Use it to analyze the California & US Code, the California & Federal Codes of Regulation, and bills currently in the California legislation & Congress. It's far from useless but far more useful for creative writing than any kind of understanding or instruction following when it comes to complex topics.
Even performing a map-reduce over large documents to summarize or analyze them for a specific audience is largely beyond it. A 32K context size is a pittance when it comes to a single Title in the USC or CFR, which average into the millions of tokens each.
Yes. I can parse them just fine after reading a single book called Introduction to Legal Reasoning [1]. I can also autonomously take notes and keep track of a large context using a combination of short and long term memory despite not having any kind of degree let alone experience or a license to practice law.
How do you think people become lawyers and how smart do you think the average lawyer actually is? The problem is that there's hundreds of thousands if not millions of pages, not that it requires superhuman intelligence to understand.
Even if it were capable of intelligence in the bottom quartile of humanity it would be SO MUCH more useful than it is now because I'd be able run and get something useful out of thousands of models in parallel. As it stands now GPT4 fails miserably at scaling up the kind of reasoning and understanding that even relatively stupid humans are capable of.
Fine-tuning requires you to train the model with a set of prompts and desired completions. Building a suitable dataset is not trivial and it's not clear what it would mean to use a book for fine-tuning anyway – masking sentences and paragraphs and training the model to complete them in the book's style?
OpenAI doesn't support fine tuning of GPT4 and with context stuffing,the more of the book I include in the input the less of the bills I can include - which, again, are millions of tokens - and the less space there is for memory.
I believe you. But at the same time they showed during the demo how it can do taxes, using a multi page document. An ability to process longer documents seems more like an engineering challenge rather than a fundamental limitation.
Even performing a map-reduce over large documents to summarize or analyze them for a specific audience is largely beyond it. A 32K context size is a pittance when it comes to a single Title in the USC or CFR, which average into the millions of tokens each.