Data art is anti-dada.
161 karma · joined May 14, 2012
Don't worry, we've all been there.
When people see for example, * or + (or a, b, c). They may have some preassumptions about some implied associativity from arithmetic (depending on what they are taught and what level of math they are at), that may be hard to break. If you have learned some college (abstract) algebra, it may mean something quite different. How about the = sign? Of course, a, b, c may be meaningless to someone who is not a native latin-1 speaker either. My point I guess is that these are just matters of convention, there is just some implied commutativity or associativity usually implied, but this is all arbitrary.
Now, one intereting "quirk" with with PL/I was that certain things looked similar "to what people were used to" (relative to say other PL/I code, or FORTRAN or COBAL), but worked differently even in some small spatial area on a screen (two blocks of nearby code in some editor). For example, if the programmer's eye saw a block of code, reflexively, depending on their experience they may be able to predict what the result of the computation could do. PL/I was an interesting experiment because of the lack of reserved keywords. This made it very expressive but very hard to understand code in context. For example, in pseudo PL/I: foo = 1; = = 2; bar 2 + foo. You are basically changing the grammatical syntax of the language in 3 lines.
But on the other hand, everything is just a symbol and this may not be completely unusual. Consider the diversity of the world's languages and how they are written and how meaning is derived. Natural language grammars may connotate very different representations and transformations, but people learn because they see enough examples. Consider for the differences between Han, Brahmic scripts, Arabic BiDi, various African scripts, Cuneiform, Emoji, whatever. Perhaps all computer languages are "overfit" due to for example, Chomsky's ideas and BNF (keep in mind Chomsky's ideas about morphology were quite different).
Now, let's consider mathematical notation. Depending on how much pure math (or say, mathematical physics or other sciences) you consider, there may be more and more semantic overhead with the conventions of mathematical notation, and people often historically just "cartesianize" and "euclidized" things for convenience because of lack of tooling (think of a sheet of paper metaphor, we've simply moved it over to a computer. it's a skewmorph). Clearly we have better computer graphics, so why haven't developer tools and languages changed along with it? Maybe with more immersive manipulation they will.
Meanwhile the Oracle vs Google case is still going on.
If you know haskell, Rust's traits are very similar to type classes, except it also has c++-like generics (templates) and is primarily expression-based like ocaml.
traits vs haskell type classes:
trait -> class struct -> data instance -> impl
- Main abstraction are classes (of objects).
- Concept of self-initializing data/procedure objects Internal ("concrete") view of an object vs an external ("abstract")
- Differentiated between object instances and the class
- Class/subclass facility made it possible to define generalized object classes, which could be specialized by defining subclasses containing additional declared properties
- Different subclasses could contain different virtual procedure declarations
- Domain specific language dialects
I haven't seen that in practice. A good point of reference are implementations of things like ruby, python, or the erlang vm in rust compared to the C alternatives. This might be because Rust is also more expressive (probably by borrowing certain syntax/semantics from ocaml/haskell), though the borrow checker does add back some verbosity.
I use fuzzers with a Redex driver usually, which is unusually great at intelligently driving fuzzers: https://docs.racket-lang.org/redex/index.html
Though until the CCPA/GDPR, it was probably fairly legally nebulus. Still waiting for a privacy act in the US. Since it was a wide variety of actors, we may never know who captured what how.
I think companies like Apple who tend to make margin on the hardware and not the information probably are to be commended by pushing a lot of privacy/extra scrutiny requirements through the platforms they control (iOS, mac, webkit, etc).
I like how Julia implemented this (but they use Fortran-like defaults, with clear inspiration from matlab, numpy, etc), with a relatively compact set of functions to do any sort of "index ordering": https://julialang.org/blog/2016/02/iteration/
Rust is very much a child of Ocaml (with a lot of idioms form haskell) with much more control of memory than pretty much any other language (which probably makes it better for implementing complex or safety critical things like optimizing compilers or an operating system). Actually, learning any ML language is probably easier than Rust, but you'll get more fluent at a ML-like (expression based) language like Rust. For me, I felt like I understood Rust way more after looking at how rustc works and started unlearned everything I knew about C/C++.
You can do similar things with other Ocaml or Lispy Langs, depending on how you want to do it. All you need is a function that returns possibleTypeTransitions for givenType(type, enclosedLexeme, type.validTransitions). A gradually typed lang sitting in top of a prototype-based blob also makes this easy to do (see typescript) in-codo.
