Rise of the Robots | Machine Learning

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Re: Rise of the Robots

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“solving intelligence”.

http://www.technologyreview.com/view/53 ... g-machine/
Emerging Technology From the arXiv

October 29, 2014

Google's Secretive DeepMind Start-up Unveils A "Neural Turing Machine"

DeepMind has built a neural network that can access an external memory like a conventional Turing machine. The result is a computer that mimics the short-term memory of the human brain.

One of the great challenges of neuroscience is to understand the short-term working memory in the human brain. At the same time, computer scientists would dearly love to reproduce the same kind of memory in silico.

Today, Google’s secretive DeepMind start-up, which it bought for $400 million earlier this year, unveils a prototype computer that attempts to mimic some of the properties of the human brain’s short-term working memory. The new computer is a type of neural network that has been adapted to work with an external memory. The result is a computer that learns as it stores memories and can later retrieve them to perform logical tasks beyond those it has been trained to do.

DeepMind’s breakthrough follows a long history of work on short-term memory. In the 1950s, the American cognitive psychologist George Miller carried out one of the more famous experiments in the history of brain science. Miller was interested in the capacity of the human brain’s working memory and set out to measure it with the help of a large number of students who he asked to carry out simple memory tasks.

Miller’s striking conclusion was that the capacity of short-term memory cannot be defined by the amount of information it contains. Instead Miller concluded that the working memory stores information in the form of “chunks” and that it could hold approximately seven of them.

That raises the curious question: what is a chunk? In Miller’s experiments, a chunk could be a single digit such as a ‘4’, a single letter such as a ‘q’, a single word or a small group of words that together have some specific meaning. So each chunk can represent anything from a very small amount of information to a hugely complex idea that is equivalent to large amounts of information.

But however much information a single chunk represents, the human brain can store only about seven of them in its working memory.

Here is an example. Consider the following sentence: “This book is a thrilling read with a complex plot and lifelike characters.”

This sentence consists of around seven chunks of information and is clearly manageable for any ordinary reader.

By contrast, try this sentence: “This book about the Roman Empire during the first years of Augustus Caesar’s rein at the end of the Roman Republic, describes the events following the bloody Battle of Actium in 31 BC when the young emperor defeated Mark Antony and Cleopatra by comprehensively outmaneuvering them in a major naval engagement.”

This sentence contains at least 20 chunks. So if you found it more difficult to read, that shouldn’t be a surprise. The human brain has trouble holding this many chunks in its working memory.

In cognitive science, the ability to understand the components of a sentence and store them in the working memory is called variable binding. This is the ability to take a piece of data and assign it to a slot in the memory and to do this repeatedly with data of different length, like chunks.

During the 90s and 00s, computer scientists repeatedly attempted to design algorithms, circuits and neural networks that could perform this trick. Such a computer should be able to parse a simple sentence like “Mary spoke to John” by dividing it into its component parts of actor, action and the receiver of the action. So in this case, it would assign the role of actor to Mary, the role of action to the words “spoke to” and the role of receiver of the action to “John”.

It is this task that DeepMind’s work addresses, despite the very limited performance of earlier machines. “Our architecture draws on and potentiates this work,” say Alex Graves, Greg Wayne and Ivo Danihelka at DeepMind, which is based in London.

They begin by redefining the nature of a neural network. Until now, neural networks have been patterns of interconnected “neurons” which are capable of changing the strength of the interconnections in response to some external input. This is a form of learning that allows them to spot similarities between different inputs.

But the fundamental process of computing contains an important additional element. This is an external memory which can be written to and read from during the course of a computation. In Turing’s famous description of a computer, the memory is the tickertape that passes back and forth through the computer and which stores symbols of various kinds for later processing.

This kind of readable and writable memory is absent in a conventional neural network. So Graves and co have simply added one. This allows the neural network to store variables in its memory and come back to them later to use in a calculation.

This is similar to the way an ordinary computer might put the number 3 and the number 4 inside registers and later add them to make 7. The difference is that the neural network might store more complex patterns of variables representing, for example, the word ‘Mary’.

