Wednesday, October 31, 2007

Learning from United States of America

When I was in my undergrad in India sometime in 2001-2002, our college Principal Narasimha Reddy said "Go to America and learn the work culture". Recently in 2007 at a workshop on "Computer Vision applications for developing countries" that was in conjunction with ICCV in Rio de Janeiro Brazil, Ramesh Jain gave a talk in which he mentioned how the research in developing countries like India is aimed at working for USA since most researchers focus on publishing in conferences, journals run by USA which address problems pertinent to socio-economic situations of typical developed countries.

OK. The longer I stay in America the deeper my appreciation of America grows. What can we (developing countries) do to really learn from it? Ideally we want to learn the underlying process that generates the American success. We typically use observed data to learn the process: an inverse problem. We need data that can truly characterize American success. If we use wrong data no matter how strong our learning algorithms are, we are bound to learn wrong concepts. Typical problems that we run into in learning are that the data acquired is too noisy and even corrupted by unwanted signficant processes. So to be efficient in learning from USA we need data as little corrupted as possible. To acquire such data:
  • One needs to have a first hand experience of life in USA.

  • One needs to be open and courageous so that he actually collects the data.

  • Should interact with atleast a few elite Americans not necessarily personally but through different media like reading articles, blogs and working etc.

  • I say elite because they minimally corrupt the data. And if you encouter a few of them it's good enough to learn the ground truths and you can peel off layers when interacting with average or below average Americans.

  • Check objectively if you are able to learn. A good test is to check if you like America more than just for money and comforts. Understand that I am not preaching money is not important I am just saying it is not the causal variable for deep dynamics. It's how we use money that matters.

  • Periodically "smooth" your data by re-interpreting past experiences.

Just a side-note. Nobody is perfect. America has its faults but it is actually a worthy leader in doing what matters, that is struggling for ensuring longterm human survival. Doing nothing is trivial and doing things by being all powerful is also trivial. What is non-trivial is understanding the dynamics with constraints.

My expressions in last paragraph are influenced by my regular reading of Scott's blog. Especially the "trivial/non-trivial part" and "the doing what matters thing"s.

Note: I edited this post so many more times than any other posts after publishing.

Sunday, October 28, 2007

Survival using science

Pure math is not very useful. Pure mathematicians publish results among themselves and never really get used. Applied mathematicians and engineers make the world.

We hear such statements from time to time in academia. Typically one perceives something to be useful if one can ensure survival through it. It's true that not many can survive in pure mathematics because it is so damn tough. Here I should mention that typically abstractions higher than one's level of imagination are considered "pure" by him. Pure is rather a spectrum of higher abstractions. In fact the higher the abstraction the higher are the chances that the results can survive through odds or in other words stand the test of time. I encourage to read this article and this one to get a nice perspective on math.

Conferences are a good way to measure the progress and importance of a field. For e.g. conferences on aritificial intelligence kind of died but several of them are budding again. Hence participating in conferences is a big treasure to learn the dynamics of a field. If you can actively participate in conferences of a particular field it means you possibly can be fit in the survival sense in that field. You can always learn not only from active participation but also from passive participation. By passive participation I mean being mostly a spectator. Conferences' radiance can be measured in different dimensions like by rigor (typical pure math conferences), immediate impact (engineering conferences), deeper impact (theoretical conferences), commercial impact (industrial conferences). Even though you survive using one class of conferences it always helps to gain edge benefits by being aware of the dynamics of other classes.

After all people in academia struggle to survive primarily using science. It's important for one to have broader awareness if he wants to survive the real significant dynamics. The deeper or steeper one's understanding is the higher are the chances of his survival in times of crisis. Rationality is sufficient when things are smooth, rationality with rigor is necessary when sailing through rough waters.