Mad Dog 21/21: Coining Money
February 17, 2014 Hesh Wiener
The number of bitcoins in circulation is more than 12 million and growing. They have an aggregate value with an order or magnitude of $10 billion. Are bitcoins money? That depends in on how one defines money and where in the world one happens to be. In China, it is illegal for banks to trade bitcoins but in the USA bitcoins are kosher. Overstock.com sells IBM x servers for bitcoins. But there is no simple way to buy Power or mainframe servers from IBM with the bitcoins they resemble.
Briefly, a bitcoin is not a physical coin like a penny. It is a data record, defined by software, various conventions, and its pseudonymous inventor, Satoshi Nakamoto. In 2009, Nakamoto put in the public domain software called Bitcoin-Qt that creates and manages bitcoins. Part of the management scheme is a public record, called the block chain. The block chain is a publicly available data file that includes the inception of every bitcoin and every transfer of ownership of that bitcoin subsequent to its creation. The software defines a process that creates fewer and fewer bitcoins as time goes on. The process is designed to end in about 25 more years. No more new bitcoins will be created after 2140, by which time there will be 21 million bitcoins.
This constrained supply stands in contrast to the population of computers, particularly if one defines computers broadly to include tablets, smartphones, and gaming systems. If one defines computers to encompass even more things, such as system-on-a-chip devices, or SOCs as they are commonly called and that seem to be pretty much everywhere these days, the supply is vast. Either way, the number of computers is growing at a stunning pace, but that is not the case with every type of computer.
Computers of any particular type have production lives that can end for a variety of reasons. After they are manufactured and deployed, computers have functional lives that end when they are no longer practical, often because better, smaller, less costly, and otherwise more attractive computers take their place.
But, in aggregate, the market for computing devices is like the market for fuel. One type may replace another, but demand just keeps growing. The demand for computing grows faster as computer costs come down. The demand for energy grows faster as energy costs come down. But in the case of energy and, possibly someday in the case of computers, increases in cost may reduce but not eliminate growth in the aggregate market.
IBM has distinguished its computer business from the industry at large, and succeeded on its own terms. It has not, however, successfully participated in the high-volume markets that constitute the lion’s share of the total computer industry. IBM doesn’t make and hardly uses state-of-the-art SOCs. It only for a short while, during the 486 era, made the processor chips used in the PC business it sold and it has never made X86 chips for the server business it is leaving. It does make Power and mainframe chips, but only in the small volumes required by three proprietary server lines formerly known as z, p, and i. In IBM’s proprietary server trade, unit volumes are measured in thousands, while X86 servers are measured in millions, PCs and mobile standalone devices are measured in hundreds of millions and unit volumes in the myriad embedded computers that manage automobiles, appliances, communications devices, medical apparatus and most everything one can think of that runs on electricity are measured in the hundreds of millions, too. ARM Holdings, which licenses its eponymous chip architecture, counts the fruits of its output in billions.
IBM’s business models don’t seem to include operations that grow revenue and profit with soaring hardware production volumes. That is not the case at Apple, Samsung, Intel, Hewlett-Packard, and other companies that are in today’s computing mainstream, nor is it the case in the product divisions of computer industry participants with larger interests outside the device business, such as Google, Microsoft, and Amazon.
The computer manufacturing industry leaders also include companies that once were the nearly invisible assemblers and manufacturers of machines for others, typically Taiwanese or Chinese industrial enterprises that today seek to be the primary suppliers of Google’s servers and other high-volume, high-total-revenue products.
IBM knows all this and apparently prefers to choose a path that takes it away from the computer business. But its success, and perhaps its very survival, depends on another business that will obey the same laws of economics that govern the markets in computer hardware and energy, among others.
In fact, it was the situation in the key energy market of his time, that for coal, that inspired William Stanley Jevons, an academic born and raised in Liverpool, England, in the middle of the nineteenth century to describe what he saw was in some ways a paradoxical development.
Jevons saw that dramatic improvements in steam engine technology and other advances in engineering were making it possible for much less coal to do much more work. When most other things became less expensive, and in his England wool may have provided a concrete example, business interests shifted focus and sought different opportunities. But in the case of coal-based energy, improved value set the markets on fire. Demand rose even faster than prices fell, with the net result that demand for coal kept soaring. One of Jevons’s books, The Coal Question, published in 1865, helped the polymath shine brightly in the emerging constellation of scholars whose collective work would come to be known as macroeconomics. Jevons also participated in related work on the marginal effects of pricing and demand on production and consumption.
