I wonder if you could teach it to understand a binary encoding using the raw bytestream, feed it compressed text, and just tell it to decompress it first.
To teach me to understand a particular binary encoding and compressed text format, you should provide the following information:
The binary encoding used (e.g., ASCII, UTF-8, UTF-16, etc.). The compression algorithm employed (e.g., gzip, Lempel-Ziv-Welch (LZW), Huffman coding, etc.). Once you provide these details, I can help you process the raw bytestream and decompress the text. However, keep in mind that my primary focus is on natural language understanding and generation, and I might not be as efficient at handling compressed data as a dedicated compression/decompression tool."
Genuine question.
Clearly this will break eventually, but I am playing around with some ideas to extend how much context I can give it. One is to do something like base64 encode file contents. I've seen some early success that GPT-4 knows how to decode it, so that'll allow me to stuff more characters into it. I'm also hoping that with the use of .gptignore, I can just selectively give the files I think are relevant for whatever prompt I'm writing.