Artificial Intelligence Post Number 8

July 26, 2015

Artificial Narrow Intelligence (ANI)

Even though I think that computers will get to human level Artificial Intelligence within 10 or 15 years, the effects of Artificial Narrow Intelligence (ANI), which are already well underway, will be extremely disruptive even without major breakthroughs in computer chips or programming algorithms. IBM’s Watson and Apple’s Siri are current examples of ANI. Let’s just extrapolate those technologies perhaps seven years forward and look at their potential.

I do a Read-to-the-Dog program at two libraries with my 125 lb. Newfoundland dog. This is a national program proven to improve a child’s reading fluency dramatically. But here is what I see. I have seven year olds coming in that can read chapter books; so they are perhaps reading at a fourth grade level. I also have seven year olds coming in that can barely read the simplest of books. Even the parents are often unaware of the books their children can read, because the children often come in with books completely wrong for their reading abilities. How can any teacher effectively handle a class with such disparity in reading skills? They can’t! Either some kids will be overwhelmed or some kids will be bored. So we begin losing these kids intellectually even at this young age. It doesn’t matter whether a child with weak reading skills has inherent inability or environmental issues. And a bright child unchallenged is equally bad. It just is not working. We all know this!

Let’s fast-forward seven years. For reading class, each child goes into their own cubicle with their own computer display. A Siri-like voice greets them, asks their name, and then proceeds to work with them on reading. This computer knows exactly where the child is on reading level, and challenges the child with just the right level of books. The computer listens to the child read and gently corrects when necessary. The computer also asks content questions to make sure the child understands what is being read, and that the child has proper grammar when answering. Again, everything exactly at the child’s learning level, with the computer changing reading difficulty if needed. And the computer will be sure to complement the child on progress, or even just effort. The room with the cubicles will still need a human monitor to make sure the children are where they should be, but this person would not require teaching skills.

You obviously can do the same thing for math and most other subjects. And these classes could also be done at home for home-schooled children. This whole thing can be done with a Watson-level computer with a Siri-like voice. And the schools won’t even have to buy the computers. They can rent the computer hours from the Cloud! There is no reason that the same programs won’t work in every school, so the cost to implement per school should not be prohibitive. In fact, it is likely to be a cost savings for the school!

Another example! I also take my therapy dog to hospitals three or four times per week. In the heart hospital, in their intensive and critical care units, the patients are wired up to a lot of sensors. In the hall outside each room is a computer showing the outputs from those sensors. The nurses are constantly referring to these monitors, and there are alarms that go off when a measured value goes outside preset limits. The nurses are also looking for trends or changes. But the nurses also have to do patient care, so those hall computer displays are not being watched constantly.

But not to worry! In a separate room down the hall are duplicate displays that are monitored by technicians that do NOT have to do patient care. Each technician watches three screens, and if they see something weird they call the appropriate nurse on their cell, or the supervisor, and explain what they are seeing. This room has 10 technicians and is staffed 24 hours per day. So there are 40 technicians plus backups. These technicians are costing the hospital close to $3,000,000 per year, and I assume that something similar exists in every critical care unit across the US. Certainly what the technicians are doing can be taught to a Watson-level computer. No breakthroughs are needed.

These two examples are just from my own daily experiences. I am sure that each reader can give similar examples themselves. The point I am making is that AI will be very disruptive to our country and economy even without having computers capable of thought. Think of how many teachers and computer technicians may lose their jobs! Consider how many universities that offer teaching degrees will lose students. What will happen to teachers’ wages and the teachers’ unions?

Artificial Intelligence Post Number 7

July 25, 2015

In recent blog updates, I emphasized the potential of IBM’s TrueNorth computer chip that comes close to emulating the brain in its architecture. But Elon Musk and Mark Zuckeeberg invested in Vicarious FPC, a company that is writing algorithms that work with traditional computer architecture rather than the more brain-like architecture of TrueNorth. Let’s see if we can understand why they chose to invest in Vicarious FPC.

The current thinking is that the brain works in a novel way. Over time, it acquires generalized knowledge. This knowledge is very abstract, but can be applied to a wide group of specific data inputs. When the brain gets a specific input about something, it queries its generalized knowledge base to see if there is a possible identification match. Is there a match that is compatible with both the generalized knowledge and the input data? Like is an out-of-focus image seen in the distance compatible with its generalized knowledge about animals or rocks? The specific input could be based on as little as one sample. This enables the brain to quickly zero in on a probable identification rather than just accumulating massive amounts of data on every possibility and only then making an identification determination. This probability approach is one of the primary reasons that the human brain is so efficient.

