𝗧𝗵𝗲 𝗦𝘁𝗿𝗶𝗱𝗲 𝗧𝗼 𝗠𝗮𝗸𝗲 𝗔𝗜 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝗙𝗼𝗿𝘁𝗵

𝗧𝗵𝗲 𝗦𝘁𝗿𝗶𝗱𝗲 𝗧𝗼 𝗠𝗮𝗸𝗲 𝗔𝗜 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝗙𝗼𝗿𝘁𝗵 I tried to train a neural network to write Forth code. It was a tough task.

• I started with a small model, but it couldn't learn Forth.
• I fine-tuned the model, but it still didn't work well.
• I realized that Forth is a hard language for neural networks to learn.

Here's what I learned:

• Neural networks are not good at generating code in Forth.
• They are better at generating code in other languages, like Python.
• To get Forth code, it's better to use an external conversion tool.
• This tool can take the output from a neural network and convert it to Forth.

I also learned about some key terms:

• Parameter: a number in a matrix that the network can train on
• Pretrain: training a network on a large corpus of text
• Token: a chunk of text that the network uses as input or output

My goal was to make a tool that can write Forth code using a neural network.

• But I realized that this is not the best approach.
• Instead, I can use a neural network to generate code in another language, and then convert it to Forth.

I created some tools along the way, including:

• fmix: a package manager for Forth
• fsemver: a semver library for Forth
• fcov: a coverage tool for Forth
• flint: a lint tool for Forth

Source: https://dev.to/ua3mqj/forth-made-neural-networks-suffer-4p7h Optional learning community: https://t.me/GyaanSetuAi