oxinabox

16 ms·

1.
Deprecating in JuliaLang(invenia.github.io)
1 points by oxinabox 4y ago|0 comments
2.
by oxinabox 5y ago
This is amazingly field dependent. I am from a field where you only cite the most significant tools you use (Machine Learning). E.g. "We implemented this with a neural network build with TensorFlow (cite). We augmented the data using s
3.
by oxinabox 5y ago
I love how this read me is as much about woodwork as it is about software
4.
by oxinabox 5y ago
> in my days at Amazon Web Services, I saw exactly zero instances of major service releases that, in the opinion of customers, crippled or broke the product. ... the PM could go talk to them and bounce improvement ideas off them. Custome
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by oxinabox 5y ago
Right, can't to abstract callable overloads in older versions of julia
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by oxinabox 5y ago
You can't do it with license. It causes more harm than it prevents. See how this played out with the JSON License https://lwn.net/Articles/707510/ We can assume: noone evil took heed -- because they are evil.
7.
by oxinabox 5y ago
My particular prediction for Machine Learning and Data Science is its going to become less and less Python vs R vs Julia. and more like the situation we have for for web-servers. Where basically every language has a solid quality webserver.
8.
by oxinabox 5y ago
Why does Javis use `act!(object, action)` rather than making actions callable structs so you could do `action(object)` ?
9.
JuliaSPICE: A Composable ML Accelerated Analog Circuit Simulator(youtube.com)
7 points by oxinabox 5y ago|0 comments
10.
by oxinabox 5y ago
I think particular nice thing about this is that it is a bundle of nice libraries integrated together well, with nice docs. Those libraries in turn also break down into other nice libraries and so forth (but many don't have does quite
11.
by oxinabox 5y ago
> Since FastAI.jl uses Flux, and not PyTorch, functionality has to be reimplemented. Yes, and? That is how a port is. When FastAI for swift was a thing (is it still a thing?) it was (is?) using Swift For TensorFlow, not PyTorch. https
12.
by oxinabox 5y ago
Claiming a language is bad such click-bait. Even when it is valid, it basically will get a lot of attention from haters and fanboys. It's not a title that leads to interesting discussion.
13.
JuliaCon 2021: Package development: improving engineering quality and latency(youtube.com)
2 points by oxinabox 5y ago|0 comments
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by oxinabox 5y ago
> it's almost indistinguishable from base R (when you're calling it). I am very surprised by this. Given how R is extremely dynamic. and has things like lazy-evaluation, that you can rewrite before it is called with substitute
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by oxinabox 5y ago
> For scripting, interpreted Julia is coming. Citation for this? Julia has had a built-in interpretted since 1.0, in 2017 use `--compile=min`, or `--compile=none` to make use of it. And JuliaInterpretter.jl has been working since 2018. B
16.
by oxinabox 5y ago
Mostly because, without us really thinking about it, implicitly it was predicated on the premise that the founders would remain largely unemployed for about 6-12 months. Even through we were looking for work. And so when most of us found jo
17.
by oxinabox 5y ago
Cool post but kinda dated. It's not wrong as such but of it were written today I would expect a lot more context and depth around various aspects. E.g. Apache Arrow. E.g. Julia's constellation of different dataframe (Tables.jl) li
18.
by oxinabox 5y ago
For most intents and purposes one can use a (potentially Singleton) type passed as a argument to functions instead of a module containing functions. And doing that gets you all the tooling and power you could want. (But probably in a differ
19.
by oxinabox 5y ago
Window registry issues have been a thing. I have heard it is to do with how windows antivirus works. Since the registry is like 10,000 seperate files. It chokes on them. I have heard there is an upcoming feature to allow the package manager
20.
by oxinabox 5y ago
Since 0.7 (which was 1.0 with deprecations) In julia 0.6 and before it was exactly as bad as described. (though there were things like Playground.jl to kind of work around it)
21.
by oxinabox 5y ago
> This is not my experience. Even if you code without caring about performance it is way faster than Python. It is very usecase dependant. If your Python code is writing lots of loops and scalar processing then naive julia code will tras
22.
by oxinabox 6y ago
> Your observations in V.B.4 are pretty well understood in circuit design. Indeed, I am actually surprised the paper doesn't include something like _"This is inline with the well known result for progressive sizing [cites textb
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by oxinabox 6y ago
1. yeah these are super expensive. Even the cheaper ones are close to a grand a liscense 2. definately got to have a front-end. Writing netlist by hand is suffering. 3. Interestingly (to me) the components are more or less portable between
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by oxinabox 6y ago
Scientific and technical computing. --- Not saying you can't do this stuff in rust. I mean its turing complete. But contrast the description of Rust: A language empowering everyone to build reliable and efficient software. vs Julia Jul
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by oxinabox 6y ago
Something like that is the idea. Silicon area is what costs money. Use as little as possible while still being fast enough to beat the clock-rate of your system. PSO's are way better than brute force. but yeah. It was a purely academic
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by oxinabox 6y ago
fair enough. I can't say i've seen inside how things things are made. Julia definately has cutting edge for DEs. I doublt LTSpice does, but ORCAD etc might.
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by oxinabox 6y ago
A modern circuit simulator, that has a fully featured programable API, that can be run from a real modern programming language, would be a dream. Every simulator i have used has been pretty limited in that way, or at least those features we
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by oxinabox 6y ago
This seems very promising to me One big part of circuit simulation is solving differential equations. That's the whole inducer, resistor, capacitor thing. Julia has hands down the best toolkit for differential equation solving. Most ci
29.
by oxinabox 6y ago
Strong agree. I will use the command line for basics, commit, push, pull, simpler rebases. But it I am going to be cherry picking a commit onto a backport branch, or splitting up one branch into two, or doing an interactive rebase, or (as s
30.
Julia plugin for the datax LaTeX package(github.com)
5 points by oxinabox 6y ago|0 comments

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