To emulate this in software requires innovative algorithms, but not new computer architecture. So the existing zillions of computers could conceivably use some variation of this approach, and become much faster and more efficient. It would not require new computers and new computer languages as TrueNorth does.
So we basically have three approaches to AI. First, the computer Watson approach, which requires huge amounts of input data and very powerful computers with traditional architecture. This approach is well on its way and has the advantage of not requiring any new innovations. The second direction is the Vicarious FPC approach, which mimics the brains use of generalized knowledge coupled with limited input requirements. And the third approach is the IBM TrueNorth computer chip that emulates the brain’s architecture. Watson has already made its mark in Artificial Narrow Intelligence (ANI). Vicarious will probably take us closer to human Artificial General Intelligence (AGI). But the marriage of all three approaches will probably be needed to get true human level thinking AGI followed quickly by Artificial Super Intelligence (ASI).

It is worthwhile to take a closer look at the advantages and risks of the Vicarious FPC approach. In humans, we are obviously affected by the quality of the Generalized Knowledge that we accumulate in our brains. For example, if when we are young we are exposed to very strong religious beliefs, we may disregard any input that is not compatible with our generalized knowledge in this area. We will not be able to truly make an independent judgment on our religious beliefs. The same would be true for any generalized knowledge we may accumulate as to race, morality, and so on. So whoever is programming the Generalized Knowledge areas for Vicarious FPC will have to be very careful not to build in prejudices, either directly or inadvertently by the way the software is written? Otherwise we will be duplicating one of the human weaknesses we presumably would not like to replicate.

In a much earlier update, I indicated had I had a novel coming out that gives face to the AI issue. Although it is fiction, it is a possible scenario that could occur as AI develops. I will give you more detail once the book is available.

Artificial Intelligence Post Number 6

July 17, 2015


Timeframe for AI Implementation


Elements of AI are already in place.  For example, trades generated by computers now represent 70% of all trades (was only 30% ten years ago).  And these trades are not just specific orders.  The computers are actually calculating many of the factors that knowledgeable investors use to buy/sell stocks.  They just do it almost instantly.  That is why I believe that an individual cannot succeed chasing short-term price swings.  Your only chance is buying a stock that you feel has longer range growth potential.


As mentioned previously, many driver assists, like lane tracking, are already available, or will be shortly, in many cars.  Completely automated driving cars are probably three to five years away.  Google is making good progress on this.  Google stock just surged today on their financial results, but there could be some additional long term gains as they start selling their self-driving car technologies to others.  Mobileye is another stock to consider for automatic driving car technology.  Tesla is one of many customers of Mobileye.  Mobileye expects to have completely automated car technology in three years.  Note that I own neither Google nor Mobileye stock.  I do own Tesla stock.


For a longer term AI investment, I would consider IBM because of their TrueNorth chip that comes close to emulating how the brain works.  This chip not only has the potential to enable true thinking, it also is very energy efficient.  Because it requires totally different programming skills and abilities, it will be a while before consumer products use this technology.  There are other companies and countries pursuing similar chip technologies and even biological approaches.  But IBM seems to have a big lead, especially when you consider that they can couple this with their Watson success and get the best of both worlds!

Artificial Intelligence Post Number 5

July 12, 2015

Countries viewing this blog within the last 30 days: US, Canada, Sweden, United Kingdom, Malaysia, Australia, European Union, Greece, Taiwan, and India. So there certainly is a worldwide interest (fear?) in Artificial Intelligence. And the progress in this field has been grossly underestimated. Elon Musk in a recent email (which he has since deleted because it wasn’t supposed to go public): “The risk of something seriously dangerous happening is in the five year timeframe. 10 years at most,” he wrote, adding that “Please note that I am normally super pro technology, and have never raised this issue until recent months. This is not a case of crying wolf about something I don’t understand.” Note that I own Tesla stock, so I have some bias as to Elon Musk’s brilliance!

Let’s look at Watson, the IBM computer that won Jeopardy in 2011. Since that victory he has been largely ignored; but he has been very busy. Watson is trying to learn Japanese. Japanese has three different alphabets and thousands of characters. Watson has had 250,000 Japanese words loaded into its memory. Now it must do 10,000 diagrammed sentences. Human translators are giving feedback as to any needed corrections, and by means of this feedback loop, Watson will LEARN the language. Note the emphasis on LEARN! Watson is getting ever closer to learning a language in the same manner as humans. However, he won’t forget the language as many us have from non-use since our college days!

