I am just back from the first ever Cognitive Computing Forum organized by DATAVERSITY in San Jose, California. I am not new to artificial intelligence (AI), and was a software developer in the early days of AI when I was just out of university. Back then, if you worked in AI, you would be called a SW Knowledge Engineer, and you would use symbolic programming (LISP) and first order logic programming (Prolog) or predicate calculus (MRS) to develop “intelligent” programs. Lot’s of research was done on knowledge representation and tools to support knowledge based engineers in developing applications that by nature required heuristic problem solving. Heuristics are necessary when problems are undefined, non-linear and complex. Deciding which financial product you should buy based on your risk tolerance, amount you are willing to invest, and personal objectives is a typical problem we used to solve with AI.
Fast forward 25 years, and AI is back, has a new name, it is now called cognitive computing. An old friend of mine, who’s never left the field, says, “AI has never really gone away, but has undergone some major fundamental changes.” Perhaps it never really went away from labs, research and very nich business areas. The change, however, is heavily about the context: hardware and software scale related constraints are gone, and there’s tons of data/knowledge digitally available (ironically AI missed big data 25 years ago!). But this is not what I want to focus on.
At a CIO roundtable that Forrester held recently in Sydney, I presented one of my favourite slides (originally seen in a deck from my colleague Ted Schadler) about what has happened r.e. technology since January 2007 (a little over five years ago). The slide goes like this:
Source: Forrester Research, 2012
This makes me wonder: what the next five years will hold for us? Forecasts tend to be made assuming most things remain the same – and I bet in 2007 few people saw all of these changes coming… What unforeseen changes might we see?
Will the whole concept of the enterprise disappear as barriers to entry disappear across many market segments?
Will the next generation reject the “public persona” that is typical in the Facebook generation and perhaps return to “traditional values”?
How will markets respond to the aging consumer in nearly every economy?
How will environmental concerns play out in consumer and business technology purchases and deployments?
How will the changing face of cities change consumer behaviors and demands?
Will artificial intelligence (AI) technologies and capabilities completely redefine business?
OK, it’s time to stretch the 2012 writing muscles, and what better way to do it than with the time honored “retrospective” format. But rather than try and itemize all the news and come up with a list of maybe a dozen or more interesting things, I decided instead to pick the best and the worst – events and developments that show the amazing range of the technology business, its potentials and its daily frustrations. So, drum roll, please. My personal nomination for the best and worst of the year (along with a special extra bonus category) are:
The Best – IBM Watson stomps the world’s best human players in Jeopardy. In early 2011, IBM put its latest deep computing project, Watson, up against some of the best players in the world in a game of Jeopardy. Watson, consisting of hundreds of IBM Power CPUs, gazillions of bytes of memory and storage, and arguably the most sophisticated rules engine and natural language recognition capability ever developed, won hands down. If you haven’t seen the videos of this event, you should – seeing the IBM system fluidly answer very tricky questions is amazing. There is no sense that it is parsing the question and then sorting through 200 – 300 million pages of data per second in the background as it assembles its answers. This is truly the computer industry at its best. IBM lived up to its brand image as the oldest and strongest technology company and showed us a potential for integrating computers into untapped new potential solutions. Since the Jeopardy event, IBM has been working on commercializing Watson with an eye toward delivering domain-specific expert advisors. I recently listened to a presentation by a doctor participating in the trials of a Watson medical assistant, and the results were startling in terms of the potential to assist medical professionals in diagnostic procedures.