Last time we talked about the weird quantum universe, where particles can be in more than one state at the same time and can be entangled with another particle at great distances. What does this have to do with computers?

Since their beginning in the late 1930s, all digital computers are based on binary digits (bits), which can have a value of zero or one. Early computers might have a few thousand bits in a box the size of a refrigerator. Your smart phone probably has more than 100 billion bits in a box that fits in your pocket. Digital computers work because the computer can tell a particular bit to be a zero or a one, and it will stay in that state until it is explicitly told to change. This is a good thing, and a bad thing. It is good because we can rely on the state of that bit. It is bad because it takes time to set the value of a bit, and later to look at it to see what that state is. Because of that, there are problems that would take computers millions of years to solve.

The quantum world is a little different. Niels Bohr who won the 1922 Nobel Prize in physics for his work in quantum theory famously said, “If quantum mechanics hasn’t profoundly shocked you, you haven’t understood it yet.”

Quantum computers use quantum bits, called qubits. Qubits are very small; they must be to have quantum effects. They can be individual atoms, photons, or electrons. Unlike a digital computer, each qubit can be in multiple states simultaneously. The effect of that is that a quantum computer with a single qubit could solve two simple problems at the same time, one with two qubits could solve four simultaneously, and one with ten qubits could solve over a thousand simple problems simultaneously. This is called parallelism. A 30-qubit quantum computer would be at least a thousand times faster than today’s conventional desktop computer.

To solve very complex problems, the digital world has created computers to take advantage of problems that can be solved using parallelism techniques. Computer companies have created computers with dozens to thousands of separate processors, each doing the same function across a large array of data. IBM’s Blue Gene is one example of a massively parallel supercomputer. SETI@home (Search for Extraterrestrial Intelligence) is an example of a distributed parallelism approach, often called grid computing, where 290,000 computers around the world can work on the same problem across the Internet.

Blue Gene cost $100 million to build. SETI takes advantage of idle time on lots of computers, so it hard to put a dollar cost on it. In ten years, it managed to cover only about 20% of the celestial sphere.

One problem with a qubit is that if you look at it, it assumes a specific state and stays there; superposition disappears. This is where entanglement comes in: you can indirectly look at the value of qubit’s attribute.

Armed with a quantum computer, what could you do? In general, not what you do today on your digital mainframe, desktop, or phone. A quantum computer would be lousy at balancing a checkbook, creating a spreadsheet, or writing a book. (Unless you were trying to prove the infinite monkey theorem: a monkey sitting at a typewriter hitting the keys at random would eventually write the complete works of William Shakespeare.)

Quantum computers will be very good in two areas: search and factoring.

  • If you have a lot of data to search (like the SETI problem), a quantum computer could look at all of the data at once.
  • While it is easy for a digital computer to multiply two large numbers, even if they each have hundreds of digits. Determining the factors of a very large number, like one with 500 digits in it, is very difficult and can take thousands of years with today’s fastest computers. A quantum computer could factor a 500-digit number in seconds.

OK, a very quick search would be neat but Google is fast enough for me. And I never even want to think about factoring a 500-digit number, so I don’t care about that.

Next time we will explore why you should care.

The last word:

As you probably know, the US is far behind most of the rest of the world in cell phone and credit card technology. Almost every point of sale in Europe takes EMV cards, smart cards that store the card data in integrated circuits embedded in the cards or in RFID chip. If you are wondering what the acronym “EMV” stands for, it is ”Europay, Mastercard and VISA,” the three companies that created the standard.

There are two security concerns you should be aware of:

  1. The RFID chips in your smart credit card can be read over a distance of up to three feet. Anyone close to you for a second could be a thief stealing your card. Always carry it in an RFID shielded envelope, wallet, or purse.
  2. Because non-smart cards are a pain for the retailers in Europe, they don’t like to take them and when they do they are not very careful. They won’t bother checking the signature on the card, even if you have signed it with “CHECK ID.” Anyone who steals your physical card will have no problem using it. Your credit card company should cover your costs, but it will be a huge pain. Never carry debit cards – you have very little protection against someone emptying your bank account, and they can do it in a matter of minutes.