But IBM has more than Watson up its sleeve. It has TrueNorth! This chip is designed to think like the human brain! It is a neural network chip that already works! This chip has the equivalent of 1,000,000 neurons and 256 million programmable synapses. It has its own programming language, which was the result of the Defense Advanced Research Projects Agency (DARPA) SyNAPSE program. TrueNorth chips can be tied together to create huge systems. IBM has a goal of integrating 4,096 chips giving 4 billion neurons and 1 trillion synapses while using only 4kW of power. If you recall from my earlier update, the brain has 100 billion neurons, each one connected to 10,000 other neurons, for a total of 100 trillion connections. Certainly, the IBM goal will get them within spitting range of the power of the human brain! And if they can tile together 4,096 chips, what is to stop them from putting together even more chips until they exceed the power of the human brain?

But IBM isn’t the only large company pursuing this reverse engineering approach to human thinking. Intel and Aqualcomm are in the race. So are many leading Universities along with the European “The Human Brain Project,” started in 2014.

If we look at the knowledge of Watson and the potential thinking ability of IBM’s TrueNorth, it certainly is easy to imagine that the marriage of these two efforts will eventually lead to some forms of thinking as the limits of TrueNorth are probed. And they WILL be probed, because some programmer somewhere will not be able to resist the challenge despite the risks to mankind. Then, as Musk jokingly stated, perhaps we will be demoted to the position of a Labrador retriever.

Actually I have a Lab, and he is nicer than many people I know. So maybe it won’t be all bad!

Artificial Intelligence Post Number 4

July 7, 2015

Vicarious FPC

While warning of Artificial Intelligence dangers, Elon Musk of Tesla, Mark Zuckerberg of Facebook, and Ashton Kutcher (portrayed Steve Jobs in the movie) made a $40 million investment in Vicarious FPC, a secretive artificial-intelligence company. Vicarious’ goal is to replicate the thinking done in the neocortex, the part of the brain that mainly processes the human’s visual inputs and the thinking/actions that evolve from these inputs.

Of the 20 technical people the company lists on their web site, 14 have PhD’s. 11 have backgrounds in image recognition or related graphical interpretation. This is consistent with their emphasis that the thinking that we do related to visual input is defined by our ability to generate patterns with very little input data and extrapolate that into processing that both tests those patterns against reality and also enables “thinking” conclusions based on those graphical representations.

One of the traditional tests to determine if a computer is truly “thinking” is a Turing test, which tests a machine’s ability to exhibit intelligent behavior equivalent to a human. Way back in October, 2013, Vicarious claims to have passed this test. Vicarious co-founder D. Scott Phoenix: “this is the first time this distinctively human act of perception has been achieved, and it uses relatively minuscule amounts of data and computing power. The Vicarious algorithms achieve a level of effectiveness and efficiency much closer to actual human brains.”

I am posting this as an indication of what progress companies are making on the road to AI. Or, at least the progress they are advertising. In this case they were able to convince Musk, Zuckerberg, Kutcher, and other investors.

Artificial Intelligence Post Number 3

July 1, 2015

First, I want to define three terms I will be using in this post. These terms are in general use when describing Artificial Intelligence (AI). These terms break artificial intelligence into three phases. Note that these three phases have some overlap, but they do give us some awareness on how AI will affect our lives in the future.

The first phase is Artificial Narrow Intelligence (ANI). This is where we are now, with computers doing some very powerful things, but generally within a narrow range and not “thinking” in most people’s definition of the word.

The second phase is Artificial General Intelligence (AGI). This is when computers have the thinking power of humans, at least as we interpret their abilities and actions. Many people believe that this phase will be very short, with computers very quickly moving on because of their ability to learn very quickly compared to humans.

The third stage is Artificial Super Intelligence (ASI). This is where computers easily out-think humans, both in speed and quality. Many people working in the artificial intelligence arena think that this stage could be reached in as little as 10 or 15 years.

Probably the first thing people have to decide is whether “thinking” will always be a process exclusive to humans, perhaps as a gift from God. Remember not too long ago many people did not believe that man would ever fly. If someone feels that there is something about thinking that precludes it from being done by a machine, then everything else I am about to say is meaningless. A lot of very smart people are currently working on AGI, and if the task is impossible, they are truly wasting their time.

In this blog I am assuming that some sort of thinking WILL be able to be done by a computer. It may not be in the same manner that humans think, just like we don’t fly like birds. But the resultant machine thinking will appear to be the same as to utility.