See also MacKay (RIP)'s classic book: http://www.inference.org.uk/itprnn/book.pdf
I enjoy Rust the days. Modern C++ certainly ain't bad, but nostdlib Rust is also the first serious threat to full spectrum C in a long time.
https://en.wikipedia.org/wiki/Telescript_(programming_langua...
These days, ironically, Telescript is a model for how distributed computation works in the 3rd world, and even in the first world. But Telescript basically would have made the lattice structures more hybridizable to project information and jobs within the context of already existent social networks and maybe provided a better nexus for useful work done vs power given up (it was made on a very astute observation about the energy, work, power, time, information, transmission nexus) before anyone named a "peer to peer network", a distributed consensus protocol, or introduced money into the picture.
Wt is basically Qt for the web. I've used a lot of UI toolkits across many languages, and Qt with modern-ish C++ is fairly productive, doubly so if you're slapping something together for an existing C++ codebase you have.
Sage is a lot larger than Sympy (it's more than 1 million LOC AFAIK), but it still delegates to other libraries to do most types of underlying symbolic and numerical computations.
I usually use sympy (or rather some wrapper of symengine these days) when I'm writing a pure python script, sage otherwise.
For a lot of math and CS courses, I think having some knowledge of some sort of computer-assisted theorem proving. I think the most promising is maybe Lean these days (Coq still might take too long to learn): https://github.com/leanprover-community/mathlib
Works well, I'm guessing for other platforms, similar things exist using remarkable's api.
That being said, there is still room for improvement, particularly with reading (vs writing, which this device is very good at).
I mostly use it this to replace stacks of notebooks (my brain thinks better with pen and paper in hand, but with all the digital conveniences in hand. This device is the best that I've tried for writing (and I've tried many, including an ipad pro)
Cons: historically, the price. No blacklight. Clearly the device has been optimized for writing, not reading, although supposedly 3rd party ebook readers like Apollo are good (the device is not locked down and has a hacker community).
Only caveats - I like aftermarket cases more than Remarkable's. I bought one one from Amazon for about 30$.
Also I've been using staedtler's digital pencils, works great!
https://www.bloomberg.com/opinion/articles/2020-03-10/how-co...
For example: Why was H1N1 allowed to spread around the world more or less unchecked, while countries are going to far greater lengths to try to halt Covid-19? Why did the WHO call H1N1 a pandemic but not Covid-19? Isn’t 12,469 deaths a lot worse than the 26 that have been attributed to Covid-19 in the U.S. so far?
That last one is the simplest to answer: Covid-19 is near the beginning of its spread in the U.S., and thus cannot be compared with H1N1’s effect over a full year. If the U.S. death toll from Covid-19 is only 12,469 a year from now, that will likely be counted as a great success. The legitimate worry is that it could be many, many times higher, because Covid-19 is so much deadlier for those who get it than the 2009 H1N1 influenza was.
How much deadlier is still unknown, but of the cases reported to the WHO so far 3.4% have resulted in fatalities. That’s probably misleadingly high because there are so many unreported cases, and in South Korea, which has done the best job of keeping up with the spread of the virus through testing, the fatality rate so far is about 0.7%. But even that is 35 times worse than H1N1 in 2009 and 2010. Multiply 12,469 by 35 and you get 436,415 — which would amount to the biggest U.S. infectious-disease death toll since the 1918 flu. Hospitalization rates are also many times higher for Covid-19, meaning that if it spread as widely as H1N1 it would overwhelm the U.S. health-care system.
That’s one very important reason governments (and stock markets) around the world have reacted so much more strongly to Covid-19 than to the 2009 H1N1 pandemic. Another reason is somewhat more hope-inspiring. It’s that public health experts generally don’t think influenza can be controlled once it starts spreading, other than with a vaccine, whereas several Asian countries seem to have successfully turned back the coronavirus tide, for now at least.
Influenza can’t be controlled because as much as half the transmission of the disease occurs before symptoms appear. With Covid-19 that proportion seems to be lower, meaning that even though it’s more contagious than influenza once symptoms appear, it may be possible to control by testing widely and quickly isolating those who have the disease.
Oil and other commodities also took a dump.
ruth bader ginsburg is 86 years old, and still seems sharp as a tack.
I think the fact that it's an election year, more people are susceptible to thinking the pandemic is overblown and thus a conspiracy to defeat Trump.
Maybe that's why MERS never spread widely outside of areas where camels don't exist widely.
https://www.reuters.com/article/us-health-coronavirus-usa-po...
Irony.