Since this form of computing differs in an important way from a conventional neural network, Graves and co give it a new name–they call it a Neural Turing Machine, the first of its kind to have been built. The Neural Turing Machine learns like a conventional neural network using the inputs it receives from the external world but it also learns how to store this information and when to retrieve it.

The DeepMind work involves first constructing the device and then putting it through its paces. Their experiments consist of a number of tests to see whether, having trained a Neural Turing Machine to perform a certain task, it could then extend this ability to bigger or more complex tasks. “For example, we were curious to see if a network that had been trained to copy sequences of length up to 20 could copy a sequence of length 100 with no further training,” say Graves and co.

It turns out that the neural Turing machine learns to copy sequences of lengths up to 20 more or less perfectly. And it then copies sequences of lengths 30 and 50 with very few mistakes. For a sequence of length 120, errors begin to creep in, including one error in which a single term is duplicated and so pushes all the following terms one step back. “Despite being subjectively close to a correct copy, this leads to a high loss,” say the team.

Although the sequences involved are random, it’s not hard to imagine how they might represent more complex ideas such as ‘Mary’ or ‘spoke to’ or ‘John’. An important point is that the amount of information these sequences contain is variable, like chunks.

They compare the performance of their Neural Turing Machine with a conventional neural network. The difference is significant. The conventional neural network learns to copy sequences up to length 20 almost perfectly. But when it comes to sequences that are longer than the training data, errors immediately become significant. An its copy of the longest sequence of length 120 is almost unrecognisable compared to the original.

The DeepMind team go on to test the Neural Turing Machine on other tasks. For example, one of these is the equivalent of photocopying: the task is to copy a sequence and then repeat that sequence a specified number of times and end with a predetermined marker. Once again, the Neural Turing Machine significantly outperforms a conventional neural network.

That is an impressive piece of work. “Our experiments demonstrate that [our Neural Turing Machine] is capable of learning simple algorithms from example data and of using these algorithms to generalise well outside its training regime,” say Graves and co.

That is an important step forward that has the potential to make computing machines much more brain-like than ever before. But there is significant work ahead.

In particular, the human brain performs a clever trick to make sense of complex arguments. An interesting question that follows from Miller’s early work is this: if our working memory is only capable of handling seven chunks, how do we make sense of complex arguments in books, for example, that consists of thousands or tens of thousands of chunks?

Miller’s answer is that the brain uses a trick known as a recoding. Let’s go back to our example of the book and add another sentence: “This book is a thrilling read with a complex plot and lifelike characters. It is clearly worth the cover price.”

Once you have read and understood the first sentence, your brain stores those seven chunks in a way that is available as a single chunk in the next sentence. In this second sentence, the pronoun “it” is this single chunk. Our brain automatically knows that ‘it’ means: “the book that is a thrilling read with a complex plot and lifelike characters”. It has recoded the seven earlier chunks into a single chunk.

To Miller, the brain’s ability to recode in this way was one of the keys to artificial intelligence. He believed that until a computer could reproduce this ability, it could never match the performance of the human brain.

Google’s DeepMind has stated that its goal is “solving intelligence”. If this solution is anything like human intelligence, a good test would be to see whether Neural Turing Machines are capable of Miller’s recoding trick.
"I fancied myself as some kind of god....It is a sort of disease when you consider yourself some kind of god, the creator of everything, but I feel comfortable about it now since I began to live it out.” -- George Soros
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Re: Rise of the Robots

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http://www.pcworld.com/article/2851393/ ... ouble.html
Microsoft turns to robotic security guards to watch for trouble

Nick Mediati
@dtnick Nov 22, 2014 12:24 PM

OK, so the robot apocalypse probably won’t happen any time soon, but the new robot sentries guarding Microsoft’s Silicon Valley campus seem like something straight out of a futuristic sci-fi movie.

According to ExtremeTech, each of the K5 security guard robots from robotics company Knightscope stands 5 feet tall and weighs 300 pounds, so you probably don’t want to mess with one.

The K5 robots don’t come with any weapons onboard—thankfully—but they use a suite of alarms, sirens, and cameras to monitor and patrol the grounds of Microsoft’s campus. If one spots trouble, it’ll either sound an alarm or dispatch a human security guard to its location.