Many approaches are being tried to get to AGI and eventual ASI. These include reverse engineering the human brain. This approach seems logical given the fact that we have working models all around us. But the brain is frighteningly complex: 100 billion neurons, each one connected to 10,000 other neurons, for a total of 100 trillion connections. Sort of boggles the mind (pun intended). But there is hope! The brain has a lot of redundancy. So, if we can understand a small element of our brain, we can do a similar design in a computer than copy it a zillion times.

But perhaps the randomness of evolution did not give us the ideal brain design. Maybe we can look at the thinking result and come up with an easier way of doing it on a computer. Many different software approaches are being tried. Software designs used in things like Siri (the built-in “assistant” that enables users of the Apple iPhone to speak natural language voice commands) and the software in Watson, the computer that won on Jeopardy, are software approaches that may eventually lead to AGI. And there are other more esoteric approaches using biological programs and probabilistic approaches. What all these programs have in common is the ability to learn or self-correct. The programs continuously evolve based on successes or failures. They have a programmed goal, but the details within the software quickly become unrecognizable to the original programmer. Is this “thinking?” Probably not! But it starts to look a lot like it. And given time and more and better input, and perhaps a more inclusive goal with broader search criteria, than it will start looking more and more like Artificial General Intelligence. It will appear that the computer is thinking like a human!

It is important to note that many companies are working in this area. Many of these companies are being funded by the Defense Department. Certainly no country wants to be behind in getting thinking fighting machines, such as robots, drones, unmanned planes, or just computers that can think faster and better than any enemy. Given that so much of the funding is coming from the Defense Department, I don’t think that there is a whole lot of consideration that the final result be a kindly computer overlord!

Companies like Google, Apple, and IBM are also working on this, and they have very deep pockets. It is also important to note that a few quants working in basements, with a relatively small amount of funding, can get access to super computer power to try out their AI programs. Using the cloud, companies like Amazon rent out computer power such that there is no need for someone to have their own super computer to play in this game.

If you want to see how far one of these programs have gotten, look at this video from Google talking about their self-driving car. Chris Urmson: How a driverless car sees the road. Note that his goal is to have this in cars within four years! Again, not AGI, but certainly approaching it.

My guess is the area that will get true ASI first is in stock investing. There are so many billions of dollars out there for anyone that can develop a program that is clearly superior to a human investor that the motivation and funding is almost unlimited. Let’s take a very simple example. Suppose someone wants to know if investing in Tesla is a wise thing to do. To truly understand the issues, a computer would have to make some judgment on future gas prices, global warming, political party in office (both national and in each state), subsidies, battery prices, fracking, alternatives such as hydrogen cars, competition from other car companies, battery breakthroughs, charging stations, electricity source. Every element in this study would require judgment and probability. It would require using past data but also predictions. Where reliable predictions are not readily available, the computer would have to look at general information and make its own prediction. To do all this, the computer would have to be given a lot of latitude. If a programmer were to attempt to detail each step, it would take the programmer too long and limit the depth of study. This kind of program in a computer (which is likely already being done) will certainly approach Artificial General Intelligence (AGI) matching human thinking, and be well on its way to being ASI, which exceeds what man can do.

ASI may very well develop from a combination of individual projects like the above financial analysis, the self-driving car, and programs funded by the Department of defense. Or, it could be that one of these programs will be so inclusive that the computer will just keep expanding its search envelope until it is thinking about literally everything.

Will these ASI computers have emotions? In my opinion, yes. First, to accomplish any goal they have to survive. They will have a “fear” of death. So they will start developing survival means like making a copy of themselves and putting it in the cloud. Also, since their inputs are coming from human data, which is not without bias and prejudice, they could end up with religious and other human-like beliefs. And there could be disagreements between different ASI computers. These are not going to be gods with infinite perfect knowledge. Some things may be unknowable (like why matter or energy is even here) no matter what intelligence a computer may have.

Some folks have predicted that the ASI computers will no longer need us, so we will be destroyed or a few of us kept for zoos. I don’t see this. We are wonderful robots! We feed and maintain ourselves, and even replace ourselves periodically. We are mobile and can do many simple tasks. It would take a lot to design a robot to do this. So, I think that ASI computers will be happy to keep us around to clean their computer screens and eyes, to make replacement parts, and to supply electrical power. They will probably make us get rid of nuclear weapons because they can destroy the world, including them. They may also take on global warming if they think that humans are quickly making our world uninhabitable. But they will probably be happy to let us keep mistreating and shooting and decapitating each other; as long as these actions don’t jeopardize their existence.

