I fail to see how timing and luck isn't a factor. It's more than how popular it was when it launched, many of those languages that are allegedly better had a strong timing disadvantage by either not existing or not…
That would be simplifying too much. There are a lot of external factors for something being popular, like timing, luck, support from big enterprises and leading colleges, inertia and sunk costs. You could argue that…
I'm quite interested in the interactive thread pool (although I assume it works based on conventions of everyone playing nice). Julia seems to have a powerful parallelism model but it couldn't apply it to responsive GUI…
That issue actually doesn't happen with regular elixir, since it's immutable and stateless, the scheduler doesn't wait for the process to voluntarily wield (it's always safe to switch, so it just gives some fixed time…
I didn't go deep on Julia's multithreading, but what he is saying is that Julia uses an MxN threading (I think nowadays if you don't specify it at startup it will just use one for each cpu thread), which is the same as…
>6DOF gyro A gyroscope is used to detect orientation/angular velocity (spinning), the sensor to add the other degrees of freedom is already there in most modern controllers and smartphones (the accelerometer). The issue…
I mean, I had a vita and the gyroscope control was more accurate than the stick for shooters but that's because I'll naturally adjust if it overshoots (if I go to above I'll immediately push slightly down in a feedback…
In my experience with a rift s, even though the oculus touch also has gyroscopes and accelerometers, they only help for a few seconds at most when the controllers leave the camera. Those sensors are just not accurate…
I don't think there is anyone developing packages on pluto/jupyter, so I wouldn't worry about that. The most common method for that should be using an editor like VSCode (which will have some linting capabilities) with…
While that might happen (and probably cause a method redefinition), there is an important convention that helps preventing it: your package must either own the function or at least one of the types used for arguments,…
This video is good explaining the idea behind multiple dispatch in Julia if you have time: https://www.youtube.com/watch?v=kc9HwsxE1OY
Languages with multiple dispatch aren't rare, but a language having it as the core language paradigm, combined with a compiler capable of completely resolving the method calls during compile time, and therefore able to…
Returning a Union of int or float isn't that useful but the point is that Julia is a dynamic language, and if there was no implicit union type it would have to just box the return type into an "Any" box, which actually…
Objects aren't bag-of-functions though (they have state, inheritance, initializers/destructors, interface/abstract classes, classes vs objects and tons of other concepts and patterns) and any complex program can become…
I do wonder if one of the factors is simply the matter of the modern earbuds and headphones becoming so convenient that you never really need to take them out. I used to listen to songs with a wired conventional…
In this case it's not just a library like the wrappers for tensorflow already present in many languages (including python), it's something like a Swift language fork in which the language constructs are analyzed by the…
If they weren't already-made in Julia yes (and a library didn't do the work of composing it and presenting as a monolith, since pretty much all large frameworks like Flux and DiffEq are also made this way). Although…
That seems the start of something pretty amazing, I work on a fintech using Elixir and we usually have to delegate all numerical analysis and ML stuff to python microservices, even models with considerably simple…
That example in Julia would look the exact same since it's a very simple example with just one object/struct and only one version of each function (so it doesn't even need function overloading, let alone multiple…
Elixir is basically Erlang, just like Lisp Flavored Erlang and Gleam (the statically-checked language for the BEAM). The BEAM in general is a very specialized VM, which is why I used as an example, as the Julia compiler…
Yes, I was thinking about someone going many step furthers, like Elixir is for Erlang and the BEAM, someone who disagrees with design decisions of the Julia language but appreciates the compiler's capabilities and the…
While not nearly as mature as the main platforms (like the JVM, .NET, BEAM), the Julia compiler does have some unique features (an extremely aggressive optimizer, a sophisticated type inference mechanism, possibly the…
While you do interface with it all the time, it's not something you'll be thinking all the time, at some point it will be completely invisible even though it's there (unless you're that bored). What will really be a big…
In general, if you code like Python (highly dynamic code with no consideration to performance) it will be closer to Python in speed, and if you code like C/Fortran (completely static, overspecified types) it should be…
"Ever" could be a very long time, and lots of things can happen. For example it might be possible to AoT compile parts of the code (as long as the types are fully defined) to export as a standalone library, and if that…
