Tag Archives: robotics

Links – early August, 2015

Well, I’m back, after deep dives into R programming and statistical modeling. I’d like to offer these links which I’ve bookmarked in recent days. The first four cover a scatter of topics, from impacts of the so-called sharing economy and climate developments to the currency impacts of the more and more certain moves by the US Federal Reserve to increase interest rates in September.

But then I’ve collected a number of useful links on robotics and artificial intelligence.

How the ‘sharing economy’ is upending the travel industry

DS: New York Attorney General Eric Schneiderman last October issued a report finding 72 percent of the reservations on Airbnb going back to 2010 were in violation of city law. What’s the industry doing to address these concerns?

MB: Listen, I think there are a lot of outdated regulations and a lot of outdated laws that were written in a time where you couldn’t possibly imagine the innovation that has come up from the sharing economy, and a lot of those need to be updated to meet the world that we live in today, and I think that’s important.  Sometimes you have regulations that are put in place by incumbent industries that didn’t want competition and you have some regulations that were put in place back in the ’60s and ’70s, where you couldn’t imagine any of these things, and so I think sometimes you need to see updates.

So there you go – laws on the books are outdated.

Brain-controlled prosthesis nearly as good as one-finger typing

The goal of all this research is to get thought-controlled prosthetics to people with ALS. Today these people may use an eye-tracking system to direct cursors or a “head mouse” that tracks the movement of the head. Both are fatiguing to use. Neither provides the natural and intuitive control of readings taken directly from the brain.

The U.S. Food and Drug Administration recently gave Shenoy’s team the green light to conduct a pilot clinical trial of their thought-controlled cursor on people with spinal cord injuries.

Jimmy Carter: The U.S. Is an “Oligarchy With Unlimited Political Bribery”

Unfortunately, very apt characterization from a formal standpoint of political science.


What to Expect from El Niño: North America

The only El Niño events in NOAA’s 1950-2015 database comparable in strength to the one now developing occurred in 1982-83 and 1997-98… Like other strong El Niño events, this one will almost certainly last just one winter. But at least for the coming wet season, it holds encouraging odds of well-above average precipitation for California. During a strong El Niño, the subtropical jet stream is energized across the southern U.S., while the polar jet stream tends to stay north of its usual winter position or else consolidate with the subtropical jet. This gives warm, wet Pacific systems a better chance to push northeast into California… Milder and drier a good bet for Pacific Northwest, Northern Plains, western Canada.. Rockies snowfall: The south usually wins out…Thanks to the jet-shifting effects noted above, snowfall tends to be below average in the Northern Rockies and above average in the Southern Rockies during strong El Niños. The north-south split extends to Colorado, where northern resorts such as Steamboat Springs typically lose out to areas like the San Juan and Sangre de Cristo ranges across the southern part of the state. Along the populous Front Range from Denver to Fort Collins, El Niño hikes the odds of a big snowstorm, especially in the spring and autumn. About half of Boulder’s 12” – 14” storms occur during El Niño, and the odds of a 20” or greater storm are quadrupled during El Niño as opposed to La Niña.

According to NOAA, the single most reliable El Niño outcome in the United States, occurring in more than 80% of El Niño events over the last century, is the tendency for wet wintertime conditions along and near the Gulf Coast, thanks to the juiced-up subtropical jet stream.

Emerging market currencies crash on Fed fears and China slump

The currencies of Brazil, Mexico, South Africa and Turkey have all crashed to multi-year lows as investors flee emerging markets and commodity prices crumble.

Robotics and Artificial Intelligence

Some of the most valuable research I’ve found so far on the job and societal impacts of robotics comes from a survey of experts conducted by the Pew Research Internet Project AI, Robotics, and the Future of Jobs,

Some 1,896 experts responded to the following question:

The economic impact of robotic advances and AI—Self-driving cars, intelligent digital agents that can act for you, and robots are advancing rapidly. Will networked, automated, artificial intelligence (AI) applications and robotic devices have displaced more jobs than they have created by 2025?

