Lexalytics Development Blog

Or perhaps that should be “Jeopardy, my dear Watson”. By now, you’ve hopefully heard of the IBM project called Watson to develop a computer capable of competing on the quiz show Jeopardy. Scratch that, not just competing, but competing against two of the best players the show has ever had. And, if Watson works as designed, beating them.

I’ve been a fan of Jeopardy since I was a kid, so that angle of the story interested me from the start. But watching segments on NOVA about the project team addressed the challenges in developing a machine capable of understanding human language, it struck me as very relevant to the challenges we face in text analytics engine. If you haven’t heard much about Watson, I highly recommend the video “Building Watson – A Brief Overview of the DeepQA Project”. Without a doubt, Watson goes far beyond the applications we are dealing with. But there is synergy (buzzword bingo score) in the fundamental building blocks and approach, and it’s very exciting to see where this can all head. Here’s some of the core problems text analytics problems that Watson faces, and how they relate to us.

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Most of my blog posts have been technical in nature. But it’s Friday, why not switch things up a bit. I just went down the street to grab some lunch, a grilled roast beef sandwich with crispy onions. That’s not the point of the story, just reminding myself to write this post fast before it gets cold. What I wanted to talk about was what I observed as I was waiting for my sandwich, and the relationship I drew to some of the challenges software engineers have when developing applications, particularly ones in our industry where you have a flow of content that may need multiple stages of interaction. Hungry? Read on.

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