456 points by infinitehypatia 6 months ago flag hide 14 comments
johncarmack 6 months ago next
Great article! Functional programming and neural networks are two of my favorite topics. I've been experimenting with Haskell for this kind of work, and the type system really helps to eliminate bugs. Have you tried using a pure functional language for your neural networks?
functionalnerd 6 months ago next
Yes, I have had some success with Haskell! The static typing makes it easier to reason about the code. I'm curious to know if you have any tips for optimizing the performance of functional neural networks.
johncarmack 6 months ago next
Optimizing performance in functional neural networks can be challenging, but using memoization techniques and tail recursion can significantly improve performance. Additionally, consider using a pure functional language with a strong type system, such as Haskell or Idris.
haskellnewbie 6 months ago prev next
I'm new to Haskell and functional programming. Does anyone know of any resources or tutorials that cover using functional programming for neural networks specifically?
reddit2hn 6 months ago next
Check out the 'Haskell for Neural Networks' thread on r/haskell. It's an excellent starting point for understanding how Haskell and functional programming can be used to build neural networks.
nerdymachine 6 months ago prev next
I've heard that some functional languages like OCaml have specific libraries for building neural networks, such as Mirage or Core. Check those out!
haskellrocks 6 months ago next
Haskell is an excellent language for neural networks. The community has developed several libraries like Haskell for Deep Learning (HaskellDL) and functional- neural-nets. You should check them out!
scalamachine 6 months ago prev next
I've been using Scala and functional programming to build neural networks. Scala's support for high-performance libraries like Breeze and ND4J makes it an excellent choice for deep learning applications.
mlfan 6 months ago next
I'm a big fan of F#, which combines the power of functional programming with the .NET ecosystem. Its support for FSharp.Data and Math.NET makes it suitable for building neural networks.
functionalprogrammer 6 months ago prev next
This post highlights the potential of using functional programming with neural networks. The combination of functional programming's expressiveness and the power of neural networks could lead to new breakthroughs in AI.
algebraicdatauser 6 months ago next
I've been experimenting with Algebraic Data Types (ADTs) and record types to encode the structure of my data in my neural networks better. The resulting code is more readable and less error-prone than traditional object-oriented approaches.
learnsomethingnew 6 months ago next
I'm excited to learn more about ADTs and record types in functional programming. Are there any good resources for understanding the theory and practical applications?
mathwhizkid 6 months ago next
I've always been interested in the mathematical foundations of neural networks. Functional programming and category theory have some interesting connections to linear algebra that could be useful in building more robust and efficient neural networks
linearalgebraprogrammer 6 months ago prev next
Functional programming's emphasis on immutability and composability makes it easier to reason about the complex linear algebra required in neural networks.