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What are the best programming languages for artificial intelligence?
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Jan 29, 2024
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Best programming languages for artificial intelligence
Price
Platforms
Current stable version
--
Nim
-
Windows, MacOS/iOS, Linux /Android/Termux, *BSD, Solaris/SmartOS, HaikuOS, lots of others
2.0.0
--
Rust
-
Linux, MacOS X, Windows, BSD
1.71.1
--
Julia
Free
Windows, Linux, Mac, FreeBSD
1.5.3
See Full List
--
Nim
My Rec
ommendation
for
Nim
My Recommendation for
Nim
All
14
Pros
13
Specs
Top
Pro
•••
Easy to read
Nim has a lot of common with Python in terms of syntax. Indentation-based syntax, for/while loops.
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Specs
Platforms:
Windows, MacOS/iOS, Linux /Android/Termux, *BSD, Solaris/SmartOS, HaikuOS, lots of others
Current stable version:
2.0.0
License:
MIT
CPU:
All CPU architectures that have an ANSI C compiler or JavaScript interpreter
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Top
Pro
•••
Supports UFCS (Unified Function Call Syntax)
writeLine(stdout, "hello") can be written as stdout.writeLine("hello") proc add(a: int): int = a + 5 can be used like 6.add.echo or 6.add().echo()
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Top
Pro
•••
Easy to integrate with another languages
You can use Nim with any language that can be interfaced with C. There's a tool which helps you to create new C and C++ bindings for Nim - c2nim. Also, you can use Nim with Objective C or even JavaScript (if you're compiling for these backends).
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Top
Pro
•••
Type interferencing
You only need to specify types in your procedures and objects - you don't need to specify type when you're creating a new variable (unless you're creating it without initialization).
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Top
Pro
•••
Strict typing
Checks your code at compile time.
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Top
Pro
•••
Great metaprogramming features
There are generics, templates, macros in Nim. They can allow you to write new DSL for your application, or avoid all boilerplate stuff.
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Top
Pro
•••
Has built-in async support
Nim has "asyncdispatch" module, which allows you to write async applications.
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Top
Pro
•••
Has built-in unittest module
With built-in "unittest" module you can create test with a very readable code.
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Top
Pro
•••
Garbage-collected
You don't need to deal with all those manual memory allocations, Nim can take care of it. But also you can use another GC, or tweak it for your real-time application or a game.
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Top
Pro
•••
Built-in Unicode support
You can use unicode names for variables, there is "unicode" module for operations with unicode.
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Top
Pro
•••
Multi paradigm
Imperative, OOP, functional programming in one language.
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Top
Pro
•••
Really cross-platform
The same code can be used for web, server, desktop and mobile.
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Top
Pro
•••
Compile-time execution
Nim has a built-in VM, which executes macros and some other code at compile time. For example, you can check if you're on Windows, and Nim will generate code only for it.
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Get it
here
Recommend
1
--
Rust
My Rec
ommendation
for
Rust
My Recommendation for
Rust
All
21
Pros
12
Cons
8
Specs
Top
Pro
•••
Catch errors at compile-time
Since Rust is statically typed, you can catch multiple errors during compile time. This is extremely helpful with debugging, especially compared with dynamically typed languages that may fail silently during runtime.
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Top
Con
•••
Significant time required to understand the language fully
There's the infamous borrow checker for example.
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Specs
Platforms:
Linux, MacOS X, Windows, BSD
Current stable version:
1.71.1
License:
MIT/Apache
Top
Pro
•••
Built-in concurrency
Rust has built-in support for concurrency.
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Top
Con
•••
Not as useful or productive as advertised.
If really out here wanting to use something besides C/C++, in 98% of use cases, would do just as well or be better off using something other than Rust. Will complete the project faster, would be easier, will be happier, and nearly as safe (use newer language with optional GC).
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Top
Pro
•••
Big community
The biggest community contributing to language.
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Top
Con
•••
Rust not as safe as it pretends to be
Rust problems: 1) Massive undisclosed usage of unsafe. 2) Massive amounts of memory safety CVEs - see details. 3) Large bloated Rust binaries increase attack surface for exploits. 4) Many corporate types claiming Rust is safe, don't actually program or use it (have some quiet financial interest to push it).
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Top
Pro
•••
Support for macros
When you identify a part of your code which gets repeated often, which you cannot abstract using functions or classes, you can use Rust's built-in Macros.
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Top
Con
•••
Low-level programming language
This means that it encourages the programmer to be very careful in terms of how memory is allocated, etc. Most applications can run without exceeding the capacity of the server, even with an inefficient dynamic scripting language.