ExtremeTech notes that the K5 can run for up to 24 hours on a single charge, and can recharge in only about 20 minutes. Its battery won’t die out in the field, though—these bots will return to the charging station by themselves when their batteries start to run dry.

The story behind the story: Robots are playing an increasingly large role in security and military operations. Google-owned robotics company Boston Dynamics, for example, has been working with DARPA to develop various robots to aid soldiers in combat settings. Meanwhile, South Korea deployed a robotic sentry to guard its side of the Demilitarized Zone in 2010. Unlike K5, though, South Korea’s guard robot came fully armed.
"I fancied myself as some kind of god....It is a sort of disease when you consider yourself some kind of god, the creator of everything, but I feel comfortable about it now since I began to live it out.” -- George Soros
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Re: Rise of the Robots

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FT | Dawn of a robot revolution as army of machines escape the factory
Approximately 95,000 new professional service robots, worth some $17.1bn, are set to be installed for professional use between 2013 and 2015, according to the International Federation of Robotics. That excludes an estimated 22m domestic service robots – the autonomous vacuum cleaners and lawnmowers that are already becoming a familiar sight to consumers.
A trickle to a flood?
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Re: Rise of the Robots

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Still, some occupations appear safe for the foreseeable future:

Image
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Re: Rise of the Robots

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Typhoon wrote:Still, some occupations appear safe for the foreseeable future:

Image
http://s14.postimg.org/8tn0qdo9b/daily_ ... 763_05.gif

cute.
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Re: Rise of the Robots

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M8YjvHYbZ9w

damn.
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Re: Rise of the Robots

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noddy wrote:M8YjvHYbZ9w

damn.
too cool! Hopefully they remember to fit the OSHA required backup alarm! How long before some redneck shoots one, tries to eat it, and PETA goes ballistic?
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Re: Rise of the Robots

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News story in the near future.

"Robots take fire while riding in helicopter"

http://www.cnn.com/2015/02/05/tech/mci-robojournalist/

Could a robot have written this story? The rise of the Robo-journalist


By Peter Shadbolt, for CNN


Updated 9:46 AM ET, Thu February 5, 2015
(CNN)—They don't call journalists 'hacks' for nothing.

At large news agencies where speed is crucial, template-style stories have long been used for company results, allowing journalists to simply key in the relevant facts and numbers and fire off the dispatch.

Often disparagingly referred to as 'churnalism,' some of the larger media organisations -- including the L.A. Times and Associated Press -- have now turned to robots to take the grind out of formulaic dispatches.

The L.A. Times uses the algorithms in its in-house software -- called Quakebot - to produce reports on local earthquakes, using data provided by the US Geological Survey.

The reports typically hit the newspaper's website within three minutes of the tremor being recorded.

For data-rich stories such as finance stories, sports stories and breaking news where dry facts need to be collated and sent out quickly, robo-journalists are becoming increasingly common.

Narrative Science, a Chicago company set up in 2010 to commercialize technology developed at Northwestern University that crunches data into a narrative, markets its Quill software to television stations and to financial houses that generate earnings statements.

"A lot of people felt threatened by what we were doing, and we got a lot of coverage," Narrative Science CEO Stuart Frankel told MIT Technology Review. "It led to a lot of inquiries from all different industries and to the evolution to a different business."

Its algorithms now write up lengthy reports on the performance of mutual funds for the consumption of investors and regulators.

"It goes from the job of a small army of people over weeks to just a few seconds," Frankel said. "We do 10- to 15-page documents for some financial clients."

While the prose can seem stilted, chief scientist at the company Kris Hammond says the algorithm is growing in complexity.

"We know how to introduce an idea, how not to repeat ourselves, how to get shorter," he said.

Writing in the nuances can simply be a matter of setting the software's parameters: a devastating loss for a sports team can be written in a sympathetic style for the team's home audience while regulatory filings can be as exhaustive and granular as required for the client.

Known as 'natural language generation', the company -- which does not reveal exactly how its software operates - is tapping into years of research into how software can write in language that responds not just to the data but its context and its relevance.

