The need for speed seems to be driving towards a signpost up ahead and it is not the Twilight Zone. Artificial Intelligence or A.I. is just down the road.
January 1, 2008
From the 1960’s through the mid 1980’s, we have seen remarkable changes in the world of communications, primarily in telecommunications. At the beginning of the 1960’s the predominant traffic on communication highways was voice traffic, specifically man-to-man.
By the early 1970’s, there was a remarkable increase in traffic for man-to-machine-to-machine, machine-to-man, and machine-to-machine.
During the 1970’s, the amount of traffic on our networks involving machines grew to more than 52%. During the 1990’s machine-to-machine traffic reached more than 93% of the total network traffic.
The touch of the computer is felt everywhere and it is just the beginning.
Many of today’s laptop PCs are more powerful than the mainframe computer of 25 years ago. The information age is moving ahead, literally, at the speed of light.
In the world of cabling networking systems, during the past two decades, we have watched an unstoppable parade of infrastructure products that deliver higher performance, better transmission, and increased interoperability.
From the early LEVELS Program by Anixter to the EIA/TIA Standards, we have Category 3 through Category 7 cables and connectors. Network speeds soared from 64 Kbps to 40 Gbps. Now they are working on 100 Gbps speeds.
The consumer has become accustomed to buying network solutions only to find them obsolete before the installation warranty has expired.
This migration strategy of products and the development curve has been driven by the demand for more information at faster rates.
The need for speed seems to be driving towards a signpost up ahead (not the Twilight Zone). Artificial Intelligence or A.I. is just down the road. A system that learns and can make decisions is modeled on the human machine.
Back in the early 1960s, there were still a few manual (cord board) PBXs still in service. The telephone companies were pushing hard to replace them with newer technology. The customers were clinging to old switchboards because the operator added so many features to the communications service.
The human machine (i.e.. the operator) recognized voices of important frequent callers, remembered many frequently called numbers, knew when calls should be handled as priority, knew which parties were available or would be available.
Many businesses wanted to recapture the properties of the human that were lost when the traffic became so heavy that dumb machines were required. Ever since then, we have been wrestling with how to put the human into the machine.
Consider the custom calling features offered by the telco central office and the programmable station capabilities of current PBX’s.
These are just a few examples of our pitiful attempts to put the human in the machine. The cabling networking systems are gathering and sending information from a host of different applications.
The systems are “learning” just like a child. The more information gathered, the greater the decision making process is facilitated.
The examples are all around us.
Today, automobile windshield wipers can be sensitized to water and send commands to the brake system to auto-dry. In buildings we have added control of security, access, energy, lighting, wireless, networks, communications, and computer resources.
Power of Smart Buildings
The cabling networking systems are similar to the nervous system of our bodies. Our industry is like an infant learning how to use its capabilities. The infrastructure is perhaps the most important component of our ability to increase the power of our “smart buildings.”
The “Big Payback” for these improved technologies is the improved work performance of the people it affects. Increased work performance translates to huge financial gains. In the world of real estate, it used to be “location, location, location” and now it has changed to “location, location, communications.”
Better working environments promote improved creativity and performance. For the building owner this also reduces costly tenant turnover. The infrastructure systems are being looked at in a whole new light.
They are also no longer just tenant specific and thrown out with the garbage when the tenant leaves. As this networking infrastructure extends its tentacles into many areas that affect the workers’ job performance, the value of the structure increases dramatically.
The information gathering capabilities facilitated by the networks begins the first giant step toward A.I. Many of our productivity gurus support the Bayes’ Theorum as the best path to developing systems that can “learn and make decisions”.
Bayes’ theorem (also known as Bayes’ rule or Bayes’ law) is a result in probability theory, which relates the conditional and marginal probability distributions of random variables. In some interpretations of probability, Bayes’ theorem tells how to update or revise beliefs in light of new evidence a posteriori.
The probability of an event A conditional on another event B is generally different from the probability of B conditional on A. However, there is a definite relationship between the two, and Bayes’ theorem is the statement of that relationship.
As a formal theorem, it is valid in all interpretations of probability.
However, frequentist and Bayesian interpretations disagree about the kinds of things to which probabilities should be assigned in applications: frequentists assign probabilities to random events according to their frequencies of occurrence or to subsets of populations as proportions of the whole; Bayesians assign probabilities to propositions that are uncertain.
A consequence is that Bayesians have more frequent occasion to use Bayes’ theorem. The articles on Bayesian probability and frequentist probability discuss these debates at greater length.
The principles of Bayesian theory (pre-test probability, likelihood ratios, post-test probability, treatment threshold): We can legitimately use the Bayesian approach even on an unstable system, since we use Bayesian probability theory to describe the distribution, not of the data itself, but of our knowledge about it.
William Edwards Deming was an American statistician, college professor, author, lecturer, and consultant.
Widely credited with improving production in the United States during World War II, he is perhaps best known for his work in Japan.
There, from 1950 onward he taught top management how to improve design (and thus service), product quality, testing and sales (the last through global markets)] through various methods, including the application of statistical methods such as analysis of variance (ANOVA) and hypothesis testing.
Deming made a significant contribution to Japan becoming renowned for producing innovative high-quality products and becoming an economic power.
He is regarded as having had more impact upon Japanese manufacturing and business than any other individual not of Japanese heritage. Despite being considered something of a hero in Japan, he was only beginning to win widespread recognition in the U.S. at the time of his death.
For most of his life, including when he wrote his major statistical works, Deming believed that the frequentist approach was a better theoretical orientation. However, later in his life his views changed somewhat, and he became somewhat more open to the Bayesian interpretation.
Pathways For Tomorrow
The reach of fiber optic networks will continue to extend closer to the termination as the demand for transmission and throughput increases. FTTX or Fiber To The ??? is our next big horizon for the cabling networking systems.
Will copper-based communications cabling disappear? No. However, we do expect the copper- based cabling to lose significant growth share in the next decade.
The list of applications for cabling to handle is growing faster than most people can assimilate.
Many industry and trade associations are stepping up to the
plate to be part of this dazzling new opportunity in the Information Age.
Many users will continue to follow traditional cabling technology until the value of smart systems is so overwhelming that they will no longer be able to hold back. Some users will never need or want these advanced technologies.
The GEM Sector (Government – Education – Medical) is prime for the benefits of these technologies.
We forecast that these areas will lead the pack in the increased productivity and the resultant A.I.
Heck, the flow of information on the (World Wide Web) Internet is equal to the entire U.S. Library of Congress every five minutes.
Imagine, the access to this amazing world of the future is through a simple little cable.
Frank Bisbee is a communications consultant based in Jacksonsville, Fla. & Editor of Heard On The Street (HOTS), a monthly newsletter that can be accessed at www.wireville.com. He can be reached via e-mail at firstname.lastname@example.org.