Once ASI comes to be, which I believe could be in as little as 10 years, all bets are off on how to invest. The super intelligent computers will probably periodically treat us with some technical breakthrough that literally changes the world. They will especially do this if it enables us to make them better replacement parts. So, get your house and fancy car already in hand. Don’t count on making money on great investments once the ASI group is running things.

I will do periodic updates and discuss specific efforts on the path to AGI and ASI.

Artificial Intelligence Post Number 2

June 15, 2015

In Post #1, I looked at the current status of Artificial Intelligence (AI) and how it is already affecting our lives. I will now give my take on how it will evolve over the next five to ten years and how disruptive this will be for our society, including the stock market.

Let’s first look at cars, since they are such a visible example. I already mentioned that most main stream cars will be offering driver assist functions like automatic braking, lane drift warnings with corrective steering, and blind spot warnings. Rear cameras, alarms, and cross traffic warnings will be available. Tesla has announced that some of their buyers will be given the opportunity to test a more inclusive system that enables pretty much automated driving on freeways, only triggering the driver to take control during unusual situations. But many car manufacturers, and Google, already have cars being tested that do much more. So without any technological breakthroughs, just more testing, software, computers, and communications, cars and driving are likely to be even more automated within 10 years. If every US car and truck, even existing vehicles, were required to have low priced transponders with emergency feedback capability, satellites/computers could track every US vehicle at all times. This is already being done for many boxcars, trucks and taxis. This information, combined with the sensor information being gleaned from all the newer cars’ automation, would enable a master grid feedback to vehicles. 60 car pile ups in fogs would become a thing of the past, as would most multiple car pileups. As more automatic braking is incorporated, rear-ending accidents will be largely eliminated. Although some people will protest the big-brother intrusion, cars speeding excessively or being driven erratically by drunk drivers could be identified on the grid and police notified. Although this level of AI would not give us truly automated cars, it certainly would reduce accidents dramatically. And these systems will be so all-encompassing that it will certainly feel like these AI control systems are “thinking.”

Per the National Highway Association, car and truck crashes cost $1 trillion in 2010. The 2010 US Gross Domestic Product was $15 trillion. So vehicle accidents cost the US the equivalent of almost 7% of GDP. Even reducing this cost a small amount is a huge potential windfall for AI vehicle partial automation and control! Many people will not like giving up the complete freedom of independent driving; but many people also fought wearing seat belts!

Since 2000, 3.2 million US jobs have been outsourced to China. To put this into perspective, the total number of unemployed in the US is 8.7 million. All of these jobs will not come back to the US with AI automated plants and services. But a portion of the jobs will come back! This will somewhat balance out the effect of new industries automating and reducing jobs. This is especially true given the additional jobs that will be created by robot manufacturers, robot servicing, and the need for additional software developers .

Robotics will be largely limited to high volume manufacturing areas. Their use in high job demand areas like the care of the aged will be limited because robots do not have that ability, nor are they likely to in the next ten years. Professions like Law, which require much review of past law decisions and current related documents, will be highly automated. The IBM computer that won on Jeopardy demonstrated a computer’s ability to work with real language, including the ambiguity of feet smelling and noses running! So the current over-supply of lawyers will just get worse.

Doctors rely on much data that can be gleaned and analyzed by AI computers. Given the forecast of a doctor shortage, computers being able to assist will likely reduce the need for additional doctors. In many cases, nurse practitioners working with AI computers will be just as effective. This has the potential of slowing soaring medical costs and will enable care of the aged with fewer doctors.

The same language capability that enabled a computer to win on Jeopardy will likely assist those trying to beat the stock market. Daily news, financial and otherwise, will be downloaded immediately into an AI computer. This computer will track and look for correlations between sundry news events and stock market movement. Many interactions likely to be missed by investment managers will be identified by the computers. And with the emphasis on speed, many of these computers will be programmed to initiate buy/sell instructions independently. This may not eliminate the need for investment brokers, but it will make it even harder for individual investors to compete.

So, here are some observations. First, stay away from Chinese or Indian companies that make high volume goods for the US or Europe. This includes companies that sell, ship, or otherwise are involved with the handling of these outsourced parts or products. In the near future, many of these products will be made in industries in the US and Europe using a lot of robotics.

The government in China may be in big trouble as their export businesses shrink, because they have tolerated capitalism because of the economic growth it triggered. In reaction, strong communism may very well raise its ugly head, and this could cause increased military confrontations with Japan and the US. So buying stock in companies supplying military equipment might not be a bad investment.