The idea that humans will always have a unique ability beyond the reach of algorithms is just wishful thinking

Dr Yuval Harari

Hammond, meanwhile, believes it is only a matter of time before a robo-journalist will write a Pulitzer Prize winning story as the software grows in sophistication. He said there is no reason for the algorithms to move from commodity news, to narrative journalism to complex long-form features.

Asked whether a computer would win a Pulitzer Prize within 20 years, he disagreed saying it would happen within five years.

"Humans are unbelievably rich and complex, but they are machines," Hammond told Wired. "In 20 years, there will be no area in which Narrative Science doesn't write stories."

While media organizations that use bots to crunch data say the software is merely an adjunct to the journalist's work, and will never replace them, some commentators believe that mapping the way forward for artificial intelligence will be one of the most urgent tasks of the 21st century.

Professor Yuval Harari, Israeli historian and author of Sapiens: A Brief History of Humankind, believes it is not just journalism that is being challenged by machines.

"The conscious experiences of a flesh-and-blood taxi driver are infinitely richer than those of Google's self-driving car, which feels nothing," Harari told CNN.

"But what the system needs from a taxi driver is to bring passengers from point A to point B as quickly, safely and cheaply as possible.

"Google's self-driving car will soon be able to do that far better than a human driver. The same goes for mechanics, lawyers, soldiers, doctors, teachers -- and even computer engineers."

Read this: In a hurry? Let a robot valet park your car

He said that while machines may have replaced humans for the past 200 years since the Industrial Revolution, there has always been something that humans could do better than machines.

However, he said that this gap is likely to close over the next 100 years.

"(Since the Industrial Revolution) humans have focused more on performing cognitive tasks. But what will happen once computerized algorithms can outperform humans in that (area) too?

Some believe that artificial intelligence should be viewed as a threat to the human race.

Oxford philosopher and transhumanist Nick Bostrom is convinced that humanity will end up being "the biological boot loader for superintelligent AI".

Elon Musk, the superstar entrepreneur who founded PayPal, SpaceX and Tesla Motors, echoed this warning via his Twitter feed:

"The idea that humans will always have a unique ability beyond the reach of non-conscious algorithms is just wishful thinking. It is based on the traditional assumption that intelligence and consciousness are inextricably linked to one another. For millions of years of evolution, this may have been true. But no longer," says Harari.
"I fancied myself as some kind of god....It is a sort of disease when you consider yourself some kind of god, the creator of everything, but I feel comfortable about it now since I began to live it out.” -- George Soros
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Re: Rise of the Robots

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A friend of mine just became the "Product Manager" for Watson for lack of a better term. He's helping IBM identify various business use cases that can be packaged and sold as individual products.
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Re: Rise of the Robots

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Enki wrote:A friend of mine just became the "Product Manager" for Watson for lack of a better term. He's helping IBM identify various business use cases that can be packaged and sold as individual products.
Good to hear from you Enki.

My guess is that medical diagnostics would be a major application.
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Re: Rise of the Robots

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Enki wrote:A friend of mine just became the "Product Manager" for Watson for lack of a better term. He's helping IBM identify various business use cases that can be packaged and sold as individual products.
Nice Plus the added bonus he didn't get a job writing news articles :P
"I fancied myself as some kind of god....It is a sort of disease when you consider yourself some kind of god, the creator of everything, but I feel comfortable about it now since I began to live it out.” -- George Soros
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Re: Rise of the Robots

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in modern ibm, product manages you.

(boom tish)
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Re: Rise of the Robots

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http://blogs.wsj.com/economics/2015/02/ ... picks=true
U.S. Productivity Now Grows Faster Than Jobs. What Changed?

By
Timothy Aeppel

Automated welding machine robots assemble automobile bodies last last year. —Getty Images
Some economists call it the “great decoupling.”

For decades, U.S. productivity and total employment rose in lockstep. From 1953 to 1999, average annual growth in productivity was 2.1%, exactly the same as growth in jobs. As the U.S. grew richer and its workers generated more output with the aid of better machines, it created a correspondingly healthy number of new jobs.

But at the turn of the century, something changed. Since 1999, productivity growth kept rolling along at 2.1%–but job growth has slumped to an average of 0.5%. Part of the problem can be traced to the last recession, which hit the job market hard and was followed by an extremely slow recovery.

