The term 'disruptive', for better or worse, has entered the popular lexicon. Not in its originally intended form as in 'Ramesh is very disruptive in class', or 'the politician's henchmen tried every means to disrupt the meeting by throwing rocks and setting off fires'. Let's fault Clayton Christensen of Harvard Business School for this bit of lexical outrage; and he for one, would likely cheerfully accept the blame. Christensen popularized the current -- and positive -- usage of term in his successful first book, The Innovator's Dilemma, with which he has launched an entire franchise around the concept of disruption. Now every business out there yearns to be disruptive. (And politicians' henchmen too, now legitimately.)
In the Christensen Universe, a disruptive technology or innovation is one that does not threaten the market leader when it is introduced because it is limited in its scope (or too high priced) so that it doesn't appeal to the current mainstream market. Over time, however, the price/performance as well as feature set of the innovation improve rapidly, eventually eclipsing the formerly dominant paradigm.
Personal Computers (PCs) are one example. When introduced in the late 1970's, they were considered toys for hobbyists, at best. In time, a variety of useful programs began to be written, and given their relatively low price, PCs began to proliferate. The massive inflow of profits to beneficiary vendors such as Microsoft and Intel permitted them to pursue R&D which resulted in rapidly rising technical performance and capabilities as well as a relative lowering of costs with respect of performance. Along the way, the sped past microcomputers from vendors such as Digital Equipment Corp., Data General, Prime and numerous others, who, because of their smaller markets (and higher unit prices) could not afford to keep pace and eventually were wiped out.
And while the Unix operating system which originally ran on minicomputers is still going strong, there are no longer any dedicated Unix vendors left since Unix runs equally well on mainstream Windows/Intel machines.
Disruptive innovations always have some key attribute that is of great relevance to a specific market segment. The important part of disruption is that the innovation process continues relentlessly, eventually making a certain kind of technology acceptable even to those market segments at which it was not originally aimed. Another disruptive example is digital photography. When first introduced, digital cameras delivered poor images compared to film cameras, and even cost more. For certain applications, however, such as the military, the instant availability of a picture (and the ability to store and transmit them digitally) made them good enough. With steady sales and the flow of funds available for R&D, the prices began to drop while quality improved enough that even hard-core photographers began switching. Although photographic film is unlikely to disappear in a while, it has been marginalized and used primarily for very high quality photography and other special applications.
Disruption is not a phenomenon restricted to the digital realm, but it happens to be the space in which a very high proportion of disruptions occur. Moore's Law which describes a trend in digital electronic components where the performance of a technology grows exponentially with an accompanying rapid reduction in cost is probably the explanation for this.
Which brings us to WolframAlpha, the latest offering from the vendor that brought is Mathematica. The 800-pound gorilla (or the Microsoft) of the Search space is Google, and anyone with pretensions to taking on the Big Guy is lying or delusional. And so, according to this New York Times article,
Despite the online chatter comparing it to Google, his service is not intended to dethrone the king of search engines.
So, this is a technology that some who are familiar with it think is trying to go up against Google, but whose vendor vociferously claims otherwise. Hmmm .... sounds like a potential disruptive technology (or innovation) to me.
"I am not keen on the hype,”
says Stephen Wolfram, a former child prodigy not exactly famous for his modesty. According to the Wikipedia description of WolframAlpha:
It is an online service that answers factual queries directly by computing the answer from structured data, instead of providing a list of documents or web pages that might contain the answer.
So how does Alpha do its job? Here's the NYT again:
Mr. Wolfram’s service does not search through Web pages, and it will not help with movie times or camera shopping. Instead it computes the answers to queries using enormous collections of data the company has amassed. It can quickly spit out facts like the average body mass index of a 40-year-old male, whether the Eiffel Tower is taller than Seattle’s Space Needle, and whether it is high tide in Miami right now.
So it does numbers and logic rather than search and pattern matching, which is what Google essentially does. Here is some more:
Traditional search engines like Google and Yahoo, by and large, excel at finding information that already exists online. If there are Web pages that include the words used in a query, the engines will find them and rank them in order of relevance.WolframAlpha is different. For starters, it does not gather data from the Web. Instead, its “knowledge base” is made up of reams and reams of data — ranging from the kinds of facts you would find in a World Almanac, to highly specialized data from physics and other sciences — that some 100 employees at Wolfram Research have gathered, verified and organized over several years.When a user types in a query, WolframAlpha tries to determine the relevant area of knowledge and find the answers, often by performing calculations on its data. If you type “LDL 120,” it will return a graph showing the distribution of cholesterol levels among the United States population, and display the percentage of people above and below that figure. If you type “LDL 120 male 33,” it will adjust the results to focus on that gender and age group.In response to “how far is the Moon from Earth,” WolframAlpha will calculate the exact distance based on an algorithm that computes the ever-changing distance between the two bodies. The engine that computes answers is largely built on Mathematica.
Even Doug Lenat, who has an ego not significantly smaller than Wolfram's, is persuaded to exclaim,
“It may become a massive player alongside Google,” Mr. Lenat said.
So Alpha is attempting to shift the user's goal some: Google is a Search Engine -- you search for information that may or may not be out there, and frequently come away empty handed or not quite satisfied. Alpha, on the other hand is NOT A SEARCH ENGINE at all. It is an ANSWER ENGINE. [UPDATE: It is a "computational knowledge engine." Whew!] You have a question, you ask Alpha, and in a ideal world, it will give you precisely the answer you seek. A lot of times, one is not really doing a expansive search -- all you want is a single, precise answer to a question. And sometimes you find it, if the answer is out there. Google seeks an answer if it exists; Alpha calculates an answer if it can and gives it to you. Different from Google, but something that a lot of people need, a lot of the time, but use Google since it is pretty much the only thing out there. Perhaps like using a mainframe computer to do some word processing -- until a dedicated PC came along to help you do just that.
Now, a lot of claims have been made over the past several decades (usually from the Artificial Intelligence community -- including Doug Lenat) about the possibility of building something like the Alpha, but none have been particularly successful. If Wolfram succeeds then he is probably worthy of worship.
My prognostication? Alpha will definitely prove to be, well, disruptive. There, I used the word.