Half of these experts (48%) envision a future in which robots and digital agents have displaced significant numbers of both blue- and white-collar workers—with many expressing concern that this will lead to vast increases in income inequality, masses of people who are effectively unemployable, and breakdowns in the social order.

The other half of the experts who responded to this survey (52%) expect that technology will not displace more jobs than it creates by 2025. To be sure, this group anticipates that many jobs currently performed by humans will be substantially taken over by robots or digital agents by 2025. But they have faith that human ingenuity will create new jobs, industries, and ways to make a living, just as it has been doing since the dawn of the Industrial Revolution.

Read this – the comments on both sides of this important question are trenchant, important.

The next most useful research comes from a 2011 publication of Brian Arthur in the McKinsey Quarterly The second economy – which is the part of the economy where machines transact just with other machines.

Something deep is going on with information technology, something that goes well beyond the use of computers, social media, and commerce on the Internet. Business processes that once took place among human beings are now being executed electronically. They are taking place in an unseen domain that is strictly digital. On the surface, this shift doesn’t seem particularly consequential—it’s almost something we take for granted. But I believe it is causing a revolution no less important and dramatic than that of the railroads. It is quietly creating a second economy, a digital one.

Twenty years ago, if you went into an airport you would walk up to a counter and present paper tickets to a human being. That person would register you on a computer, notify the flight you’d arrived, and check your luggage in. All this was done by humans. Today, you walk into an airport and look for a machine. You put in a frequent-flier card or credit card, and it takes just three or four seconds to get back a boarding pass, receipt, and luggage tag. What interests me is what happens in those three or four seconds. The moment the card goes in, you are starting a huge conversation conducted entirely among machines. Once your name is recognized, computers are checking your flight status with the airlines, your past travel history, your name with the TSA (and possibly also with the National Security Agency). They are checking your seat choice, your frequent-flier status, and your access to lounges. This unseen, underground conversation is happening among multiple servers talking to other servers, talking to satellites that are talking to computers (possibly in London, where you’re going), and checking with passport control, with foreign immigration, with ongoing connecting flights. And to make sure the aircraft’s weight distribution is fine, the machines are also starting to adjust the passenger count and seating according to whether the fuselage is loaded more heavily at the front or back.

These large and fairly complicated conversations that you’ve triggered occur entirely among things remotely talking to other things: servers, switches, routers, and other Internet and telecommunications devices, updating and shuttling information back and forth. All of this occurs in the few seconds it takes to get your boarding pass back. And even after that happens, if you could see these conversations as flashing lights, they’d still be flashing all over the country for some time, perhaps talking to the flight controllers—starting to say that the flight’s getting ready for departure and to prepare for that…

If I were to look for adjectives to describe this second economy, I’d say it is vast, silent, connected, unseen, and autonomous (meaning that human beings may design it but are not directly involved in running it). It is remotely executing and global, always on, and endlessly configurable. It is concurrent—a great computer expression—which means that everything happens in parallel. It is self-configuring, meaning it constantly reconfigures itself on the fly, and increasingly it is also self-organizing, self-architecting, and self-healing…

If I were to look for adjectives to describe this second economy, I’d say it is vast, silent, connected, unseen, and autonomous (meaning that human beings may design it but are not directly involved in running it). It is remotely executing and global, always on, and endlessly configurable. It is concurrent—a great computer expression—which means that everything happens in parallel. It is self-configuring, meaning it constantly reconfigures itself on the fly, and increasingly it is also self-organizing, self-architecting, and self-healing

I’m interested in how to measure the value of services produced in this “second economy.”

Finally, China’s adoption of robotics seems to signal something – as in this piece about a totally automatic factor for cell phone parts –

China sets up first unmanned factory; all processes are operated by robots

At the workshop of Changying Precision Technology Company in Dongguan, known as the “world factory”, which manufactures cell phone modules, 60 robot arms at 10 production lines polish the modules day .. The technical staff just sits at the computer and monitors through a central control system… In the plant, all the processes are operated by computer- controlled robots, computer numerical control machining equipment, unmanned transport trucks and automated warehouse equipment.