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In my last post I indicated that the fifty-year trend of doubling computer processing power every two years was coming to an end, and growth with the current integrated circuit technologies is expected to become almost flat by 2018. One of the possible ways around this limit is quantum computing. Quantum computers take advantage of the strange world of quantum mechanics.

This is the first in a series of planned posts to give a brief overview of quantum physics (with no math), a discussion of quantum computers, the potential impact of them especially as it pertains to data security, and the current state of development of quantum computers.

Most of us spend nearly all of our time in a Newtonian physical environment. If we drop something, it falls, and we can predict how long it will take to fall. We can throw a baseball with, depending on our skill, a reasonable expectation that we know where it will go. We know how long it will take for something to travel between two points, subject to understandable issues like traffic jams, construction, or weather. This works whether we are trying to drive to the grocery store or land a spacecraft on Mars.

But outside of this environment, things may work differently. At really high speeds, relativity has an effect. NASA scientists were able to measure this, admittedly very small, effect on the Apollo missions to the moon: the astronauts aged a tiny fraction of a second less the rest of us stuck on earth due to the speed of their travel to and from the moon. At very small sizes, quantum effects take over, and some of these effects may seem to be just weird.

One of these weird effects is the uncertainty principle: if you measure one aspect of a quantum particle you will not be able to measure another. At the quantum level, a policeman could determine how fast you were driving, but could not then determine where you were.

Superposition is the principle that a quantum object is actually in all possible states simultaneously all the time, until something checks it. You have probably heard of the “Schrodinger’s cat” thought experiment: place a live cat in a steel box along with a sealed vial of a highly poisonous gas, a hammer, and a very small amount of radioactive material, plus a very sensitive radioactive decay sensor (e.g., Geiger counter). If the sensor detects the decay of a single radioactive atom during the test period, a relay causes the hammer to fall on the vial of gas and the cat dies. If not, the cat lives. We cannot know the state of the cat until we actually break into the box and look, and in the quantum world the cat is both dead and alive, until we observe it. If you are a cat lover, then substitute “evil squirrel” for “cat” in this paragraph. Like most thought experiments, this one is technically flawed; a cat is not a quantum entity and “looking” at one cannot change it’s living state.

Quantum entanglement may be one of the strangest concepts in the weird quantum world. If two particles are entangled, then if you measure one property of one of the particles, then the same property of the other particle is identical. Measuring the property of the one particle fixes the property for the other particle, so if it is also measured it will always be the same as the first particle. Somehow, the second particle learns the result from the first particle, and this happens instantaneously over any distance. When the particles are far enough apart, this “learning” travels faster than the speed of light. However, you do not learn anything about another property of the entangled pair. Any other property still has all of its possible values on each particle, and there is no relation of that value between the particles. For example, assume these entangled quantum particles had two properties: color (red or green) and shape (cube or sphere). Then if you measured the shape of one of the particles and found it to be a cube, then the other particle would also be a cube. However, the color of each particle could be red or green independently.

As the current computer chip technology gets faster, the individual components on the chip of necessity get smaller and closer together. At the speed our current chips operate, the speed of light is too slow. We need to have components as close to each other as possible to minimize the time it takes a signal to travel between components. At this time, components may be the size of a molecule. Chips with this level of component density face three main challenges: high defect rates, process variation, and quantum effects. The first two challenges are simply the result of the closer tolerances in the actual manufacturing phase. The industry has been pushing these limits for the past couple of decades, resulting in the continuous development of more exacting, and more expensive, manufacturing methods as well as more stringent testing processes.

Quantum effects are not as easily overcome. They can cause high leakage currents and large variability in the device’s characteristics. As transistors get smaller, quantum superposition will make it impossible to distinguish between the two states of a transistor. The real barrier to unlimited performance increases in computers using today’s technology is the reality of the quantum universe.