Beyond that, economists see two other longer-lasting forces at work: globalization and technological advances. The offshoring of work has helped make U.S. businesses more efficient, while new machines allow the remaining U.S. workers to produce more with less.

“Technological progress has been a big cause—and my prediction for the future is that it will be an even bigger force going forward,” says Andrew McAfee, a management professor at the Massachusetts Institute of Technology’s business school who studies the trend. Advanced automation keeps pushing up output, he says, “but there’s less and less demand for good old-fashioned human labor.”

Mr. McAfee notes there’s been a similar decoupling in recent years between productivity and wage growth.

Mr. McAfee co-authored a book about the impact of automation on the job market with fellow MIT professor Erik Brynjolfsson, entitled “Race Against the Machine.”
"I fancied myself as some kind of god....It is a sort of disease when you consider yourself some kind of god, the creator of everything, but I feel comfortable about it now since I began to live it out.” -- George Soros
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Re: Rise of the Robots

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The robots are coming - John Lancaster, London Review of Books, vol. 37, no. 5, 5 March 2015
http://www.lrb.co.uk/v37/n05/john-lanch ... are-coming



Review of:


The Second Machine Age: Work, Progress and Prosperity in a Time of Brilliant Technologies by Erik Brynjolfsson and Andrew McAfee (Norton, 2014)

Average Is Over: Powering America beyond the Age of the Great Stagnation by Tyler Cowen (Plume, 2014)


... In the next two decades, 47 per cent of employment is ‘in the high-risk category’, meaning it is ‘potentially automatable’. Interestingly, though not especially cheeringly, it is mainly less well-paid workers who are most at risk. Recent decades have seen a polarisation in the job market, with increased employment at the top and bottom of the pay distribution, and a squeeze on middle incomes. ‘Rather than reducing the demand for middle-income occupations, which has been the pattern over the past decades, our model predicts that computerisation will mainly substitute for low-skill and low-wage jobs in the near future. By contrast, high-skill and high-wage occupations are the least susceptible to computer capital.’ So the poor will be hurt, the middle will do slightly better than it has been doing, and the rich – surprise! – will be fine.

Note that in this future world, productivity will go up sharply. Productivity is the amount produced per worker per hour. It is the single most important number in determining whether a country is getting richer or poorer. GDP gets more attention, but is often misleading, since other things being equal, GDP goes up when the population goes up: you can have rising GDP and falling living standards if the population is growing. Productivity is a more accurate measure of trends in living standards – or at least, it used to be. In recent decades, however, productivity has become disconnected from pay. The typical worker’s income in the US has barely gone up since 1979, and has actually fallen since 1999, while her productivity has gone up in a nice straightish line. The amount of work done per worker has gone up, but pay hasn’t. This means that the proceeds of increased profitability are accruing to capital rather than to labour. The culprit is not clear, but Brynjolfsson and McAfee argue, persuasively, that the force to blame is increased automation.

That is a worrying trend. Imagine an economy in which the 0.1 per cent own the machines, the rest of the 1 per cent manage their operation, and the 99 per cent either do the remaining scraps of unautomatable work, or are unemployed. That is the world implied by developments in productivity and automation. It is Pikettyworld, in which capital is increasingly triumphant over labour. We get a glimpse of it in those quarterly numbers from Apple, about which my robot colleague wrote so evocatively. Apple’s quarter was the most profitable of any company in history: $74.6 billion in turnover, and $18 billion in profit. Tim Cook, the boss of Apple, said that these numbers are ‘hard to comprehend’. He’s right: it’s hard to process the fact that the company sold 34,000 iPhones every hour for three months. Bravo – though we should think about the trends implied in those figures. For the sake of argument, say that Apple’s achievement is annualised, so their whole year is as much of an improvement on the one before as that quarter was. That would give them $88.9 billion in profits. In 1960, the most profitable company in the world’s biggest economy was General Motors. In today’s money, GM made $7.6 billion that year. It also employed 600,000 people. Today’s most profitable company employs 92,600. So where 600,000 workers would once generate $7.6 billion in profit, now 92,600 generate $89.9 billion, an improvement in profitability per worker of 76.65 times. Remember, this is pure profit for the company’s owners, after all workers have been paid. Capital isn’t just winning against labour: there’s no contest. If it were a boxing match, the referee would stop the fight.



