slightperturb

MRC is hardly an unbiased source of information. Their news group's stated goal is to be the "Leader in Documenting, Exposing and Neutralizing Liberal Media Bias."

From the wikipedia page:

Journalist Brian Montopoli of Columbia Journalism Review in 2005 labeled MRC "just one part of a wider movement by the far right to demonize corporate media" rather than "make the media better." Additionally, Montpoli wrote that "false equivalence is at the very root of MRC’s beliefs."

No, but with gradual attrition due to fundamental disagreements with the new management, I imagine the character of the company will change significantly within the year, if not sooner.

I think you should reconsider your take on that paper 11. It's not "about" Google-- it is the cornerstone work that led to the creation of Google-- and it was written by two academics (PhD candidates at Stanford). In your previous post, you mentioned "the somewhat vacuous atmosphere of an universities[sic] thinking". But you need to step back and realize that this paper is showing that the university environment led to the creation of the key ideas behind Google, and thus I don't see justification to call it a "vacuous atmosphere".

In fact, I believe what Google is doing so well (and what is attracting great academic researchers like Hinton) is the creation of the rich and rewarding atmosphere mimicking that of classic academia. (And at the same time, cuts to education and research budgets are helping to erode the benefits of a life in the academy.)

Of the most-cited 20 papers in CS (from citeseer), the affiliation of the first author of all but four is with academia:

Academia --------

1) Maximum likelihood from incomplete data via the EM algorithm, 1977. Dempster, Harvard.

2) Communicating sequential processes, 1978. Hoare, Oxford at time of publication.

4) Chord: A scalable peer-to-peer lookup service for internet applications, 2001. Stocia, Berkeley.

5) Distinctive Image Features from Scale-Invariant Keypoints, 2004. Lowe, UBC.

6) Induction of Decision Trees, 1986. Quinlan, New South Wales Institute of Technology.

7) Reinforcement Learning: An introduction, 1998. Sutton, UAlberta.

9) Graph-based Algorithms for Boolean Function Manipulation, 1986. Bryant, CalTech.

10) Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment, 1973. Liu, MIT.

11) The anatomy of a large-scale hypertextual web search engine, 1998. Brin, Stanford.

12) A method for obtaining digital signatures and public-key cryptosystems, 1978. Rivest, MIT.

14) A scalable content-addressable network, 2001. Ratnasamy, Berkeley.

15) New directions in cryptography, 1976. Diffie, Stanford.

16) Eigenfaces for recognition, 1991. Turk, MIT.

17) Authoritative sources in a hyperlinked environment, 1999. Kleinberg, Cornell.

18) Indexing by latent semantic analysis, 1990. Deerwester, UChicago.

20) Handbook of Applied Cryptography, 1996. Menezes, UWaterloo.

Industry --------

3) A tutorial on hidden Markov models and selected applications in speech recognition, 1989. LR Rabiner, Bell Labs.

8) Optimization by simulation annealing, 1983. Kirkpatrick, IBM.

13) Snakes — active contour models, 1987. Kass, Schlumberger Palo Alto Research.

19) Fast algorithms for mining association rules, 1994. Agrawal, IBM.