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Posts Tagged ‘Google’

Google wave unveiled

Google just unveiled its new (open source) attempt to change email by combining it with essentially all other electronic collaboration modes (IM, blogs, collaborative editing…) .  Google Wave may completely change how we collaborate electronically.  Or, it may not.

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Wired magazine published a (rather enthusiastic) popular article on Hal Varian’s role as chief Google economist.  It shortly mentions that Microsoft now has Susan Athey in a similar role.

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The new GoogleReserach on Twitter will certainly have some tweets related to algorthmic game theory such as the announcement of the WWW’09 paper “Bid Optimization for Broad Match Ad Auction” by Eyal Even Dar, Vahab S. Mirrokni, S. Muthukrishnan, Yishay Mansour, and Uri Nadav.

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Muthu has announced a new paper “Bidding on Configurations in Internet Ad Auctions” in his blog.

Abstract: In Internet advertising, a configuration of ads is determined by the seller, and advertisers buy spaces in the configuration. In this paper, motivated by sponsored search ads, we propose an auction where advertisers directly bid and determine the eventual configuration.

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A skeptical reader made the following comment to a previous post:

What exactly do all those AGT researchers do to increase profitability?

Shouldn’t we stop pretending that AGT has any relation to the real world?

 The theory vs. practice debate in every field is interesting, but for now just a few quick comments:

1) Actually it seems to me that ignoring the relation of AGT to the real world is pretending.  It is a fact that many companies are interested in this work, whether or not justifiably so.

2) At least what I did for a while in Google can be seen in this paper.

3) While there are a few “deep” theoretical problems in AGT, most of the interest in this young field is actually figuring out the right questions and models.  An early split from the “real world” would make sure that we end up with the wrong questions and models.

4) It seems to me that this comment is part of a game we theoreticians like to play: “we don’t do anything useful — we just pretend so in order to get grant money”.  I don’t buy.

5) However, I can’t resist participating a bit in this game and sharing a strategy of pretending to be useful: when I started working in the econ/CS border I observed a difference in the way economists and computer scientists gave examples.  While in CS examples would look like “Suppose Alice bids $3 for a pair of socks“, economists would give the same example as “Suppose ATT bids $3B for a spectrum license“, which is so much more practical.  My new suggestion for computer scientists is to move to “Suppose Alice the plumber bids $0.003 for an ad slot”, trumping the $3B, I would say.  (Which makes me wonder how many other human inventions function over a range of twelve orders of magnitude like auctions do?)

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Internet advertising is perhaps the number one current application (revenue-wise) for algorithmic game theory, and is paying the salaries of many AGT researchers in Microsoft, Yahoo, Google, and elsewhere.    Beyond the basic “generalized second price auction” used for ad-auctions, there are many other issues and questions involved.  

About a week ago, Google annouced a new beta program for interest-based targeting (a form of behavioral targeting).  The basic idea is very simple: allow advertisers to target ads to segments of people according to their previous Internet behavior and not just the current web-page that they are on.   E.g. if you visit many sports web-sites, the it makes sense to show you sports-related ads even on a general news page rather than, say, detergent ads.  In general, this should result in less annoying (or even actually useful) ads for the viewer, higher effectiveness for the advertiser, and higher revenue for the web-site  “publisher” (and of course, for my own current employer, Google).

Technically, this is quite easy to do using browser cookies, and is already heavily used by most advertising middlemen on the web.   The catch is of course in the privacy issues.  It seems that the main innovation here was in how Google managed to handle the privacy issues, as explained on it’s public policy blog.  The main technical ingredient here is the ads preferences manager that gives viewers full control of their data.

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