joiguru

Very interesting work!

Did you guys get a chance compare with [1]. These seen to be the standard for high-performance not Crypto RNGs.

[1]: https://github.com/DEShawResearch/random123

Location: Virginia, USA

Remote: Yes

Willing to relocate: Yes

Technologies: C, Python, Javascript, HTML, CSS, SQL, Python ML and DL tools, Distributed systems, High performance computing (MPI, OpenMP, OpenACC)

Résumé/CV: Available on request

Email: parantapa at the popular google email service

Education: PhD in CS

I am a general purpose systems person.

I have significant experience developing distributed systems and HPC tools, some of which are backed by state of the art ML/DL methods.

I also have experience prototyping web based UIs to interact with the said systems. However, I am not a frontend developer. The frontends I build are intended to be polished/remade by experienced frontend teams.

Which Python 3.10 and static type checkers much of the benefits of algebraic data types is already available [1].

[1]: https://stackoverflow.com/questions/16258553/how-can-i-defin...

There are two primary criticisms of this move in this thread:

C1) This is just hurting ordinary Russian citizens and serves no other purpose. I empathize strongly with the Russians. But I also empathize with the Ukrainians. Since Russia has nuclear weapons, the only thing rest of the world can do is impose sanctions. Sanctions work in the long run, but they take a long time to show effects. Ukrainians do not have a long time. All of these moves will cumulatively amplify the unrest among common Russian people, giving Putin less time to sit back and let his plan go to work. Will these be enough? Only time can tell. But ignoring the impact of secondary and tertiary effects for the primary negative effects is short sighted.

C2) This is just virtue signaling. Virtue signaling may be a component of this move, but this is business for Cogent. They make money moving data, and Russian money has lost a lot of its value. So I am not convinced this is just virtue signaling, there is definitely a business component.

Because grep is not a "full text search tool".

Full text search [1] is different from regular expression search.

[1] https://en.wikipedia.org/wiki/Full-text_search

Filling out tax forms and FBAR requirements were a pain.

One theoretical objection to this idea is that distances measured have an accuracy limit of Planck length (1.616e-35 meters). So if your number needs more precision then "just mark" step can't be done.

Surprising-ness is a not a good metric to measure social/psychological science research by. Often a statement and its opposite can be intuitive.

If the opposite result was stated here one could have easily come up with many "intuitive" explanations.

What would be the benefits of this over neovim-qt?

In regular natural language, cutting the ball into 5 pieces implies cutting 5 contiguous pieces.

If I say a cake is cut into 5 pieces, no person will consider that each piece contains parts from all parts of the cake.

"cut the ball into 5 pieces" is not the best description. A better one is: 2a. Split the ball into infinite pieces 2b. Divide the infinite pieces into 5 groups

The basic idea is as follows.

Lets say you are building an ML model to decide whether to give someone insurance or not. Lets also assume your past behavior had some bias (say against some group). Now ML model trained on this past data will likely learn that bias.

Part of modern ML focus is then to understand what bias exists in data, and how can we train models to use the data but somehow counteract that bias.

I did the same, for the last 10 years. And now I don't remember 90% of what I did.

Do you have a citation for this? My google searches have led me to believe this to not be true; see [1]

Here is the relevant quote from [1]: "In the context of julia though, compile time type simply do not exist ...."

[1]: https://discourse.julialang.org/t/claim-false-julia-isnt-mul...

One point I have read repeatedly is that Julia is aimed at High Performance Computing (HPC). Another argument I have read repeatedly is how object oriented programming (with its single dispatch) is bad for HPC because of pointer indirections leading to cache misses. This leads me to conclude Julia will be much worse (than well written C/C++) due to its multiple dispatch.

I am a researcher, and this seems incredibly useful for me. Will definitely give this a try when Linux builds are available.

One feature request that I would suggest is synctex support. I can see this to be being useful when writing a paper using LaTeX as well.

Honest question. Why not just use C/subset of C++ with a template language like Python+Jinja2 for meta programming?

Code generation is already popular with popular C++ libraries like protobuf and in game dev.

Performance is the currency which you trade for ease of development, new features, etc.

Ignoring performance comes at a cost to you (server side resources) and your users (device resources). This is why generation after generation devices get more powerful and slower (from user point of view).

It is up to you to find out which point in the performance vs new feature/bugfix tradeoff gives you maximum value.

It is important to acknowledge that this is a conflict between two ethical ideologies: Deontology/Kantian ethics vs Utilitarian ethics. The Deontological argument is that free speech is good, and any effort to curtail it would lead to a domino effect which will be disastrous. The Utilitarian argument is that this curtailing of free speech is acceptable as the alternative is causing more harm than good. Both ideologies have their limitations and criticisms, and there doesn't seem to be any clear winner.

Self contained containers (like singularity) have come up to fill this gap. Since a few years back we have started investing in creating these containers at the end of every project, as it is becoming increasingly hard to depend on dependencies remaining available online indefinitely.

UVA also has a nice Covid19 monitoring dashboard https://covid19.biocomplexity.virginia.edu/dashboards

While I understand the ease of use pure Python provides, I think when manipulating real binary or in memory data, a little bit of C would really simplify and speed things up.

Writing raw C extensions can be a pain, but with Cython or CFFI using C from Python has become extremely easy.

Fascinating language pedantry.