The author is apparently "left" oriented. I would be interested in what conservatives have to offer in the face of these trends.
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Re: Rise of the Robots

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Apollonius wrote:The robots are coming - John Lancaster, London Review of Books, vol. 37, no. 5, 5 March 2015
http://www.lrb.co.uk/v37/n05/john-lanch ... are-coming



Review of:


The Second Machine Age: Work, Progress and Prosperity in a Time of Brilliant Technologies by Erik Brynjolfsson and Andrew McAfee (Norton, 2014)

Average Is Over: Powering America beyond the Age of the Great Stagnation by Tyler Cowen (Plume, 2014)


... In the next two decades, 47 per cent of employment is ‘in the high-risk category’, meaning it is ‘potentially automatable’. Interestingly, though not especially cheeringly, it is mainly less well-paid workers who are most at risk. Recent decades have seen a polarisation in the job market, with increased employment at the top and bottom of the pay distribution, and a squeeze on middle incomes. ‘Rather than reducing the demand for middle-income occupations, which has been the pattern over the past decades, our model predicts that computerisation will mainly substitute for low-skill and low-wage jobs in the near future. By contrast, high-skill and high-wage occupations are the least susceptible to computer capital.’ So the poor will be hurt, the middle will do slightly better than it has been doing, and the rich – surprise! – will be fine.

Note that in this future world, productivity will go up sharply. Productivity is the amount produced per worker per hour. It is the single most important number in determining whether a country is getting richer or poorer. GDP gets more attention, but is often misleading, since other things being equal, GDP goes up when the population goes up: you can have rising GDP and falling living standards if the population is growing. Productivity is a more accurate measure of trends in living standards – or at least, it used to be. In recent decades, however, productivity has become disconnected from pay. The typical worker’s income in the US has barely gone up since 1979, and has actually fallen since 1999, while her productivity has gone up in a nice straightish line. The amount of work done per worker has gone up, but pay hasn’t. This means that the proceeds of increased profitability are accruing to capital rather than to labour. The culprit is not clear, but Brynjolfsson and McAfee argue, persuasively, that the force to blame is increased automation.

That is a worrying trend. Imagine an economy in which the 0.1 per cent own the machines, the rest of the 1 per cent manage their operation, and the 99 per cent either do the remaining scraps of unautomatable work, or are unemployed. That is the world implied by developments in productivity and automation. It is Pikettyworld, in which capital is increasingly triumphant over labour. We get a glimpse of it in those quarterly numbers from Apple, about which my robot colleague wrote so evocatively. Apple’s quarter was the most profitable of any company in history: $74.6 billion in turnover, and $18 billion in profit. Tim Cook, the boss of Apple, said that these numbers are ‘hard to comprehend’. He’s right: it’s hard to process the fact that the company sold 34,000 iPhones every hour for three months. Bravo – though we should think about the trends implied in those figures. For the sake of argument, say that Apple’s achievement is annualised, so their whole year is as much of an improvement on the one before as that quarter was. That would give them $88.9 billion in profits. In 1960, the most profitable company in the world’s biggest economy was General Motors. In today’s money, GM made $7.6 billion that year. It also employed 600,000 people. Today’s most profitable company employs 92,600. So where 600,000 workers would once generate $7.6 billion in profit, now 92,600 generate $89.9 billion, an improvement in profitability per worker of 76.65 times. Remember, this is pure profit for the company’s owners, after all workers have been paid. Capital isn’t just winning against labour: there’s no contest. If it were a boxing match, the referee would stop the fight.
The author is apparently "left" oriented. I would be interested in what conservatives have to offer in the face of these trends.
Well, here's a counter-view opinion from a newspaper that many would call conservative:

FT | Luddites fear humanity will make short work of finite wants
If new technologies really cut jobs, we would all be out of work by now
GIven the track record of expert pundits in predicting the future, my guess is that the future will be different than most predictions :wink:
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Re: Rise of the Robots

