I was recruited as a fresher at Infosys and had to leave the company after training in Dec. 2008 due to recession starting to set in by the time i completed my 6 months training.

I thought finding a new job would be very hard as the market was not so good but to my surprise, i found a new job within 1 month and started working at an Ahmedabad based startup as an iPhone Developer and now after 2 years, i have developed more than 15 iPhone apps and have learnt enough at my company to start my own.

It was painful to leave Infosys then but looking back, i can say that it is the best thing that has happened to better my career. My friends at Infosys who joined along with me now have mixed reactions about the company as not all of them got into desirable roles and many ended up doing support work and they often tell me that you got out of the company at the right time.

So yes, from my own experience, i can say that a startup is a much better place to work even if the salary is low (the learning experience more than makes up for it) than some large MNC where you wont even know how the module you worked on is being used (or not used at all).

I'm digressing a bit here, but with regard to the last paragraph:

> we were writing a gender classifier to categorize people as males/females based on first name and last name (this forms an important part of any social media monitoring product). The most common way to achieve this is through Machine Learning approaches. Gunaa tested his algorithm on a random data set (~22000 unique names if I recall correctly) and achieved 62% accuracy on the classification (awesome!). although THAT meaning might seem less apparent from the conversation above :P

Isn't 62% ridiculously bad? I would expect a naive Bayesian classifier trained on first names to do much better than that. Am I missing something here?