Our collective f8 (fate) after the “Like” button was released… Google beware…

April 25th, 2010

The like button was released recently to great fanfare. Some loathed it and busily updated their privacy settings. Some welcomed it with a warm embrace. I did not realize its full impact until today, after some distillation of thoughts.

What if these likes are all but a way for us to rank the web pages for Facebook? Whereas Google uses Pagerank to do it by thousands of rack-mounted PC, Facebook just used us. We are like the people wired up to machine in the Matrix, while the candy are spoon-fed to us in the form of friend, sharing, photo posting & so on, the machine quietly aggregates our likes into the biggest human ranking machine ever built.

It is even scarier when people log in and search using this Facebook data backed search engine (let’s called it FaceIt). Imagine yourself being a geologist, your friend circle may also be in the same field and their likes will be similar to yours and therefore act as a very strong ranking mechanism for you. A search with Google may obtain popular articles, but with this FaceIt search, it will be showing results relevant to geologist such as scholarly articles.

I have been thinking about this problem for some time and thought about ways to get to it, but I have to admit that solving it by human filter is a clever way.

The Matrix is here, Neo. Good job, Mark. Sergey may not sleep well now…

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The 12 chairs of Silicon Valley

March 31st, 2010

From my 14 years of professional life in the silicon valley, I have learned some secrets:

  1. Hot chair: when they want you to fail
  2. Cold chair: when you are given nothing to do
  3. Small chair: when you are given a much smaller cubicle than your title
  4. Big chair: Peter’s principle, if you fail, then…
  5. 3-legged chair: somewhat uncomfortable
  6. Musical chair: reorg for 1 month, find a position at end of music, else…
  7. Empty chair: when all your direct reports are gone
  8. Wet paper mache chair: a timed exit
  9. no chair: position eliminated
  10. needle chair: it hurts to stay
  11. merry-go-round chair: job rotation to the Nth degree
  12. see-saw chair: now I see you, now I don’t

Which chair are you on now?

Human capital

March 31st, 2010

There seems to be a shift on linking information (HTML) to linking people (Facebook, Twitter, Linked-in). Has the age old adage been rediscovered again: “It’s not what you know, but WHO you know”. May be because of getting introduced thru a friend becomes a human filter, pre-screening is done free.

Accumulation of information now is less important than accumulation of human capital.

Image representing Facebook as depicted in Cru...
Image via CrunchBase
Image representing Twitter as depicted in Crun...
Image via CrunchBase
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Study in Genesis using Prolog

September 16th, 2009

Do you know that the flood came in the year 1656, the year when the last of the patriachs, Methuselah, died?

The following piece of code tells me that:

born(adam,0).
/*born(X,Year):-
begot_age(adam,Year,X).*/
born(X,Year):-
begot_age(Y,Y1,X),
born(Y,Y2),
Year is Y1+Y2.
die(X,Year):-
born(X,Y1),
die_age(X,Y2),
Year is Y1+Y2.
alive(X,Year):-
born(X,Y1),
die(X,Y2),
Year < Y2,
Year > Y1.
contemporary(X,Y):-
born(X,Y1),
born(Y,Y2),
die(X,Y3),
die(Y,Y4),
Y3 > Y2,
Y4 > Y1.

begot_age(adam,130,seth).
begot_age(seth,105,enosh).
begot_age(enosh,90,kenan).
begot_age(kenan,70,mahalalel).
begot_age(mahalalel,65,jared).
begot_age(jared,162,enoch).
begot_age(enoch,65,methuselah).
begot_age(methuselah,187,lamech).
begot_age(lamech,182,noah).
begot_age(noah,500,shem).
begot_age(noah,500,ham).
begot_age(noah,500,japtheh).

die_age(adam,930).
die_age(seth,912).
die_age(enosh,905).
die_age(kenan,910).
die_age(mahalalel,895).
die_age(jared,962).
die_age(enoch,365).
die_age(methuselah,969).
die_age(lamech,777).
die_age(noah,950).
flood(noah,600).
flood_year(Y):-
flood(noah,X),
born(noah,Y1),
Y is X+Y1.

Man twitters and women facebooks?

August 2nd, 2009

Now I feel better after finding this piece of gem:

My excuses…

The following data are from a November 2007 Rapleaf study:

“Facebook Users
63% female, 36% male
17% <18 yrs, 52% 18-25 yrs, 21% 26-35 yrs, 5% 36-45 yrs, 5% >45 yrs
MySpace Users
63% female, 36% male
20% <18 yrs, 40% 18-25 yrs, 27% 26-35 yrs, 7% 36-45 yrs, 6% >45 yrs
LinkedIn Users
38% female, 61% male
2% <18 yrs, 9% 18-25 yrs, 49% 26-35 yrs, 24% 36-45 yrs, 16% >45 yrs
Friendster Users
58% female, 41% male
12% <18 yrs, 39% 18-25 yrs, 36% 26-35 yrs, 7% 36-45 yrs, 5% >45 yrs
Plaxo Users
62% female, 37% male
16% <18 yrs, 39% 18-25 yrs, 24% 26-35 yrs, 10% 36-45 yrs, 11% >45 yrs
Hi5 Users
60% female, 39% male
21% <18 yrs, 44% 18-25 yrs, 23% 26-35 yrs, 6% 36-45 yrs, 6% >45 yrs”

It may not be the latest but it proved my point.

I rest my case, your honor.

 

 

In a nutshell: 60% of social network members are women and they have more online friends.

To tweet or not to tweet? That is the question.

August 2nd, 2009

Should I succumb to the face (Facebook)? Or should I stay true to my followers on Twitterspace?

My wife has 29 friends now at facebook and I have only 7. Social media envy is running high in this household.

Problem with Twitter is that there is no stickiness. Things are so transient that you cannot go back to original post and edit it. Let’s Face it, FB does do a good job in putting things in context, especially for comments. With status updates and SMS also available, I am not sure what can Twitter do to counter that anymore. May be it can go below the surface and become like email protocols of yonder years. But how can money be made there if things remain so subliminal and cannot sell ads?