Building a better world, with math.

MathHarbor was literally the love of my life.

I kid you not. For two years, I lived, ate, breathed this idea of mine, that grew from being a simple idea off the top of my head, into an actual venture that went ahead, raised a bit of money, managed to get some traction, and actually built a decent product.

But. We faltered. And after months of analyzing where we went wrong, we now know where we want to go, what we want to be.

This post isn’t about going through what went wrong, and what we’re taking away from it. I feel some things are best left private. What matters, in my opinion, is where we go from here.

Going forward, we’re making a number of changes to what we do.

1. For now, we’re shutting down our computing platform. We feel it’s run its course, and we can’t continue to support it, from a financial and technical perspective. If you had an account with us, you’ll receive an email shortly, with instructions on accessing your models and data. In the meantime, we encourage you to check out the Sage Cloud, which is an excellent platform for computational mathematics, and hopefully, something we can partner up with, in the future. We’re also shutting down our website for a couple of days, while we do a bit of redesign, and move it to another cloud of ours.
2. We intend to invest more in spreading awareness about open-source scientific and technical computing; the biggest bar to using open-source is the fact that a lot of people don’t know about it, and don’t feel comfortable with it. Our goal is to lower that bar, and we’re going to do that with expanding online courseware, that are get-your-hands-dirty video lectures on using open-source languages, libraries and toolsets for solving real-world problems across the sciences, arts, finance, and more. We would of course, charge nominal amounts for these courses, to help support their development In addition, we’re pleased to say that we’re partnering up with JuliaBox, in order to spread the awesomeness that’s inherent in the Julia language. It’s a very, very powerful language for science, and we want to make sure it reaches as many people as possible.
3. Lastly, we believe that math and data science are extremely powerful tools to solve a lot of social problems. To this end, we’re putting together a framework that allows us to support fellowships, which pair the best computational scientists, with non-profit and governmental organizations trying to solve problems that affect communities across urban and rural spaces. We also plan to start India’s own version of SciPy, the popular scientific Python conference, but on a broader scale, incorporating more languages and tools in the mix. We’ll have more on this later, as we intend to relaunch MathHarbor at the Construkt Festival in Bangalore, in the latter half of February.

It’s a good time, to be computational. Let’s build a better world together, with math.