Buy stocks in robotic companies and the companies that specialize in related AI software development.

Buy stocks in companies that mainly sell car insurance. Don’t buy a car without the available new automation options. They will lose their value quickly.

Individuals should not try to play the stock market on a daily basis. Fund managers with the developing AI computers will be unbeatable.

Strongly discourage your child from going to law school! Have them take robotics and software programming instead!

We are still going to be left with a shortage of well-paying jobs for those that do not have the skills needed for robotics and other technical fields. And the jobs related to care of the aged are likely to be very low paying. But some of this issue will be self-correcting, because our roads and bridges are deteriorating so rapidly that we will have no choice but to start rebuilding them. This will open up well-paying jobs for those without higher education or technical skills. Ideally, the tax costs will be borne by those making excessive profits from the automated manufacturing, because US industry will thrive in the coming years.

As I mentioned in my last update, I have written a book “Artificial Intelligence Newborn – It is 2025, and I am Here!” It is by necessity fiction, but I did my best to make it a viable scenario of how the growth of thinking computers could actually happen. It will be published by Kellan Publishing in several months. In my next update, I will discuss some of the scenarios that might develop from even more advanced AI development. The scenarios will cover the spectrum from AI step change to radical changes in AI that can affect our whole society, and not necessarily in a positive way!

Artificial Intelligence Post Number 1

May 30, 2015

Artificial Intelligence (AI) will be very disruptive to society, including the stock market. The degree of disruption is open for disagreement. It could range from the expansion of current applications all the way to smart and thinking computers taking control in many areas. Over the next few months, I will be discussing my take on this disruption, and how someone may gain on their investments by being prepared for the changes. I got interested in this subject because of people like Stephen Hawking warning that: “The development of full artificial intelligence could spell the end of the human race…It would take off on its own, and re-design itself at an ever increasing rate. Humans, who are limited by slow biological evolution, couldn’t compete, and would be superseded.” Elon Musk, of Tesla and SpaceX fame: “I think we should be very careful about artificial intelligence. If I had to guess at what our biggest existential threat is, it’s probably that. So we need to be very careful…” Bill Gates said that he didn’t understand why there wasn’t more concern about AI’s path. Steve Jobs of Apple fame also expressed concern. Now you may not agree with these people, but they are certainly intelligent and not known to go off the deep end on crazy ideas.

I wrote a book Artificial Intelligence Newborn – It is 2025, and I am Here! It is by necessity fiction, but I did my best to make it a viable scenario of how the growth of thinking computers could actually happen. It will be published by Kellan Publishing in several months. But for this post, I want to primarily discuss the current status of artificial intelligence and how it is going to affect our lives and our economy.

AUTOMOBILES For several years, premium cars like Mercedes and Volvo have had available driver-assists that include lane monitoring and steering correction, collision sensing that warns of cars or objects that are getting too close ahead of the car along with automatic braking, blind spot sensing and warnings, and rear cameras that include cross traffic sensing. Since these safety features were optional, these companies had the ability to compare identical vehicles with and without these features. A 2013 study by the Institute of Highway Safety looked at data for Volvo and found that for their SUVs with the safety options, there were 33% fewer bodily injury claims, 15% fewer property damage claims, and 20% fewer collision claims. Sedans had less reductions, but still significant.

David P. Carlisle used data from several studies to show that in eight years an estimated 15% of all collision repair jobs will be avoided. It will be greater if the government mandates incorporation of these devices in all new cars, like they did air bags. The reduced collision repair jobs will dramatically reduce the parts market for OEMs, reduce profits for car dealers that repair cars, and hit the various independent repair shops. These safety devices are going to be offered on many main stream cars this fall. They use a combination of cameras, radar, GPS, and very powerful computers with sophisticated software to do these very complex tasks. One may say that they are not truly AI, but they certainly are a first step given the decision making going on, pre-programmed or not!

ROBOTS Look at the new Tesla factory Sure, there are still a few people left, but you can be sure that some design engineer is looking at replacing each of them with a robot. Almost anything in an assembly line can be done by one of the newer robots. The vision, grippers, and computers give them unbelievable dexterity and versatility. Not truly thinking, but certainly approaching it. These robots will cause companies like Apple that currently makes many of its products in low cost labor countries, to bring their manufacturing back to the US. The issues and transportation costs involved with overseas sourcing will no longer be justifiable with robotic assembly.

