<html><head><meta http-equiv="Content-Type" content="text/html charset=windows-1252"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;">Of course, but imagine the nature of the problem if you didn’t have the focus provided by the theory — you know what the needle in the hay stack is supposed to look like.<div><br></div><div>The brain project intends to simply construct the hay stack (literally).</div><div><br></div><div>Furthermore, there isn’t any ‘force” (I apologize) like selection in the biological sense, organizing the structure of your data. Another (of many) soap boxes I can get on, is that lack of comparative and evolutionary thinking in neuroscience - made much much worse now by ‘Translational” science.</div><div><br></div><div>So, your big data sorting problem might be more significant than ours, if we had the right kinds of models.</div><div><br></div><div>I would love to find that out.</div><div><br></div><div>Jim</div><div><br></div><div>BTW, I am very aware that the NN efforts have resulted in technology that is, in fact useful. This has been pointed out by several “off list” comments I have gotten along the following lines:</div><div><br></div><div><blockquote type="cite"><div dir="ltr">The big difffrence is that now we justify the "neural" nets not by the hope that they are brain like but by the fact that for a growing number of tricky computations they work better than any of the alternative technologies.</div></blockquote><br></div><div>to which I replied:</div><div><br></div><div>Absolutely and no doubt - I love the voice recognition on my iPhone<div><br></div><div>However, did getting there really require, intellectually, the faux neuroscience argument - or was that only a way to rally the troops and get the generals to pay :-) (My brain still doesn’t mess up as much as Siri does, but it is getting closer :-), I wish she also knew how to wash the dishes or balance the grocery bags :-) )</div><div><br></div><div>And BTW, I actually found the NIPS meeting to be much more honest than in the old days - little faux neuroscience - turns out a visit by Zuckerburg is more than enough to rally the troops. :-)</div><div><br></div><div><br></div></div><div><br></div><div><br><div><div><div>On Jan 25, 2014, at 3:57 AM, Balázs Kégl <<a href="mailto:balazskegl@gmail.com">balazskegl@gmail.com</a>> wrote:</div><br class="Apple-interchange-newline"><blockquote type="cite"><blockquote type="cite">Forbes magazine estimated that finding the Higgs Boson cost over $13BB, conservatively. The Higgs experiment was absolutely the opposite of a Big Data experiment - In fact, can you imagine the amount of money and time that would have been required if one had simply decided to collect all data at all possible energy levels? The Higgs experiment is all the more remarkable because it had the nearly unified support of the high energy physics community, not that there weren’t and aren’t skeptics, but still, remarkable that the large majority could agree on the undertaking and effort. The reason is, of course, that there was a theory - that dealt with the particulars and the details - not generalities. <br></blockquote><br>I agree with you on your argument for needing a model to collect data. At the same time, the LHC is also probably a good example for showing that even with a model you end up with huge data sets. The LHC generates petabytes of data per year, and this is after a real-time filtering of most of the uninteresting collision events (a cut of roughly six orders of magnitude). Ironically (to this discussion), the analysis of these petabytes makes good use of ML technologies developed in the 90s (they mostly use boosted decision trees, but neural networks are also popular) .<br><br>Balázs<br><br><br><br>—<br>Balazs Kegl<br>Research Scientist (DR2)<br>Linear Accelerator Laboratory<br>CNRS / University of Paris Sud<br><a href="http://users.web.lal.in2p3.fr/kegl">http://users.web.lal.in2p3.fr/kegl</a><br><br><br><br><br></blockquote></div><br><div apple-content-edited="true">
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