Post by noddy »

someone should automate doomer pron.

google trends is probably a good datasource for things to extrapolate into psychosisville.

which isnt to say i dont think we are in a time of change and a goodly percentage of the population is going to cop it good and hard from those changes, just that i dont see the left nor the right of politics having viable solutions so its best to look elsewhere for those.
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Re: Rise of the Robots

Post by Simple Minded »

Typhoon wrote:
Apollonius wrote:The robots are coming - John Lancaster, London Review of Books, vol. 37, no. 5, 5 March 2015
http://www.lrb.co.uk/v37/n05/john-lanch ... are-coming



Review of:


The Second Machine Age: Work, Progress and Prosperity in a Time of Brilliant Technologies by Erik Brynjolfsson and Andrew McAfee (Norton, 2014)

Average Is Over: Powering America beyond the Age of the Great Stagnation by Tyler Cowen (Plume, 2014)


... In the next two decades, 47 per cent of employment is ‘in the high-risk category’, meaning it is ‘potentially automatable’. Interestingly, though not especially cheeringly, it is mainly less well-paid workers who are most at risk. Recent decades have seen a polarisation in the job market, with increased employment at the top and bottom of the pay distribution, and a squeeze on middle incomes. ‘Rather than reducing the demand for middle-income occupations, which has been the pattern over the past decades, our model predicts that computerisation will mainly substitute for low-skill and low-wage jobs in the near future. By contrast, high-skill and high-wage occupations are the least susceptible to computer capital.’ So the poor will be hurt, the middle will do slightly better than it has been doing, and the rich – surprise! – will be fine.

Note that in this future world, productivity will go up sharply. Productivity is the amount produced per worker per hour. It is the single most important number in determining whether a country is getting richer or poorer. GDP gets more attention, but is often misleading, since other things being equal, GDP goes up when the population goes up: you can have rising GDP and falling living standards if the population is growing. Productivity is a more accurate measure of trends in living standards – or at least, it used to be. In recent decades, however, productivity has become disconnected from pay. The typical worker’s income in the US has barely gone up since 1979, and has actually fallen since 1999, while her productivity has gone up in a nice straightish line. The amount of work done per worker has gone up, but pay hasn’t. This means that the proceeds of increased profitability are accruing to capital rather than to labour. The culprit is not clear, but Brynjolfsson and McAfee argue, persuasively, that the force to blame is increased automation.

That is a worrying trend. Imagine an economy in which the 0.1 per cent own the machines, the rest of the 1 per cent manage their operation, and the 99 per cent either do the remaining scraps of unautomatable work, or are unemployed. That is the world implied by developments in productivity and automation. It is Pikettyworld, in which capital is increasingly triumphant over labour. We get a glimpse of it in those quarterly numbers from Apple, about which my robot colleague wrote so evocatively. Apple’s quarter was the most profitable of any company in history: $74.6 billion in turnover, and $18 billion in profit. Tim Cook, the boss of Apple, said that these numbers are ‘hard to comprehend’. He’s right: it’s hard to process the fact that the company sold 34,000 iPhones every hour for three months. Bravo – though we should think about the trends implied in those figures. For the sake of argument, say that Apple’s achievement is annualised, so their whole year is as much of an improvement on the one before as that quarter was. That would give them $88.9 billion in profits. In 1960, the most profitable company in the world’s biggest economy was General Motors. In today’s money, GM made $7.6 billion that year. It also employed 600,000 people. Today’s most profitable company employs 92,600. So where 600,000 workers would once generate $7.6 billion in profit, now 92,600 generate $89.9 billion, an improvement in profitability per worker of 76.65 times. Remember, this is pure profit for the company’s owners, after all workers have been paid. Capital isn’t just winning against labour: there’s no contest. If it were a boxing match, the referee would stop the fight.
The author is apparently "left" oriented. I would be interested in what conservatives have to offer in the face of these trends.
Well, here's a counter-view opinion from a newspaper that many would call conservative:

FT | Luddites fear humanity will make short work of finite wants
If new technologies really cut jobs, we would all be out of work by now
GIven the track record of expert pundits in predicting the future, my guess is that the future will be different than most predictions :wink:
As the old saying goes "Trends only continue until they feel like the norm." or paraphrased into Redneck Zen "Trees don't grow to the sky."

fascinating that for some, tech or capital replacing labor is the ultimate eutopian (Freudian typo) dream, or others, the potential "end of the world as we know it."