Video Friday on Steroids

Here is a list of the URL’s for all the YouTube and other videos shown on this blog from January 2014 through May of this year. I encourage you to shop this list, clicking on the links. There’s a lot of good stuff, including several  instructional videos on machine learning and other technical topics, a series on robotics, and several videos on climate and climate change.

January 2014

The Polar Vortex Explained in Two Minutes


NASA – Six Decades of a Warming Earth


“CHASING ICE” captures largest video calving of glacier


Machine Learning and Econometrics


Can Crime Prediction Software Stop Criminals?


Analytics 2013 – Day 1


The birth of a salesman


Economies Improve


Kaggle – Energy Applications for Machine Learning


2014 Outlook with Jan Hatzius


Nassim Taleb Lectures at the NSF


Vernon Smith – Experimental Markets




Forecast Pro – Quick Tour


February 2014

Stephen Wolfram’s Introduction to the Wolfram Language




Econometrics – Quantile Regression


Quantile Regression Example


Brooklyn Grange – A New York Growing Season


Getting in Shape for the Sport of Data Science


Machine Learning – Decision Trees


Machine Learning – Random Forests


Machine Learning – Random Forecasts Applications


Malcolm Gladwell on the 10,000 Hour Rule


Sornette Talk


Head of India Central Bank Interview


March 2014

David Stockman


Partial Least Squares Regression


April 2014

Thomas Piketty on Economic Inequality


Bonobo builds a fire and tastes marshmellows


Future Technology


May 2014

Ray Kurzweil: The Coming Singularity


Paul Root Wolpe: Kurzweil Critique


The Future of Robotics and Artificial Intelligence


Car Factory – KIA Sportage Assembly Line


10 Most Popular Applications for Robots


Predator Drones


The Future of Robotic Warfare


Bionic Kangaroo


Ping Pong Playing Robot


Baxter, the Industrial Robot




Robotics – the Present, the Future

A picture is worth one thousand words. Here are several videos, mostly from Youtube, discussing robotics and artificial intelligence (AI) and showing present and future capabilities. The videos fall in five areas – concepts with Andrew Ng, Industrial Robots and their primary uses, Military Robotics, including a presentation on predator drones, and some state-of-the-art innovations in robotics which mimic the human approach to a degree.

Andrew Ng  – The Future of Robotics and Artificial Intelligence

Car Factory – Kia Sportage factory production line

ABB Robotics – 10 most popular applications for robots

Predator Drones

Innovators: The Future of Robotic Warfare

Bionic kangaroo

The Duel: Timo Boll vs. KUKA Robot

Jobs and the Next Wave of Computerization

A duo of researchers from Oxford University (Frey and Osborne) made a splash with their analysis of employment and computerization in the US (English spelling). Their research, released September of last year, projects that –

47 percent of total US employment is in the high risk category, meaning that associated occupations are potentially automatable over some unspecified number of years, perhaps a decade or two..

Based on US Bureau of Labor Statistics (BLS) classifications from O*NET Online, their model predicts that most workers in transportation and logistics occupations, together with the bulk of office and administrative support workers, and labour in production occupations, are at risk.

This research deserves attention, if for no other reason than masterful discussions of the impact of technology on employment and many specific examples of new areas for computerization and automation.

For example, I did not know,

Oncologists at Memorial Sloan-Kettering Cancer Center are, for example, using IBM’s Watson computer to provide chronic care and cancer treatment diagnostics. Knowledge from 600,000 medical evidence reports, 1.5 million patient records and clinical trials, and two million pages of text from medical journals, are used for benchmarking and pattern recognition purposes. This allows the computer to compare each patient’s individual symptoms, genetics, family and medication history, etc., to diagnose and develop a treatment plan with the highest probability of success..

