Archive for August, 2006

Doug Fisher is an associate professor of computer science and computer engineering at Vanderbilt University. I came across one of his interviews in which he discusses all about Artificial Intelligence , right from its definition to how it seems to be changing the world.

A ‘must listen‘ for all those aritificial intelligence and machine learning enthusiasts. Following are a few excerpts from the interview. Alternatively you can get hold of the audio as well:

His simplistic definition of AI:

Artificial Intellegence is the study in creation of programs that do what we would regard as intelligent if we saw them in humans and other animals.

When asked about how Artificial Systems actually work i.e. does a scientist need to program all the possibilities into the computer program, he responded as:

Typically No. The scientist has to think about a number of possibilities and think about…most people are familiar with when they took english in school, the idea of a grammar, what it means to be a legal english sentence. We don’t have to teach people all the possible legal english sentences in school but we have to teach them the grammar that they can use to piece together legal english sentences. And a scientist has to look at enough possibilities so that they can get and extract something like the idea of a grammar that the program can use to create, assess and simulate situations that it hasn’t explicitly seen.

The above seems to be one of the best explanations of artificial intelligence and machine learning systems that I have ever come across. On one hand it sums up the core working model of such systems and on the other hand it is easy enough for a three year old to comprehend.

One subtle point brought out in the interview was whether such systems could be trusted, with Doug stating that this surely seems to be one of the issues that has not been addressed.

They can be wrong. Who do you hold responsible if they are wrong. One complication on using AI vs a human. If a human does something wrong you know who is responsible.

In the interview Doug also talks about the various projects where AI is being used. One interesting application, he mentions, is being done at Vanderbilt University where there is a large library of cartoons. The aim of the application is to create novel cartoons by piecing together frames from older cartoons and resequencing them into new cartoons.

Q. How human like could these systems ever get?
Doug: It might be easy for an AI system to pretend to be sad, pretend to be happy or pretend to be emphatic. May be its relatively easy for an AI system to sense sadness in you but it is probably verv very difficult to actually create an AI system that is sad.

Network Laws Round Up

| August 21st, 2006

Sarnoff’s Law

Sarnoff’s Law states that the value of a broadcast network is equal to the number of recievers (viewers/readers). Hence for a broadcast network of n users would have a value of n:

n

Metcalfe’s Law

Originally targeted for the Ethernet Metcalfe’s Law states that the value of a network is proportional to the square of the number of nodes (users) in the network. That is the value of a network having n users would be proportional to n2. Consider a network having 4 users:

Metcalfe's Law

As can be seen (in figure 1a) that each user can connect to every other user in the network which amounts to a total of n*(n-1) i.e. 4*(4-1) = 12 links

Removing the duplicate linkages it amounts to 4*(4-1) /2 = 6 as can be seen in figure 1b.

Ineffect it amounts to calculating the number of diagnols in the n-agon:

Reed’s Law

Reed’s Law states that the value of a network grows exponentially with the size of the network. It is based on the assertion that the value of a network is not measured by the number of users in it but rather by the number of sub-groups that can be formed by the users. Let us consider a network consisting of 3 users:

Reed's Law

As it can be seen in the above figure that the number of possible sub-groups in a network of n users can be calculated by as 2n. Hence a network of 3 users would have 23 = 8 posiible sub-groups. Now this value can be broken as consisting of:

  • sets with (number of users) > 1
  • sets with (number of users) = 1
  • empty set

Since the empty set and sets with only one user don’t count as a valid group the final estimation as per Reed’s Law turns out to be:

2n – n – 1

Refutation Of Metcalfe’s Law

Real world communication networks, in general, grow faster than the linear growth (Sarnoff’s Law) but much slower than the quadratic growth (Metcalfe’s Law). Hence this law states that the value of a communication network of size n grows like:

n log(n)

The basis of this law is that Metcalfe’s and Reed’s Law are based on the false assumption that all connections or all groups are equally valuable.

The defect in this assumption was pointed out a century and a half ago by Henry David Thoreau when he wrote:

“We are in great haste to construct a magnetic telegraph from Maine to Texas; but Maine and Texas, it may be, have nothing important to communicate.”

Zipf’s Law states that if we order some large collection by size/popu;arity then the value of the k-th ranked item will be about 1/k of the first one. Hence by Zipf’s Law the value of a collection of n items is proportional to log(n).

Now let us suppose that the incremental value that a person gets from other people being part of a network varies as Zipf’s Law predicts. Let’s further assume that for most people their most valuable communications are with friends and family, and the value of those communications is relatively fixed – it is set by the medium and our makeup as social beings. Then each member of a network with n participants derives value proportional to log(n), for n log(n) total value.

If we lose our fight against net neutrality, then this law would be more appropriate than Metcalfe’s Law, since then connections between certain nodes in the network would become more valuable than the others.

I wonder what law did Yahoo! and Microsoft use for evaluating the value of merging their IM networks. Any guesses?

Equalizer

MPlayer allows you to apply the equalizer filter which represents a 10 octave band graphic equalizer. The filter has 10 parameters:

g1:g2:g3…g10

which are floating point numbers between -12 and +12 representing the gain in dB for the respective frequency band.

Equalizer settings for Rock would be applied as follows:

$> mplayer -af equalizer=-1:1:2:3:-1:-1:0:0:4:4 song.mp3

Plugin

Since MPlayer seems to be panacea for handling the numerous media formats, enabling MPlayer to work with the browser to handle embedded media seems to be the next step. To enable MPlayer play digital media from websites all you need is the mplayerplug-in.

Happy Streamin…

The First Page On The Web

| August 16th, 2006

With about 25 billion plus pages on the web it sometimes makes you wonder where did it all start. Here is the link to probably one of the first pages on the web and its still online (-: