Marie Wallace of IBM wrote in from Ireland to call my attention to Languageware, IBM’s latest try at natural language processing (NLP). Obviously, IBM has been down this road multiple times before, from ViaVoice (dictation software that got beat out by Dragon NaturallySpeaking) to Penelope (research project that seemingly went on for as long as Odysseus was away from Ithaca — rumor has it that the principals eventually decamped to Microsoft, and continued to not produce commercial technology there).
By the way — I by no means want to single out IBM’s natural language efforts for especial bashing. The AI industry’s unit of bogosity has long been the “microlenat,” and Doug Lenat’s life work is, approximately, solving natural language access. I sat next to Doug at dinner at an IJCAI/AAAI conference in 1985 or so. So far as I can tell, what he told me about then still hasn’t been delivered in real life. I’m not aware of any connection between Lenat and IBM.
What’s different this time, apparently, is a rigorous focus on performance. Marie and her team seem to believe that what has held natural language processing back in the past has been poor performance. That’s not as crazy as it sounds, since natural language may be one of those artificial intelligence problems in which brute force outperforms sophisticated heuristics (Lenatesque or otherwise). Still, I have to wonder if performance has really been the main problem.
One interesting side note is that a reason given for this great performance is that processing is done in one pass rather than several. Since seems to directly contradict the philosophy of UIMA, IBM’s proposed general-purpose text analytic industry standard. And it’s tough to see how that architectural choice alone can produce enough of a performance advantage to be a game-change.
The link I gave above already has quite a bit of material. Marie tells me that more and/or fresher material is coming soon.