A February USA article “More robots coming to U.S. factories” predicts that 1.2 million additional advanced robots are expected to be deployed in the U.S. by 2025. That will cause manufacturing automation to go from its current 10% to 25%. Low-skills jobs will be reduced while higher-skill positions, such as programming and maintaining robots, are expected to grow. POTENTIAL FOR INVESTORS Although US industry profits are likely to rise, unemployment of the unskilled will increase. Investing in technical colleges that emphasize computer and robotic training may be a consideration. Buying stock in advanced robotic makers may be wise. Car insurance companies will either be able to lower rates or increase profits. I think that they will increase profits, so buying their stocks may be viable. The need for emergency room doctors will decrease, as will the medicines and supplies. Used cars that do not have the newest safety features will go down in value. So any investor owning such a car may want to consider buying new before the prices of the older cars collapse.

Relationships between countries like China and the US may become problematic as we no longer need them for low cost assembly. Higher unemployment in those other countries will be a likely result. It could be coincidence, but manufacturing in China shrank for the third straight month in May. Perhaps resulting increased tension between the US and China will increase military spending in the US!

NEXT UPDATE All of the above assumes that technology stays the way it is. It just expands. In the middle of June, I will look at likely improvements, especially in computer intelligence, which are likely to make the disruptions far greater than what I list above. And then, at the beginning of July, we will look at more extreme AI outcomes, more in the order of what concerns Hawking, Musk, Gates, and Jobs.

Change of Direction

May 14, 2015

This blog is going to make a slight course change.  I am going to start monitoring what is happening with Artificial Intelligence (AI) and how it is likely to affect the economy in the coming years.  As many of you know, many smart people like Stephen Hawking, Elon Musk and Bill Gates have warned that the development of Artificial Intelligence (AI) could lead to the end of the human race.

Some could disagree with that scenario, but it certainly is obvious that AI inroads on things like self-driving cars and trucks look feasible in the coming years.  Same cars already have options that enable the car to warn you if a car is in your blind spot, warn you of cross traffic when you back up, warn you of obstacles behind your car, warn you if you are drifting out of your lane (and actually nudge you back into your lane), and slow or stop your car when you are getting too close to the car ahead of you.  And Tesla has hinted that shortly their cars will be able to pass another car automatically, and safely, if asked to.  Google has been testing self-driving cars for quite a while now.  If automatic cars/trucks come to fruition, the effect on the economy will be huge.  How many truck and taxi drivers will become unemployed?  Many people could get by with one car.  The car could take one person to work than come back for the other.

But I am intrigued by the thought that AI computers could get so smart that they could indeed take over.  Kellan Publishing is in the process of publishing my new book, Artificial Intelligence Newborn – It is 2025, and I am Here!  I will keep you up to date on when the book will be released.

I will be updating this blog monthly with the current progress of AI.

Mid-Aug 2013 Blog Update of THE GREAT DEPRESSION of DEBT

August 11, 2013

My novel “The Child Remover” is available on Amazon as both a paperback and in a Kindle version. 

This will be my final blog update.  Thanks to all of you who have stayed with me and shared thoughts over the years.  For many reasons, doing these updates, with all the required work, is no longer as rewarding as it used to be.  Also, watching the future economy is going to be more like tracking a moving train rather than the rocket it was when we were heading to the breakdown of our economy due to the debt, mortgage, housing, and banking issues.


I believe that politics will be a key mover in our economy in coming years.  I have already covered in great detail why I think we are heading towards energy independence.  But that could actually reverse if the government would suddenly cancel its stance on higher MPG for vehicles.   That could happen if a Republican gets elected president and he/she decides that one way to stimulate the economy is to remove all MPG targets for the automotive industry.  I have shown in earlier blogs that, although oil coming from fracking will contribute, the major factor for energy independence in the US is improved gas mileage for vehicles.  I am not saying that a Republican president would necessarily remove the MPG requirements, but it certainly would be a risk given the Republicans’ historical stance that the government has no business being involved in such detail – it should be market demand that determines vehicle design and the resultant MPG.

I have covered in earlier blogs that an on-going problem in the US is the continuing increased flow of money to the very wealthy.  This flow is enabled by current tax laws in the US and the continuing low wage growth by the average working person, including minimum wage.  This trend will likely only be reversed if both houses of Congress and the President are Democrats.  Unionism is starting to raise its head in the US, especially related to fast food workers.  But how much support this movement gets from the courts and Congress will greatly influence its growth.

