Interesting to ponder the question of how good you have to be at something to make a living off of it.

programming: not good at all

basketball: being in the top 99.99% is probably not even sufficient

touhou: probably not possible?

watching anime: ???


Done with school forever (literally!)💯 💯


subtoot Show more

A touching and insightful romance anime, but in the middle of the film the protagonist orders a cheap and convenient Uber™️ where the driver offers them a refreshing Sprite Cranberry™️. The movie then continues as if nothing had happened.

Me, to the liquor store owner, who is carrying a box of 50+ bottles of Barefoot: "You must sell a lot of Barefoot"

Him: "Yeah, it sells really well"

Me: "Interesting"

Him: "Not really, shit tastes terrible"


#Haskell Show more

#Haskell Show more


The key to a good Mastodon home timeline: show no boosts

If I'm bored or need new people in my network I go to the federated timeline, shudder for 2 or 3 minutes straight, and go back to my home timeline where I only see things originally posted by people I follow

9:00 wake up
10:00 project meeting with professor
10:30 start project work
12:00 quick gym session
12:30-21:00 back to work, I guess

Going to build a new computer in a few months, not sure if I should buy an Nvidia or AMD card. NV has better deep learning support, but AMD seems much easier to deal with on linux.


Meanwhile, inside the box, Schroedinger's cat plans its revenge:

When you don't write down typing rules, much less prove the soundness of them before implementation :uwu_cirno:

Finna go off on implementing this linear type system

Once I wrap up all of my compilers/optimization work, I think I'm going to do something with FRP/streaming libraries. Maybe a game written in Elerea? machines also looks really cool.

I did some work analyzing options pricing data at my previous job and just used FRP and HMatrix, and it was not too bad! Much safer than Python but still conceptually very simple.

I think Haskell's streaming, parsers, and optics story is so far ahead of Python that having a flat, value-level column store is not really that necessary.

A lot of effort in goes toward trying to make a pandas-like column data store, and it always tends to be a bit heavy on the template Haskell and typelevel tricks. I feel emulating Python is probably the wrong way to look at the problem.


I've had the opportunity to see researchers and systems integrators (let's call them programmers lol) work together and create some amazingly effective systems doing things that nobody thought were possible.

I'm thinking of all this because I think this spectrum, between mechanic and mechanical engineer, between maker and theoretician, is also present between programmers and computer scientists.

And that's a clue to why people ask computer science questions on programming interviews.

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