Here are this morning's top news headlines…
- Crooks: In his first interview since going to jail, Bernie Madoff says that the banks he worked with "had to know" of his massive fraud. [NYT]
- Cycling: Lance Armstrong is retiring for a second time. Tell that to Brett Favre. [ESPN]
- Wall Street: A source tells CNBC that the Nasdaq is reassessing its strategy and 'won't sit on the sidelines,' following the news of the NYSE/Deutsche Boerse Merger.
- Business: Borders Books has filed for Chapter 11 Bankruptcy protection. [Deadline]
- Dogs: Hickory, a Scottish deerhound, won best in show at the Westminster Dog Show last night. [HuffPost]
- Technology: During last's second man vs. machine episode of "Jeopardy," Watson lit up his human challengers, but absolutely failed the Final Jeopardy question in a complete botch job that was hilarious. Watch the video, and read IBM's explanation for the total FAIL, after the jump.
The explanation from IMDB:
David Ferrucci, the manager of the Watson project at IBM Research, explained during a viewing of the show on Monday morning that several of things probably confused Watson. First, the category names on Jeopardy! are tricky. The answers often do not exactly fit the category. Watson, in his training phase, learned that categories only weakly suggest the kind of answer that is expected, and, therefore, the machine downgrades their significance. The way the language was parsed provided an advantage for the humans and a disadvantage for Watson, as well. "What US city" wasn't in the question. If it had been, Watson would have given US cities much more weight as it searched for the answer. Adding to the confusion for Watson, there are cities named Toronto in the United States and the Toronto in Canada has an American League baseball team. It probably picked up those facts from the written material it has digested. Also, the machine didn't find much evidence to connect either city's airport to World War II. (Chicago was a very close second on Watson's list of possible answers.) So this is just one of those situations that's a snap for a reasonably knowledgeable human but a true brain teaser for the machine.