Innovation, it all starts with jeopardy. Is this a truism? Does all innovation start with jeopardy? There is little doubt that “the risk of loss, harm or failure,” which is the dictionary definition of jeopardy is a component part of why we innovate. The pace of change across most industries, driven by new technology and more open, collaborative and transparent ways of working, means we are all in potential jeopardy. We all need to innovate.
Now. One of my favourite quotes of the moment on this is “You can’t invest in the future, in the future,” we are making the bets today that will define our future selves, our future organisations and the future clients we serve. In another post for this site, How to Avoid the Iceberg, I explore some of the themes of exponential innovation, which carries great relevance here, after all we may often sense we are in jeopardy only when the time to do anything about it is long passed.
I am going to weave in the IBM Watson story, a very literal game of Jeopardy, to hopefully bring this to life. I think this serves as a great narrative for many aspects of our innovation trials and tribulations. If you are not aware of the history of IBM Watson, here is the quick backstory. In 1997 the IBM supercomputer, Deep Blue, famously defeated the then world chess champion, Garry Kasparov. In 2004, researchers chose Jeopardy! as its next conquest and began developing Watson in 2005. Watson was created as a question answering (QA) computing system that IBM built to apply advanced natural language processing (NLP), information retrieval, knowledge representation, automated reasoning, and machine learning technologies to the field of open domain question answering.
The goal was to build an AI supercomputer capable of defeating the two all-time Jeopardy! champions, a feat IBM managed to achieve in 2011 when their AI ‘machine’ the Watson computer system competed on Jeopardy! against former winners Brad Rutter and Ken Jennings, winning the first prize of $1 million.
Observation 1: Our innovation efforts can be great for PR
If we are honest, this is where many of our innovation efforts start and stop. We invest in the shiny stuff, great to showcase to new graduates, shareholders or customers. It might look great, but what value does it derive. Really? This was great PR for IBM, but so what?
The third era of computing?
The mid-1950s, the first era of computing, the tabulating era, brought forth the calculator which could perform basic arithmetic. The 1990’s gave rise to the programmatic era, where machines can process logical structures and “if/then” commands (such as “if not A then B”), but computer scientists must program the rules the computer follows. Watson straddles cognitive computing and programmable computing, harnessing and processing the more than 2.5 billion gigabytes of data generated each day. Its machine-learning capabilities simulate the human thought process, but is built to eliminate the biases and error out of decision-making. “The third era of computing, the cognitive era, starts to breakdown the rigidity inherent in that ‘if/then logic.” Cognitive computing is probabilistic computing, where the outcomes vary along a spectrum instead of being strictly “yes or no, right or wrong.” Sounds great, right? But still, so what?
“We were mainly interested in using Jeopardy! as a playing field upon which we could do some science,” Dr. Chris Welty later said about Watson’s appearance on the game show. “We wanted the ability to use questions that had not been designed for a computer to answer.”
Immediately after collecting the $1 million prize in 2011, IBM set off to apply Watson in real-world scenarios, but to date nothing has really been achieved of any material value.
Observation 2: From minimum viable product (MVP) to scaled product/service delivery is hard, even if you are IBM. Focus is often vital.
Critics say IBM executives overshot badly by allowing marketing messages to suggest that Watson’s Jeopardy! breakthrough meant it could break through on just about anything else. IBM executives are certainly guilty of setting up Watson for failure by throwing the net so wide in terms of application and focus whilst it was still in its infancy. Anyone who has built a first-generation prototype of anything will know the endless pitfalls of trying to rapidly scale off the back of your rudimentary prototype.
Read the full version of the original post at The Future Shapers