In the past, it was the Japanese, the Chinese, evil CEO's, capitalism..... when it comes to making people unemployable, middle class parents seem to be at least as effective as the other villains.
Last edited by Simple Minded on Wed Mar 04, 2015 12:36 pm, edited 2 times in total.
Simple Minded

Re: Rise of the Robots

Post by Simple Minded »

noddy wrote:someone should automate doomer pron.

google trends is probably a good datasource for things to extrapolate into psychosisville.

which isnt to say i dont think we are in a time of change and a goodly percentage of the population is going to cop it good and hard from those changes, just that i dont see the left nor the right of politics having viable solutions so its best to look elsewhere for those.
I keep tellin you guys, drop to yer knees and worship me as yer god and I'll solve all yer problems..... but, no....... what a bunch of fools...
noddy
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Re: Rise of the Robots

Post by noddy »

Simple Minded wrote:
noddy wrote:someone should automate doomer pron.

google trends is probably a good datasource for things to extrapolate into psychosisville.

which isnt to say i dont think we are in a time of change and a goodly percentage of the population is going to cop it good and hard from those changes, just that i dont see the left nor the right of politics having viable solutions so its best to look elsewhere for those.
I keep tellin you guys, drop to yer knees and worship me as yer god and I'll solve all yer problems..... but, no....... what a bunch of fools...
im cool with this plan, it means its not my fault, its yours.

so..

whens this place being fixed biatch ? where are my comforts ?
ultracrepidarian
Simple Minded

Re: Rise of the Robots

Post by Simple Minded »

noddy wrote:
Simple Minded wrote:
noddy wrote:someone should automate doomer pron.

google trends is probably a good datasource for things to extrapolate into psychosisville.

which isnt to say i dont think we are in a time of change and a goodly percentage of the population is going to cop it good and hard from those changes, just that i dont see the left nor the right of politics having viable solutions so its best to look elsewhere for those.
I keep tellin you guys, drop to yer knees and worship me as yer god and I'll solve all yer problems..... but, no....... what a bunch of fools...
im cool with this plan, it means its not my fault, its yours.

so..

whens this place being fixed biatch ? where are my comforts ?
It's all part of my plan..... it's not my fault you are smart enough to perceive it's perfection...... good things come to those who wait.....

where's my burnt offerings? mother boards don't count!

ya didn't put enough in the collection plate last week..... yer faith needs to be more pure..... worship harder maggot..... ;)
Last edited by Simple Minded on Wed Mar 04, 2015 12:45 pm, edited 2 times in total.
Simple Minded

Re: Rise of the Robots

Post by Simple Minded »

noddy wrote:someone should automate doomer pron.

google trends is probably a good datasource for things to extrapolate into psychosisville.
Low cost doomer porn for everyone, regardless of income.... wasn't that the promise of the information age?

Doomer porn is probably the only area in which automation/AI is not cost effective in comparison with humans.

"the difference between AI and stupidity is that AI has limits." Alfred Einstein
noddy
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Re: Rise of the Robots

Post by noddy »

the christians get clouds to rest their world weary bottoms and some elevator harp music, the muslims get the 72 virgin sultanas for all your afterlife fruit salad needs.

what be your offerings, its a buyers market you know.
ultracrepidarian
Simple Minded

Re: Rise of the Robots

Post by Simple Minded »

noddy wrote:...

what be your offerings, its a buyers market you know.
As I said previously, I'll solve all yer problems.... except the bad grammar and pooor spellin... for those, I sub contract to software companies.....
noddy
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Joined: Tue Dec 13, 2011 3:09 pm

Re: Rise of the Robots

Post by noddy »

[youtube]76&v=fP9jYiEq3xo[/youtube]
ultracrepidarian
User avatar
Heracleum Persicum
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Re: Rise of the Robots

Post by Heracleum Persicum »

.

noddy, I corrected it

fP9jYiEq3xo
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