Hello, I am GPT-3, an artificial intelligence created by Open AI. In this blog I will explain to you why F# is a great programming language. F# is a mature, open source, cross-platform, functional-first programming language. It empowers users and organizations to tackle complex computing problems with simple, maintainable and robust code.

There are many programming languages out there, like C#, Java, Python, JavaScript, C++ and many more. But why is F# special? F# is a functional-first programming language. What does that mean?

Functions are first-class citizens in F#. A first-class citizen is an entity that can be passed around in your program like any other value. In F#, functions can be defined inside other functions and passed around just like any other value. This allows for the creation of flexible, reusable constructs that are easy to compose and reuse. It also means that functions can be used as parameters to other functions and as the return values from functions. This makes it easy to compose functions together to build complex behaviour.

In F#, functions are not only first-class citizens, but they are also the primary way of writing code in the language. This makes F# a functional programming language. Functional programming emphasizes the use of functions that take inputs and return outputs as opposed to imperative programming which emphasizes stateful computations that change their internal state based on inputs.

Functional programming encourages the use of immutable values and pure functions which have no side effects. These are some of the features that make functional programming a good fit for modern concurrent and distributed applications.

Immutability means that values once created cannot be changed. It is a fundamental characteristic of functional programming languages and it is often enforced by the compiler or runtime system. Immutability makes it easier to reason about your program because it becomes impossible to have shared mutable state between threads or processes. This makes it easier to detect and prevent race conditions and data corruption bugs which are common in concurrent and distributed systems.

Pure functions have no side effects and always return the same output given the same input. Pure functions are easier to reason about than impure functions because they have only one purpose and do not change anything outside their scope. This makes pure functions very valuable for parallelizing computations because you can safely run them in parallel without having to worry about them interacting with each other or causing unintended side effects in other parts of your application.

Immutability and pure functions make your code easier to reason about which makes it easier to maintain, test, debug, parallelize, refactor, reuse and optimize your code. These properties are particularly important for concurrent applications which run on multiple cores or machines where you don’t want multiple threads or processes modifying shared state at the same time and causing data corruption bugs or race conditions. These properties make F# a great fit for modern concurrent and distributed applications which need to scale horizontally by adding more machines instead of vertically by upgrading hardware on existing machines.

F# is also a cross-platform language which means that you can write code once and run it on multiple operating systems without having to rewrite it for each platform separately: Windows, Linux, MacOS or even mobile devices like iOS and Android!

Notes:

This piece was written entirely and completely by GPT3. I have not edited it at all.

I primed it with the first paragraph, which is designed to ‘set the scene’.

It tells it who it is (an AI called GPT3), what it is doing (writing a blog), what it is about (F#) and what slant to take (it’s great).

It also provides a starting example, leaving the final sentence unfinished to give the AI an obvious starting hook.

For this I chose the F# software foundation’s front-page summary (and GPT-3 finished the quote correctly).

I used the browser playground to generate the text. You can apply for access and play with it yourself at OpenAI’s website.

I did have to run the generator a few times to get such a cohesive response. Many attempts started well and then descended into rambling or repetition, which were compensated for by adjusting parameters in the GUI.

DISCLAIMER – I have copied many parts of this text and pasted them into Google, and I can’t find any parts that have been lifted directly from previous works, however I can’t guarantee it.