The last word:

The two main national political conventions / carnivals are over. The Republican convention in Cleveland had no fence around the convention center, and fewer than 25 arrests for the entire four days. The Democratic convention in Philadelphia had an eight-foot tall fence around the convention arena, raised in part to twelve feet after the first night. There were more than 50 protestors cited and removed by police during the first day alone, and those protests were literally drowned out by several severe thunderstorms with gale-force winds.

Please do not jump to any conclusions from these data points. As I have said before, apparent correlation does not imply causation. The different results may be more due to the difference between Cleveland and Philadelphia, or the weather, then the political parties.

One clear distinction that is caused by the parties is the presence, or absence, of the US flag within the convention. For the first two days of the Democratic convention, there were no US flags within the convention center, a sports arena. The Democratic committee had all of the US flags removed, including the huge one that has always hung above the center in the arena. Apparently, it interfered with the balloons.

Alas, the American voter is left with the sad choice between a clown and a criminal.

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In 1965, Gordon Moore predicted that computer chips would double in performance every two years at low cost, now known as Moore’s aw. He also predicted that chips they would eventually be so small and inexpensive that they could be embedded in homes, cars and what he called “personal portable communications equipment.” In 1968, he and Robert Noyce founded NM Electronics, soon renamed to Integrated Electronics and then shortened to Intel. Integrated circuits were just in their infancy at that point, with companies trying to deal with the technical issues of putting even eight transistors in a single chip.

Of course, Moore’s law is not a physical law, but, thanks in significant part to the work of Intel, it has held remarkably true for 50 years. However, earlier this year Intel announced that it will not continue to keep up with Moore’s Law.

MooresLawThis issue is part science and part finance. As a result of the shrinking the size of microscopic transistors in a modern integrated circuit, these transistors are closer together. This causes two problems: heat and quantum effects. In order to achieve the desired high performance, these packed transistors generate a lot of heat. Too much heat can literally fry a chip, making it useless. Quantum effects cause their behavior to become unpredictable, not a desired trait in the way we use computers today.

The financial problem is due to the cost to produce these new integrated circuits. Today, each machine to “stamp” out chips costs about US$50M. Each future “generation” of chips will increase the design and production cost by up to 50%, meaning a new chip factory may cost US$10B to build.

What does this mean to you and your company? Probably not much in the short term. In fact, if you are lagging a little in your technology usage in your products, this may give you a chance to catch up.  Not surprisingly, chip manufacturing companies are working on several alternative solutions to continue to drive growth in semiconductors:

  • Carry on the current path. The real obstacle is simply money. For those cases where you actually need to get maximum performance from a single small package, you will likely to be able to get it. You may not like the cost, as there will be large production costs and smaller demand.
  • New technologies including spintronics, carbon nanotubes, and quantum computing. Intel plans to move from silicon-based transistors over the next 4-5 years.

For most companies, the real solution is distribution. We see new products every day with embedded processors connected to a network. For the past decade, cars have contained dozens of computers, each assigned to one function like brakes, cruise control, entertainment systems, and even door locks. As the car manufacturers move towards full autonomous vehicles, we are seeing integration of all the computers within a car into a single network, with additional computers added for new functions. We will over the next ten years see the cars themselves integrated into a wider network including other cars and traffic signals and monitors.

As you are looking at your future product plans, consider distribution both within your product and to the outside world as a way to expand capabilities and performance and attract new customers. Always remember that the Cloud is there to help.

The last word:

I was one of 23 thought leaders recently featured in Tenfold’s “23 Thought Leaders Answer: What’s Your #1 Tip for a Successful First Meeting with a Prospect?” You might want to check it out.

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I feel a little lazy this week. We just got back from a very busy spring with two cruises: one from Vancouver around Hawaii and back to Vancouver on Holland America and the other from Amsterdam to Budapest on a Viking Longboat. I strongly recommend both cruises. Between the trips we attended a family wedding at the other end of the state.

