In continuation of what I've learned, and am beginning to absorb, understand, and evangelize after attending this year's Singularity Summit, I live twittered a few profound thoughts spoken by some of the presenters. One of them was from Neil Jacobstein, CEO of Palo Alto based Teknowledge:
Another belief about AI is that it’s all hype. It’s boom and bust from the 1980’s and although there was a lot of that, early AI is in routine use in many domains. It’s already produced billions, with a ‘b’, worth of value. And writing off AI is a little like writing off ecommerce after the dot com meltdown.
Of the presenters that I heard speak, or had met (note: I attended only Saturday's sessions), Mr. Jacobstein was one who answered the question "So, what does all of this really mean, for me?" ...whether you were asking this question as a CEO, an investor, or practically anyone outside the "singularity circle" of thinkers.
He decided to perform a study on the application domains - or the areas of focus of these AI applications. In particular, Jacobstein studied the ones between 1986 and 2006 (there were a total of 362), and found, unsurprisingly, that the most common area was computers and software
engineering. This was followed by manufacturing, military, finance
applications, business operations, telecommunications, arts and media, health care, space, ground transportation, airlines, education, sales, biotech, insurance,
energy, emergency management, security, law, agriculture, chemical engineering,
paleontology and treaty verification.
The tasks that these systems perform are largely focused around planning and scheduling, data interpretation, information retrieval, classification, performance optimization, etc.
Mr. Jacobstein explained:
When we consider the value-added by AI and these applications, they’re in augmenting or replacing human skills, which allows you to:
- improve accuracy and consistency
- decrease costs
- increase productivity
- accelerate process timing
- improve product + service quality
- expand the range of the possible
Now, here's where you want to pay attention:
It doesn’t just do more, faster, better. It helps institutions manage their knowledge.
One early expert system example is BP’s VIDES (visual identification expert system) which does micro fossil identification system associated with rich oil fields to drill in. This system was basically constructed to eliminate delays in the process of figuring out where to drill. One day of delays cost $1 million; BP reported that one particular delay cost the company $15 million. VIDES acts as a ‘member of the team’, and has virtually eliminated identification delays.
"It doesn't do more, faster, better. It helps institutions manage their knowledge." Worth repeating. Do I have your attention yet?