Easier said than done of course!

When one talks about photo sharing sites, Flickr cannot be left out of the conversation. I was thinking about how fundamentally the two approaches differ. What it boils down to is – the former using computing power and the later using the social computing power of the web to make images searchable.

So I wonder which is more accurate and what kind of results would one produce versus another?

One thing is for sure; computers can recognize but not interpret.

But that did not stop Karan Goel and Avichal Garg from making a business plan out of it and to top that will the Edward L. Kaplan New Venture Challenge award. Now that being said four key observation I could make quickly were:

1. They were very close to the problem and understood the pain. This understanding of the problem, most likely (only guessing), made them passionate about solving it.
2. They had a very focus problem to solve. Not trying everything to save the world, but just one problem which they seemed to have addressed very well.
3. Technology that enabled them to leap frog into the already established market. Luck for them they did not have to create the market.
4. Market timing – The number of people taking SAT and other exams like these is growing at a significant rate. More people, different needs and there is never a one size fit all.

Technology applied in a clever way to solve everyday problem and at the same time make good business sense is essential my aphrodisiac.

Best of luck to www.Prepme.com

Interestingly NPR’s Science Friday (definitely my favorite radio show), had a discussion on this topic recently and many of my observations are in fact real concerns. The study discussed in the program was focused on China. If Chinese start consuming at the rate which Americans consume, we will have a huge short fall in less than 20 years. One of the examples was of oil. Current world production is 83-85 mil barrels/day. By 2020 China alone will need 90 mil + barrels/day and production of oil will not get any higher that current levels. This is just one commodity. If China starts consuming paper like the US, we will have to wipe out the forests of the world. Not ideal for our sustenance to say the least.

So what can we do? I think the answer is two fold. On one end of the spectrum we have to implement global policies, which needs bold leadership (no were in sight!) and at the grass root level each individual will have to become more environment friendly. It means more than separating recyclable stuff from regular thrash; it has to be imbued into our everyday life. Don’t leave the tap running while shaving. Don’t print anything that is not necessary. Don’t drive if you can walk or use a bicycle. Use energy efficient cars…So many thing and there very little things can have a huge impact.
But we are so reluctant. Why?

Now the the Index is expensive to maintain and keep updated and I think has the biggest est value. So what happens when Amazon, opens its A9s search engine indexes to anyone who cares? They have taken Google’s most valuable asset and made it a have just commodity, thus making it possible for anyone to try to improvise on the search algorithms that only big players had the privilege to play with.

So what are the implications? There are many in the ever changing dynamics of on line business, but one side effect is the impact on Data Mining research. Think every School’s CS department having access to a large dataset that they can apply their algorithms and theories on. Hope it aids in accelerating research.

Being so close to academia, why didn’t Google think of this? Probably the same reason Yahoo and MSN did not think of it.

I had the opportunity to attend a colloquium this month, where Dr. Avi Silberschatz, Professor and Chair of the Computer Science department at Yale University gave a very entertaining and interesting talk on some research issues in computer science. The question I pose here was what he asked while giving the talk. But this is one of the most interesting and unsolved problem in data retrieval. I am sure Google among other is working on this problem.

Let us itemize these issue and see how we could solve them. I am not researching in this area so some of it may be naive or already tried.

The challenges of course are:

• Shortlising the movies: This is challenging as the size of the movies are so large and there are so many movies. For starters, if we say “Brad Pitt”, then we can look up the Meta (like IMDB) and shortlist the movies that he acted in, this is easy.
• Then comes the question of how to scan the movies and identify Brad Patt. I think one way is to create and index of the key frame of the movie, and use some AI to do image recognition on each frame (expensive and very difficult). We can use a social software, that can provide the data set to train the AI program that analyzes the frame.
• Some of the analysis can be done offline, i.e. we can analyse a the key frames and extract known objects (car, horse, cat, man, woman, etc) and index them. Further analysis of each object can associate addtional attributes to these know object like (white car, brown horse, etc).

Well really, there are many issues and as Dr. Avi said, if you do not want to graduate, this is a good problem to solve. How can I do it any justice in a small blog post! But it is a very interesting question. An really fun to work on..

Like “Setup WP with a most popular image gallery” and it can translate to defaults and ask for specifics if needed. We are close with inivisual applications being able to run wizards, but integration is still hell. Dream on about SOA.