But cyber attacks continue unabated. Some of the more recent “highlights:”

  • On top of the 191 million voter registration records stolen in December 2015, another 56 million records were captured and exposed, probably by a Christian right-wing organization. While a lot of information in your voter registration file is public, it does include name, address, birth date, and party affiliation. Organizations can use that information to correlate other non-public information including voting history, religious affiliation, charity donations, work place, income level, political leaning, and some really strange information like whether you like auto racing.
  • State Farm had information on 77,000 customers stolen by a hack into DAC Group, a large advertising agency in the US and Canada. While it currently seems that no financial information was stolen; it is likely that these customers had their email addresses stolen. What is instructive, however, is that this information was stolen from a development server at DAC. Security on development systems is often not as comprehensive as on a production system, and one of the reasons to have a development system is to confirm that any enhancements have not impacted data security before the software moves to the production environment. You should never use production data in a development environment. DAC should have known better.
  • A Japanese travel agency, JTB Corp, had personal information for almost 8 million people. One of JTB group companies experienced a targeted email attack, and an employee opened an attached file, which infected their server.
  • On the lighter side, the Cowboys Casino in Calgary, Canada, was attacked and personal information on less than 2,000 customers and staff were stolen. You parents told you not to gamble.

These are just a few of dozens of attacks in June 2016. If you are not having trouble sleeping, check out Norse real-time threat intelligence. This shows a small sub-set in real-time of network attacks based on their service and port. This does not include email or other application-level or OS-level attacks.

The last word:

For those of you in the United States, enjoy the Fourth of July and think about the freedoms we have here.

A number of people we met on the European cruise were from the UK, and this cruise was just before the BREXIT election. Most of them were concerned that the UK might vote to leave. From my perspective, it is past time for the UK to leave the EU. The EU bureaucrats control far too much of what each individual country and company must do, down to specifying the size and shape of wine bottles. These bureaucrats all seem to be socialists. As a result, the growth of the European economy is in last place compared to Africa, Asia, North and South America. However, the European economy is growing faster than the economy of Antarctica.

In 1992, “everyone” predicted dire consequences for the UK economy when it refused to abandon the Pound and move to the Euro. In 1990, the UK entered the European Exchange Rate Mechanism, a prerequisite for adopting the Euro. The UK spent over £6 billion pounds trying to keep its currency within the narrow limits prescribed by the EU, but, led by Prime Minister Tony Blair and his successor Gordon Brown, finally ruled out conversion to the Euro in 2007. One of the best moves in recent UK history.

Before the BREXIT vote, the UK was the fifth largest economy in the world. Do you really think a European company will cease to trade with a UK company because they are no longer in the EU?

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Both compressed data and encrypted data look similar: they are a string of apparently random characters that seem to bear no relationship to the original data. But there are significant differences between the intent and the process of compression and encryption.

You compress data so it is smaller, thus reducing storage space or transmission times. But since you want to easily retrieve the original data, compression algorithms are standardized and well known. Consider a ZIP file. A ZIP file can be expanded back into its original file(s) on almost any kind of computer system. In most cases, the receiving system needs no additional information than that contained within the compressed file.

Compression algorithms work by finding strings of characters that are repeated within the data, and replacing each occurrence of the string by a much shorter string. If you had, for example, a long paper about George Washington, a simple compression algorithm might replace each occurrence of “George Washington” with “\gw\” thus replacing 17 characters with just 4 each time. Compression algorithms can find lots of duplicated strings like page headers and footers, and fragments involving parts of words or numbers.

You encrypt data so that only certain people can access it. In order to decrypt the data, the receiver needs to know a secret key. Depending on the type of encryption and the length of the key, it can take the fastest computers from seconds to millions of years to brute force decrypt the data. For any scheme more complicated than a simple character substitution (replace each “A” with “x”), the encryption process eliminates the duplicated strings. “George Washington” will most likely be encrypted into different strings at each occurrence.

Therefore trying to compress encrypted data is just a waste of time, and can actually make the data bigger since there is some overhead just to define the type of compression and other parameters needed to decompress it.

Some compression algorithms support some level of encryption. For example, when you create a ZIP file you can specify an encryption key. Many of these algorithms are very weak and subject to easy attack, plus you must send the key to the receiver by some means. I watched a coworker email an encrypted ZIP file to a partner, then send a follow-up email with the password. If the receiver’s email was compromised, then the cybercriminal just received the data and the key.

Both compression and encryption can take significant processing effort on each end. Usually it takes fewer resources to decompress data than to compress it. Since stored data needs only be compressed once, when it is stored, and is often decompressed many times, this attribute is desirable.

Normally, encryption and decryption times are very close to each other on the same platform. Obviously, the actual times depend on the hardware characteristics of the platform.

You should always encrypt sensitive data, whether it is personal or financial data that is protected by regulations or laws, or proprietary information for a company or classified information for a country.

Whether you choose to compress data is a simple business decision: do you save enough money or data transmission time to justify the added cost of compressing and decompression the data.

The last word:

If you need to compress and encrypt data, first compress the data, then encrypt it. That works and you get the full benefit of the compression. However, the process introduces a vulnerability to attack the encryption.

As mentioned earlier, each compression algorithm adds a header in front of the compressed data. That header defines the compression type and a bunch of parameters and is of a fixed format. It is possible to determine the type of compression that an organization uses or accepts by simply trying different compression schemes and see which ones are accepted. It then becomes far easier to attack the encryption since you know how the clear-text message starts.

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Benford’s Law

Benford_1Have you ever wanted to do a quick sanity check on a long list of numbers? It might be a budget, worldwide sales by country or product, or a marketing forecast. There is a cute little trick that can possibly tell you if the numbers might be manufactured instead of real: Benford’s Law.

Benford’s Law, which is not really a “law of nature” but the result of more than 125 years of observation, states that the first digit of many real-life sets of numerical data is more likely to be a “1” then any other first digit, and the probability gets successively smaller for “2” through “9”. Intuitively, one might expect that the probability of the first digit would be evenly spread: about 11% for each possible first digit 1 through 9. Zero doesn’t count as a first digit in this case. The law works even with a set of numbers with vastly differently sized numbers based on the number of digits in the number. In fact, the more orders of magnitude covered by the data, the more accurately Benford’s Law seems to apply.

Benford_2In other words, a list that spans numbers as small as 100,000 and as large as billions is likely to follow the law closely. For example, this chart shows how closely the population of the 237 countries in the world (red bars) match Benford’s Law (the black dots).

The American astronomer Simon Newcomb published a paper in 1881 based on the fact that in his logarithm tables the earlier pages were much more worn than the other pages, implying that he was looking up numbers starting with 1 and 2 more often than others. If you have no idea what I’m even talking about, check this out. He postulated the formula in Benford’s law for first digits of 1 and 2. In 1938, physicist Frank Benford tested the theory on twenty different sets of numbers and was thus credited with the law. His data sets included the surface areas of 335 rivers, the sizes of 3,259 US populations, 1,800 molecular weights, and 308 numbers contained in an issue of Reader’s Digest.

Benford’s Law is not a law, and will not apply to sets of numbers that are restricted in value, like the phone numbers in Philadelphia (since almost all will start with 2, 4, or 6). A set of numbers that does not match Benford’s Law is not necessarily wrong, but might be worth a second look. If someone is manufacturing numbers, they are likely to not match Benford’s Laws.

Why does this law work? It has to do with the distribution of numbers in a logarithm scale, and explains why the wear on Simon Newcomb’s logarithm tables led to his initial discovery of the relationship.

Some relationships do not obey Benford’s Lw, including distributions created from square roots or reciprocals. It does not apply to numbers that are the result of mathematics combinations, like quantity times price, or sequentially assigned numbers like check numbers.

At various times, evidence based on Benford’s Law has been admitted in criminal cases at US local, state and federal levels. It has been used as evidence of fraud in the 2009 Iranian elections, although experts tend to discount Benford’s Law as a indicator or election fraud.

