darthdeus

Joined 16 years ago

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1,135
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106
Member since
Dec 24
[ my public key: https://keybase.io/darthdeus; my proof: https://keybase.io/darthdeus/sigs/urv8G4cvL0RRyVXcmYD22qnzKBPPUwK7b-a0LhIdEjI ]
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Recent submissions

Comment · 2 years ago
Author here, sorry about that, I just deployed a fix, should be readable now. If it's not, here's the first few points

- Once you get good at Rust all of these problems will go away - Rust being great at big refactorings solves a largely self-inflicted issues with the borrow checker - Indirection only solves some problems, and always at the cost of dev ergonomics - ECS solves the wrong kind problem - Generalized systems don't lead to fun gameplay - Making a fun & interesting games is about rapid prototyping and iteration, Rust's values are everything but that - Procedural macros are not even "we have reflection at home" - ...

the list corresponds to the titles of sections in the article.

Comment · 3 years ago
Comment · 3 years ago
build.rs is a source file that you can audit. A binary that has no reproducible build is not auditable even if anyone wanted to.

A single person does not audit all of their dependency tree, but many people do read the source code of some if not many of their dependencies, and as a community we can figure out when something is fishy, like in this case.

But when there are binaries involved, nobody can do anything.

This isn't the same as installing a signed binary from a linux package manager that has a checksum and a verified build system. It's a random binary blob someone made in a way that nobody else can check, and it's just "trust me bro there's nothing bad in it".

Comment · 5 years ago
Stan gives you the ability to do probabilistic reasoning. There is actually Tensorflow Probability (https://www.tensorflow.org/probability) which has a lot of overlapping algorithms, but isn't as mature and approaches some things differently.

The main difference is that with Stan you think in terms of random variables and distributions (and their transformations), while with Tensorflow/DL you think in terms of predicting directly from data. Stan lets model a problem with probabilities and do arbitrary inference, generally asking any question you want about your model.

There are many other interesting alternatives, e.g. http://pyro.ai/ which takes a yet another approach merging DL and probabilistic programming with variational inference. (Stan and TFP can do variational inference too, but I guess it's like Python vs JavaScript vs Ruby vs Java - all of them can be used for programming, but not the same way).

Comment · 8 years ago
VIM, and overall just being fast. It is extremely perceptible, especially if you ever use something like Arch Linux + st (or one of the faster terminals). iTerm is slow as shit compared to that.
Comment · 10 years ago
You mention you wrote most of the parsing yourself. Is there any reason why you didn't use something like LLVM to do the heavy lifting?
Comment · 10 years ago
In that case you have a much bigger problem :P

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