Ezra Savard

In the last few months I’ve been studying some extra computer science through edX. Most recently, I have been working through the ColumbiaX AI course , which seems to follow AI AMA pretty closely, at least for the first half. The course has had a few projects, but I really enjoyed the most recent one: writing a search agent to play 2048.

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About two years ago I realised that I needed to stop being insecure. When it comes to insecurity, there are a lot of ideas out there like imposter syndrome that I do not personally resonate with. I gave a lot of thought to what it meant to me to feel insecure and came up with a fairly simple pact that sounds a bit dramatic reading it now.

I will never again feel insecure.

I may feel unsure, afraid or confused, but those feelings have a source and I will answer them.

Insecurity in itself is useless.

Insecurity is the unanswered call to improve myself.

It is the certain knowledge that I am not being my best.

I like how this approach has been working out for me. In particular, I’ve come to appreciate how natural it is to gauge myself against my own ideals, something that I used to fight against. Though I can never reach an ideal (by definition?), I feel great satisfaction in knowing that I am making progress in the right direction.

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As a first step in my undergraduate research on simulating physical quantum annealing, I wrote some Monte Carlo solver. I wrote my first implementation of a path-integral Quantum Monte Carlo (PI-QMC) in Python using numpy linear algebra operations. The code quality was not great though and it was not particularly nice to use. So a few weeks ago, I decided to re-write it as something I would be happy to share with others, so here it is!

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