3 Big Ideas: emerging technical areas w/biggest impacts

[Randy Burge]

Three Big Ideas

ManyWorlds by Steve Flinn
published on 01/10/2005
Community Rating:  (3.8)

http://www.manyworlds.com/exploreCO.aspx?coid=CO110051553264

As we ushered in the New Year, we were fortunate to have recently had the
opportunity to spend some time with Michael Schrage, perhaps the world?s
foremost authority on business innovation, and, of course, a ManyWorlds
Thought Leader.

Our discussions with Michael were very wide-ranging as usual, but we
eventually got on the topic of what we thought were the technical areas that
will have the most impact on businesses over the next few years, and yet are
currently very under-recognized. Here are three big ones that we kicked
around:

1.    Massive parallelism in information acquisition. The reduction of
scarcity in the computing world has already transformed myriad processes ?
we no longer worry about conserving scarce memory, storage, bandwidth, etc.
We tend to forget that just a decade or two ago those were big bottlenecks.
Cycle times are dramatically reduced when the marginal cost of formerly
scarce resources plummet. In other words, waste makes haste! Now this same
philosophy is being applied to experimentation. Massive parallelism of
experiments, or more broadly, information gathering, has already had a
profound impact on the biosciences, and now is poised to revolutionize
materials science in general. While nano-tech gets all the buzz, ?waste
makes haste? is the revolution that will hit first.

2.    Inferencing from massive information. The amount of information that
is being generated, whether from ?waste makes haste? above, or from
commercial transactions, market data, etc. is growing exponentially. Making
inferences from this data remains a challenge. Coming to the rescue is a set
of new inferencing techniques, most notably statistical learning models,
that have just been mathematically established in the past five years or so.
Some of these models are based on the biggest advance in the predictive
modelling arena in 500 years! The Greeks gave us deduction, the Renaissance
brought us induction, and now statistical learning theory brings us
transduction. These new techniques promise insights from data that were
previously inaccessible.

3.    Adaptive systems and processes. We all want systems and processes that
adapt to our preferences and interests over time with use. By tracking our
system and process usage behaviors, along with those of others to whom we
have an affinity, systems can learn to become more and more effective. This
approach was tried a number of years ago under the umbrella of ?intelligent
agents?, but the data gathered was too sparse, and the means of behavioral
information capture too obtrusive to be effective. Now those barriers are
rapidly falling, and application of statistical learning approaches
described in ?Big Idea 2? above, will ensure adaptive systems and processes
will become the norm.

Each of these areas is significant in its own right, but you can also tell
from my brief musings that they will tend to reinforce one another ?
amplifying their impact.
Transformational, yet non-obvious, technologies such as these three big
ideas are the ones that end up driving the transformation of industries, and
making or breaking businesses.  
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