IBM knows all about macroeconomics. Even among the company’s top executives, a crowd in which an MBA is cheerfully passed off as proof of educational attainment, lots of people must have been compelled to read Samuelson or one of its rivals. At the very least, the company’s Dutch Dodgers, who obviously have the ears of Big Blue’s economics enchiladas, must know a bit about this stuff. If they don’t, now might be a good time for them to learn.
As they do, they might trip over some of the more amusing tales about Jevons, including his work building a machine that could solve problems in Boolean algebra that he called his Logic Piano. Also, a little inspiration about the value of invention couldn’t hurt whatever passes for a brain trust inside IBM these days. The computer industry has long since moved on. IBM’s brilliant delaying tactic in the form of a fabulous method monetizing services could soon lose its effectiveness. IBM’s success in services was built on the bedrock of its prowess in manufacturing. Now that IBM is leaving manufacturing (or vice versa) in one product line after another, the bedrock is crumbling. The services structure built on that bedrock is unlikely to stand without its former foundation.
Even the envelope trend in computing, the evolution from large engines to smaller ones and on to tiny but impressively powerful SOCs and their ilk could give way or at least cede ground to an alternative: specialized processors designed and developed by engineers who appreciate the limitations in the small handful of off-the-shelf, affordable computer architectures. X86, ARM, Power, Sparc, and MIPS may be great, but they are simply not the best possible solution to every problem.
Consequently, in addition to the companies that produce general purpose servers, there is a much smaller but very lively segment of the computer business that builds specialty chips and products. This specialty has cousins in the form of adept server makers that integrate these chips into machines that excel at certain types of mathematical functions.
Arguably, the most prominent members of this class are the manufacturers of graphics cards, such as Nvidia. Nvidia products are used in workstations where they drive displays, but the same circuits are also very good at the vector calculations used by physics and biology. Nvidia has gone very far creating software and hardware that adapts its specialty engines for use in compute-intensive tasks. As a result, some supercomputers depend on Nvidia chips (and the CUDA software that manages them) to produce results faster and more economically than could be obtained using general-purpose CPU circuits.
A related application that uses special chips is encryption, where application specific integrated circuits, ASICs, make it possible to rapidly and, of great importance, inexpensively encode and decode messages. Currently, there are chip developers creating ASICs that are used to perform the hash encryptions on which bitcoin mining is based. Bitcoin mining does not involve physical mining as done in the hunt for gold. The creators of Bitcoin as an idea used the term mining to stand for a mathematical process that encodes each bitcoin transaction using a powerful one-way hash. This process plus surrounding procedures and conventions largely guarantee the integrity of the bitcoin system.
(This integrity has been breached in dramatic but relatively small ways, at least compared to the size of the total bitcoin market, recently. The bitcoin community is scrambling to remedy flaws in the bitcoin software that have permitted malefactors to engage in double spending, something the bitcoin system is supposed to prevent and usually, but apparently not always, does.)
The ASICs are components that make bitcoin mining more economical, but they must be harnessed in servers to produce useful results. This integration process is a growing part of a computing universe that seems to live in a parallel world not yet occupied by the established big name computer companies.
Specialty server coprocessor makers like Butterfly produce bitcoin mining apparatus that is in great demand. The only way to buy a machine, at least for one of the well-regarded models, is to pay in advance and sit on the waiting list for weeks or months. Once built and delivered, this equipment is sometimes installed in users’ data centers or ordinary server hotels, but the mining servers are sometimes found in exotic data centers located where power and cooling are cheap, such as up near the Arctic Circle in Iceland.
Bitcoin is probably only the first of a bunch of synthetic moneys. The next one or the one after that–and I am inclined to think there will be quite a few of these launched during the next few years–may be defined to become a thousand times the size of bitcoin. If it could get to $10 trillion it would be large enough to make a real difference of some kind in the world, whether it succeeds or fails. And, if Big Blue got into the cryptocurrency game in a big way, making, say, one percent off the top, it would be more or less doubling its intake. Moreover, if IBM’s services customers find other vendors the way its product customers have, the mining business might be a good way for IBM to keep all the servers it already owns and lights up doing useful work.
IBM’s next money question might be: How many bitcoins is this Watson worth?