I fail to see how timing and luck isn't a factor. It's more than how popular it was when it launched, many of those languages that are allegedly better had a strong timing disadvantage by either not existing or not…
That would be simplifying too much. There are a lot of external factors for something being popular, like timing, luck, support from big enterprises and leading colleges, inertia and sunk costs. You could argue that…
I'm quite interested in the interactive thread pool (although I assume it works based on conventions of everyone playing nice). Julia seems to have a powerful parallelism model but it couldn't apply it to responsive GUI…
That issue actually doesn't happen with regular elixir, since it's immutable and stateless, the scheduler doesn't wait for the process to voluntarily wield (it's always safe to switch, so it just gives some fixed time…
I didn't go deep on Julia's multithreading, but what he is saying is that Julia uses an MxN threading (I think nowadays if you don't specify it at startup it will just use one for each cpu thread), which is the same as…
>6DOF gyro A gyroscope is used to detect orientation/angular velocity (spinning), the sensor to add the other degrees of freedom is already there in most modern controllers and smartphones (the accelerometer). The issue…
I mean, I had a vita and the gyroscope control was more accurate than the stick for shooters but that's because I'll naturally adjust if it overshoots (if I go to above I'll immediately push slightly down in a feedback…
In my experience with a rift s, even though the oculus touch also has gyroscopes and accelerometers, they only help for a few seconds at most when the controllers leave the camera. Those sensors are just not accurate…
I don't think there is anyone developing packages on pluto/jupyter, so I wouldn't worry about that. The most common method for that should be using an editor like VSCode (which will have some linting capabilities) with…
While that might happen (and probably cause a method redefinition), there is an important convention that helps preventing it: your package must either own the function or at least one of the types used for arguments,…
This video is good explaining the idea behind multiple dispatch in Julia if you have time: https://www.youtube.com/watch?v=kc9HwsxE1OY
Languages with multiple dispatch aren't rare, but a language having it as the core language paradigm, combined with a compiler capable of completely resolving the method calls during compile time, and therefore able to…
Returning a Union of int or float isn't that useful but the point is that Julia is a dynamic language, and if there was no implicit union type it would have to just box the return type into an "Any" box, which actually…
Objects aren't bag-of-functions though (they have state, inheritance, initializers/destructors, interface/abstract classes, classes vs objects and tons of other concepts and patterns) and any complex program can become…
I do wonder if one of the factors is simply the matter of the modern earbuds and headphones becoming so convenient that you never really need to take them out. I used to listen to songs with a wired conventional…
In this case it's not just a library like the wrappers for tensorflow already present in many languages (including python), it's something like a Swift language fork in which the language constructs are analyzed by the…
If they weren't already-made in Julia yes (and a library didn't do the work of composing it and presenting as a monolith, since pretty much all large frameworks like Flux and DiffEq are also made this way). Although…
That seems the start of something pretty amazing, I work on a fintech using Elixir and we usually have to delegate all numerical analysis and ML stuff to python microservices, even models with considerably simple…
That example in Julia would look the exact same since it's a very simple example with just one object/struct and only one version of each function (so it doesn't even need function overloading, let alone multiple…
Elixir is basically Erlang, just like Lisp Flavored Erlang and Gleam (the statically-checked language for the BEAM). The BEAM in general is a very specialized VM, which is why I used as an example, as the Julia compiler…
Yes, I was thinking about someone going many step furthers, like Elixir is for Erlang and the BEAM, someone who disagrees with design decisions of the Julia language but appreciates the compiler's capabilities and the…
While not nearly as mature as the main platforms (like the JVM, .NET, BEAM), the Julia compiler does have some unique features (an extremely aggressive optimizer, a sophisticated type inference mechanism, possibly the…
While you do interface with it all the time, it's not something you'll be thinking all the time, at some point it will be completely invisible even though it's there (unless you're that bored). What will really be a big…
In general, if you code like Python (highly dynamic code with no consideration to performance) it will be closer to Python in speed, and if you code like C/Fortran (completely static, overspecified types) it should be…
"Ever" could be a very long time, and lots of things can happen. For example it might be possible to AoT compile parts of the code (as long as the types are fully defined) to export as a standalone library, and if that…