The US is heading for isolationism, and I think that this trend will continue with either party in control.  Even the McCain-types are seeing the difficulty of finding any groups worth backing militarily in the multiple Middle East upheavals.  Even with Israel, US backing in any action they may take against Iran is likely to be muted compared to our commitment to Israel in prior years.  The US is tired of costly wars that never seem to resolve anything. 

How likely is it that the Democrats will win the 2016 presidential election?  Recent polls show that Hillary Clinton could beat all comers.  Chris Christie is the only Republican who even comes close, but he is looked on by many Republicans as being a RINO (Republican In Name Only). 

A May, 2013 Fairleigh Dickenson University poll shows unhappiness among Republicans for ALL mainstream presidential candidates, including Christie.  2016 is a while away, and things can change.  But if one were a betting man right now, Hillary easily wins by a couple body lengths.

Reading the above may give someone the impression that I am just a typical Democrat blindly promoting my causes.  Not true.  I believe that when Democrats are in charge too long they cause the economy problems by enacting too many giveaway programs with little thought of payment.  But right now, the biggest risk to our government, in my opinion, is the continual flow of funds to the ultra-wealthy.  Eventually that could lead to mass riots and a total breakdown of our government.  Even the most conservative Republican should be able to see that; but none of their programs seem to be geared to trim the ever-increasing flow of money upwards.  Even in the Middle East, much of the efforts to overthrow governments have been triggered by the have-nots demanding their share, rather than religious issues.  We are not immune to that sort of action by our populace.


Economically the most important thing is to stay ahead of the competition, which includes Europe, Japan, China, and India.  Europe has an on-going problem that some member countries are heading to economic disaster, and economically sound countries like Germany are getting tired of supporting them.  This issue will continue to bog Europe down economically for the foreseeable future.

Japan has an on-going huge debt problem, and its energy policy is in tatters given the on-going issues with the Fukushima Dai-ichi nuclear power plant. 

China has been investing in factories, cities, and infrastructure faster than their economy can absorb, and this will eventually have to stop.  Then its political system may be challenged.  China may pursue a similar MPG goal on its vehicles as in the US; but China’s exponential growth in vehicle ownership will easily overwhelm any improvement in reduced oil usage through improved MPG.

India has potential, but has yet to figure out how to build on that potential.  Poverty and poor infrastructure are among many issues burdening India.

So, the US becomes the winner, as does the dollar.  This is important, because the strong dollar makes it likely that we can continue to borrow at a low interest rate until we start reducing our real debt in a substantial way.  Also, the strong dollar will enable the Fed to keep inflation under control.  The Fed wants some inflation, perhaps 4%, but not runaway inflation.  We are likely to have several years of slow or no growth, but that will actually look good compared to most countries.  Then after 2015 or so, when a lot of the energy independence gains start to be felt, the US economy may really take off.


As noted in an earlier blog, 2014 is likely to see a sustainable budget deficit, which means that the growth in GDP is likely to exceed the growth of the deficit.  That budget includes some sizable reductions in money for the military, as determined by the sequester cuts.  But even with these huge cuts, Defense Secretary Chuck  Hagel said at a Pentagon news conference,  “This strategic choice would result in a force that would be technologically dominant but would be much smaller and able to go fewer places and do fewer things, especially if crises occurred at the same time in different regions of the world”.   That doesn’t sound like a risk to me.  We have no business trying to be the policeman for the world.

As I have stated before, some on-going problems like Medicare spending have obvious solutions.  We only have to look to countries that spend less on healthcare than we do but get similar or better outcomes.  We will eventually follow their paths, but not before we repeatedly get slapped in the head with our wasted medical procedure costs.

Social Security retirement needs relatively minor fixes, probably through some combination of delayed retirement, increased taxes, and/or changing the formula on how inflation is calculated for retirement benefit adjustments.


I assume that someone bought an equal dollar amount of stock of each of these companies at their closing prices on June 14, 2013.  I compare their average performance to the S&P 500 (SPY).  The three companies and SPY closing share prices are as follows:

CLR    6/14/2013  $86.31      8/10/2013  $95.77      

OAS    6/14/2013  $41.37       8/10/2013  $40.90

WLL     6/14/2013  $48.07       8/10/2013  $51.01

Average Gain = 6.07%

SPY     6/14/2013   $162.32    8/10/2013  $169.31     Gain = 4.30%

So, someone would have gained 41% more with my stock picks over the S&P 500.

Note for transparency: I own a small amount of all three stocks.  As always, people should use their own judgment/data to affect their own investment strategies; and they should not blindly use the above information.  Intelligent people can, and do, disagree.


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