adjust the rear elevators to 5 percent up-attitude.  This always put the aircraft at a safe speed to avoid a stall.  The pilots in the simulator did just what they were supposed to do and all went smoothly as they recovered control of the plane. But apparently, the pilots on Flight 447 were too busy or too distracted to follow this standard procedure.  The result was the loss of over 200 people's lives in a terrible aircraft tragedy.

Some of the pilots interviewed on the Nova program commented on how today's generation of pilots have come to depend on the flight computer to fly the plane.  They have too little experience with how to pull an out-of-control plane back to safety if the flight computer fails.  Having seen the pilots in the flight simulator follow the standard procedure of thrust and attitude adjustment, I wonder why the flight computer wasn't programmed to do the same thing when the loss of airspeed data started a sequence of failures?  Why depend on the pilots for this first safety measure?  Why doesn't the computer just do it and then alert the pilots to what had been implemented as part of the safety program to maintain control?  The program made clear that the flight computers are currently programmed to prevent pilots from maneuvering the plane in some way that would cause loss of control.  Why not in the loss of airspeed data situation?

Clearly, we are still in the infancy of computer intelligence whether it be computers like Watson which understand the difficulties of how we communicate in our natural language or the more prescriptive computers that fly airplanes, manage nuclear power plants, or even control the inner workings of our automobiles.  Much more is needed and certainly will be built into the computers in the future to enhance what we like to call intelligence. Computers are being built to mimic what humans can do under the best of circumstances.  Surpassing what humans can do is what Ray Kurzweil, the computer and music guru, calls The Singularity.  He thinks it is coming in the next decade or so.  I am not so sure.  But I am sure that it will happen in the first half of this century.  Then, like the computer, HAL in 2001: A Space Odyssey, we will be in a strange new world where the computer might say as it did, "I can't allow you to do that, Dave".  In the meantime, computers can be fun to watch or, under rare circumstances, they can create monumental tragedies.

[You can watch the entire Nova episode on the PBS website here.]

Vanished Occupations

I was looking at a "most e-mailed" story on the NPR website entitled, The Jobs of Yesteryear: Obsolete Occupations.  The NPR feature is a combination of old photos, text, and audio clips from people who used to do the work.

And what are the Obsolete Occupations?  Lector, Elevator Operator, Copy Boy, Pinsetter, River Driver, Iceman, Lamplighter, Milkman, Switchboard Operator, Typist in a Typing Pool, Typesetter, and Telegraph Operator.  All of these jobs were displaced by a combination of technology and changing society.  The article makes clear that you can still find some of these jobs in small specialty niches or in different parts of the world.

I can remember as a kid living in East Lansing, Michigan that our milkman came around with a horse-drawn milk wagon.  Lest you think I am that old, this was a gimmick on the part of the delivery service to attract business.  Still, I did get to see at least one older way in which technology was practiced.  I can remember hearing the horse and wagon coming, grabbing a carrot or apple for the horse, and racing out the door to see who would get there first.  On one occasion I won the foot race with my brother and presented a nice carrot to the horse.  But even horses can apparently have "bad days at the office" because after sniffing the carrot the horse turned his head and bit me on the shoulder.  My love of horses ended at that moment.

Of course, any list like the one in NPR story begs the question of what the Obsolete Occupations will be fifty years from now?  So here are a few of my predictions.  Add your own (you might even include your own job in the list):

• Pharmacists for routine prescriptions
• Bank tellers
• Retail store checkout clerks
• Telephone repairmen
• Toll collectors for highways and bridges
• Fast food customer clerks
• Automobile transmission repair specialists
• Oil change mechanics

The key to all of these is to think about automation or obsolete technology.  But our ability to project something like this accurately is more limited than we might think at first blush.  The reasons we may need certain jobs can change for reasons other than automation.  Take the milkman or grocery-man for an example.  In our neighborhood, a start-up company called Simon Delivers has been carving out a niche to deliver complete grocery orders to busy families where both spouses work and don't want to hassle with the grocery store.  The need being filled is not limited mobility as it was in the past but limited time.  There are a number of these types of small niche innovators who are capturing an unmet need, but these are the minority.  The bigger picture is inexorably towards automation replacing people.  

So what should the high school guidance counselors suggest?  Any job in which automation is not likely to be a factor in the near future:  physician, nurse, dentist, dental hygienist, lawyer, engineer, writer, actor, and many more.  Just think "brain power."  This also is why we need to get everyone educated beyond a high school diploma.  The jobs which not only pay, but are even there, will take brains, lots of brains.