Mark Nigrini, a well-known South African author of Forensic Analytics, has shown that Benford’s Law could be used in forensic accounting and auditing, which is how this post started.

The last word:

Benford_3As I was talking about this post, my wife said that this law should also apply to the number of children in a family. In her genealogical research, it appeared to her that there are a lot of families with just a few children and, especially in the past, families with large number of children, more than 9. I could not find any overall statistics to support or deny this claim; most government statistics talk about 1, 2, and “3 or more” children. However, I did find one family tree that had the statistics I wanted covering 344 families with up to 15 children in a family.

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London CabWhen you travel around in London you encounter three moving icons that help define the city: the Underground, the red double-decker buses, and the black London cabs. You do not want to drive yourself in the centre city for several reasons: there are a lot of cars and little parking, they drive on the other side of the road, and they have a “Congestion Charge” that, for the casual tourist, is up to £14 per day, with a £130 per day fine if you are caught without paying the CC.

Last year I predicted that by 2030, London will be the first large city to completely ban non-autonomous vehicles within the City of London. And by 2040 within the entire metropolis of London. I may have been too conservative.

Auto-MateMarcello Raeli is a young Italian designer who grew up all over the world, moving with his parents every 4-5 years. His father was an architect and a painter, and Marcello yearned and learned to be a Designer of things that solved real people’s problems. He also loved Isaac Asimov’s science fiction stories and predictions of the future. He designs shoes, including “running” shoes that can bring the same augmentation that some amputee runners have discovered to a full-limbed runner. He also designs cars, from micro-minis to high performance cars.

Auto-Mate interiorOne of his latest designs is Auto-Mate, an autonomous time-share vehicle specifically for London. It seats up to four adults in comfort. Taking inspiration from the iconic red buses, red telephone booths, and the London Eye, the giant Ferris wheel by the Thames, the Auto-Mate is a sleek, futuristic-looking vehicle the same size as the existing London cabs. These vehicles provide transportation-as-a-service to anybody at any time of the day or night, and in any weather. The number of cabs on the street can change automatically based on demand. Over a relatively short time, the system will be able to predict need based on day of week, time of day, weather, or special event and have sufficient vehicles available to meet real-time needs.

London cab drivers, usually, are well trained and know their way around. They speak a form of English, sometimes not easily understood by Americans. The Auto-Mate can speak and understand dozens of languages, and keep quiet when that is what you want.

Raeli’s Auto-Mate is just a design today, but at the rate autonomous vehicles are evolving, sometime soon you may see these as you walk by Parliament.

There are, of course, those who want to slow down the adoption of autonomous cars. The NHTSA (National Highway Traffic Safety Administration) is currently planning on having guidance for the deploying of autonomous vehicles by July 2016. Issuing actual regulations normally takes about eight years; by providing early guidance, the US government will be able to react more quickly to this rapidly changing technology.

It is very hard to stop new technology. Already, Tesla’s autopilot function will automatically drive your car on a highway, including changing lanes and adjusting speed in response to nearby traffic.

The last word:

In January, General Motors and Lyft announced an alliance to create a network of on-demand autonomous vehicles in the US. Lyft is a ride-sharing service, and this alliance plans to eliminate the driver.

Ford is also allowing some car owners to rent their car to a stranger for short periods of time. For example, 12,000 Londoners offer time slots in their cars to pre-screened renters. The plan is that they can earn enough money to cover their car payments, thus having a vehicle for their own use for free. This car-sharing and ride-sharing services like Uber and Lyft are starting a significant change in how we think about cars.

Cars are critical, especially for those of us of a certain age for whom a car represented freedom, a key disconnect from constant supervision by parental units and a means of getting where we wanted to go when we wanted. But, considering the cost of a car and the fact that most cars spend 95% of their time parked and unused, the significance of car ownership will probably decrease.

Maybe not for us over 30, but for the younger generations, the car is likely to cease to be a prized possession but just a means of getting somewhere, and it won’t have to be their’s.

Children born after 2015 will probably need a history lesson before they will understand what is going on in the Taxi TV show.

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