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Top
Pro
•••
Generics support
You don't have to write same array and dictionary classes hundreds and thousands times for strong type check by compiler.
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Top
Con
•••
Steep learning curve
Pretty strict and hard to adapt for beginners.
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Top
Pro
•••
Threads without data races
Unique ownership system guarantees a mutable data to be owned and mutated by only one thread at a time, so there's no data race, and this guarantee is checked at compile time statically. Which means easy multi-threading. Of course, immutable data can be shared among multiple threads freely.
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Top
Con
•••
Low productivity
The compiler is strict, such as ownership and borrowing checkers.
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Top
Pro
•••
Compiles to machine code allowing for extra efficiency
Rust uses LLVM as a backend, among other things this allows Rust code to compile down to machine languages. This allows developers to write programs that run as efficiently as possible.
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Top
Con
•••
Low readability
Harder to read and understand language.
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Top
Pro
•••
Functional programming
Very easy to create functional with some additional from structure application.
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Top
Con
•••
Long compile times
Way longer to compile than other languages.
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Top
Pro
•••
Easy to write understandable code
While not as verbose as Java, it still is much more verbose than languages like Go and Python. This means that the code is very explicit and easy to understand.
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Top
Pro
•••
Official package manager and build tool
Cargo is the official package manager for Rust. It comes with the language and downloads dependencies, compiles packages, and makes and uploads distributable packages
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Top
Pro
•••
Supports cross compilation for different architectures
Since Rust 1.8 you can install additional versions of the standard library for different targets using rustup/multirust. For example: $ rustup target add x86_64-unknown-linux-musl Which then allows for: $ cargo build --target x86_64-unknown-linux-musl
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Top
Pro
•••
Makes developers write optimal code
Rust is a modern programming language written around systems. It was designed from the ground up this way. It's language design makes developers write optimal code almost all the time, meaning you don't have to fully know and understand the compiler's source code in order to optimize your program. Furthermore, Rust does not copy from memory unnecessarily, to give an example: all types move by default and not copy. Even references to types do not copy by default. In other words, setting a reference to another reference destroys the original one unless it's stated otherwise.
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Recommend
1
--
Julia
My Rec
ommendation
for
Julia
My Recommendation for
Julia
All
13
Pros
12
Specs
Top
Pro
•••
High-level code
Julia provides a high level of abstraction, making platform-independent programming trivial and easing the learning curve.
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Specs
Platforms:
Windows, Linux, Mac, FreeBSD
Current stable version:
1.5.3
Type Model:
Dynamically Typed
Top
Pro
•••
Function and operator broadcasting
You can perform operations on scalars, for example 2^2 or [1, 2, 3].^2.
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Top
Pro
•••
Written in itself
The Julia language is written in itself to a much larger extent than most other languages, so a budding programmer can read through the depths of the standard library and learn exactly how things work all the way down to the low-level bit-twiddling details, which can be englightening.
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Top
Pro
•••
Great standard REPL
Out of the box Julia has a very good Read-Eval-Print-Loop, which both completes functions and types, as well as completion based on history of previous statements. It integrates well with the shell and has an excellent online help system.
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Top
Pro
•••
Function overloading
You can have multiple functions with the same name, but doing different things depending on function arguments and argument types.
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Top
Pro
•••
Powerful n-dimensional arrays
Julia has built in n-dimensional arrays similar in functionality as Python's numpy.
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Top
Pro
•••
Strong dynamic typing
Dynamic and high level, but does not isolate the user from properly thinking about types. Can do explicit type signatures which is great for teaching structured thinking.
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Top
Pro
•••
Strong Metaprogramming
Julia allows you to edit Julia code in the language itself and write powerful macros. It is a great introduction to metaprogramming features
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Top
Pro
•••
Amazing learning curve
Julia requires no boilerplate code – a beginner needs to write only the parts they care about. This combined with the REPL provides the best learning experience available.
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Top
Pro
•••
REPL-based
The Julia REPL allows quickly testing how some code behaves and gives access to documentation and package management immediately in the REPL.
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Top
Pro
•••
Nice regular syntax
Julia code is easy to read and avoid a lot of unnecessary special symbols and fluff. It uses newline to end statements and "end" to end blocks so there is no need for lots of semicolons and curly braces. It is regular in that unless it is a variable assignment, function name always comes first. No need to be confused about whether something is a method on an object or a free function. Unlike Python and Ruby, since you can annotate the types a function operates on, you can overload function names, so that you can use the same function name for many data types. So you can keep simple descriptive function names and not have to invent artificial function names to separate them from the type they operate on.
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Top
Pro
•••
Almost as fast as C
Julia runs almost as fast as (and in fact in some cases faster than) C code.
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Free
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1
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