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Comment I'm no patent lawyer.... (Score 1) 202

...so I might be wrong. But even if they did have the foresight in 2003 to describe the exact technology of Podcasting (as executed in iTunes) before there was prior art for the idea, doesn't existing patented technology utilizing their structure (i.e. iTunes) nullify their claim? Or does the fact that they applied BEFORE there was prior art give them a "first-come-first-serve" access to the patent?

Either way, I assume we've got ourselves a cute little patent-troll baby developing here.

Comment Re:Just two words (Score 3, Interesting) 395

Hmmm.. I've got 13 peer reviewed Neuroscience publications under my name, 1 book chapter in press, 2 articles in submission (one to Nature Neuroscience and one to Neuron), and several published and unpublished custom-written toolboxes for analyzing brain imaging data. I guess my Ph.D from UC Berkeley also ads to my geek-credit.

That said, Critchon was trained as a clinician through and through, not scientist. From what I can find, most of his non-fiction work in peer-reviewed journals is a review or meta-analysis. So he might have dabbled in programming and such (to give him some geek cred), I think he knew only the gist of the science he used in his popular works. He was by no means an expert.

Comment Re:Just two words (Score 2, Insightful) 395

Andromeda Strain wasn't written by a geek! It was written by a cheeky medical doctor who (like all clinicians) thinks he knows science, but really just knows how to read abstracts. No way a true geek would create Jeff Goldblum's horrifically bad mathematician character in Jurassic Park!

Comment Re:Yes, it is (Score 1) 276

Both methods require an extensive training set. The only difference (that I can see) between the two is that the Japanese model assumes the representational structure of the underlying cortical areas being recorded (i.e., the size of the receptive fields), whereas the Berkeley group trains a simple linear classifier. Expect a few more of these classifier methods to come out in the next couple of years.

Anti-Terrorist Data Mining Doesn't Work Very Well 163

Presto Vivace and others sent us this CNet report on a just-released NRC report coming to the conclusion, which will surprise no one here, that data mining doesn't work very well. It's all those darn false positives. The submitter adds, "Any chance we could go back to probable cause?" "A report scheduled to be released on Tuesday by the National Research Council, which has been years in the making, concludes that automated identification of terrorists through data mining or any other mechanism 'is neither feasible as an objective nor desirable as a goal of technology development efforts.' Inevitable false positives will result in 'ordinary, law-abiding citizens and businesses' being incorrectly flagged as suspects. The whopping 352-page report, called 'Protecting Individual Privacy in the Struggle Against Terrorists,' amounts to [be] at least a partial repudiation of the Defense Department's controversial data-mining program called Total Information Awareness, which was limited by Congress in 2003."

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