There are also specifics of computerized condition monitoring and novelty detection -substituting for closed-circuit TV operators, workers examining equipment defects, and clinical staff in intensive care units.

A followup Atlantic Monthly article – What Jobs Will the Robots Take? – writes,

We might be on the edge of a breakthrough moment in robotics and artificial intelligence. Although the past 30 years have hollowed out the middle, high- and low-skill jobs have actually increased, as if protected from the invading armies of robots by their own moats. Higher-skill workers have been protected by a kind of social-intelligence moat. Computers are historically good at executing routines, but they’re bad at finding patterns, communicating with people, and making decisions, which is what managers are paid to do. This is why some people think managers are, for the moment, one of the largest categories immune to the rushing wave of AI.

Meanwhile, lower-skill workers have been protected by the Moravec moat. Hans Moravec was a futurist who pointed out that machine technology mimicked a savant infant: Machines could do long math equations instantly and beat anybody in chess, but they can’t answer a simple question or walk up a flight of stairs. As a result, menial work done by people without much education (like home health care workers, or fast-food attendants) have been spared, too.

What Frey and Osborne at Oxford suggest is an inflection point, where machine learning (ML) and what they call mobile robotics (MR) have advanced to the point where new areas for applications will open up – including a lot of menial, service tasks that were not sufficiently routinized for the first wave.

In addition, artificial intelligence (AI) and Big Data algorithms are prying open up areas formerly dominated by intellectual workers.

The Atlantic Monthly article cited above has an interesting graphic –

jobsautomationSo at the top of this chart are the jobs which are at 100 percent risk of being automated, while at the bottom are jobs which probably will never be automated (although I do think counseling can be done to a certain degree by AI applications).

The Final Frontier

This blog focuses on many of the relevant techniques in machine learning – basically unsupervised learning of patterns – which in the future will change everything.

Driverless cars are the wow example, of course.

Bottlenecks to moving further up the curve of computerization are highlighted in the following table from the Oxford U report.


As far as dexterity and flexibility goes, Baxter shows great promise, as the following YouTube from his innovators illustrates.

There also are some wonderful examples of apparent creativity by computers or automatic systems, which I plan to detail in a future post.

Frey and Osborn, reflecting on their research in a 2014 discussion, conclude

So, if a computer can drive better than you, respond to requests as well as you and track down information better than you, what tasks will be left for labour? Our research suggests that human social intelligence and creativity are the domains were labour will still have a comparative advantage. Not least, because these are domains where computers complement our abilities rather than substitute for them. This is because creativity and social intelligence is embedded in human values, meaning that computers would not only have to become better, but also increasingly human, to substitute for labour performing such work.

Our findings thus imply that as technology races ahead, low-skill workers will need to reallocate to tasks that are non-susceptible to computerisation – i.e., tasks requiring creative and social intelligence. For workers to win the race, however, they will have to acquire creative and social skills. Development strategies thus ought to leverage the complementarity between computer capital and creativity by helping workers transition into new work, involving working with computers and creative and social ways.

Specifically, we recommend investing in transferable computer-related skills that are not particular to specific businesses or industries. Examples of such skills are computer programming and statistical modeling. These skills are used in a wide range of industries and occupations, spanning from the financial sector, to business services and ICT.

Implications For Business Forecasting

People specializing in forecasting for enterprise level business have some responsibility to “get ahead of the curve” – conceptually, at least.

Not everybody feels comfortable doing this, I realize.

However, I’m coming to the realization that these discussions of how many jobs are susceptible to “automation” or whatever you want to call it (not to mention jobs at risk for “offshoring”) – these discussions are really kind of the canary in the coal mine.

Something is definitely going on here.

But what are the metrics? Can you backdate the analysis Frey and Osborne offer, for example, to account for the coupling of productivity growth and slower employment gains since the last recession?

Getting a handle on this dynamic in the US, Europe, and even China has huge implications for marketing, and, indeed, social control.