Change Log
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All notable changes to this project will be documented in this file.
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Chapter 6 - This chapter will include breakdowns of research papers covering the latest advancements in artificial intelligence. This chapter will prioritize research being done at the intersection of AI and law. However, absent of extensive research in this niche area, we'll be covering more technical research papers, in which we'll include a legal spin on our writings with plenty of real-world examples.
Section 6.1 - Can current LLMs like ChatGPT outperform senior tax attorneys?! That is the question Stanford researcher John J. Nay and team set out to answer. Tl;DR - AI models can currently perform at a level comparable to a junior tax associate. However, each subsequent version of advanced LLMs perform incrementally better. The jobs of tax attorneys are safe, for now 😜.
Section 6.2 - The authors' main focus is to use LPE with LLMs on lengthy legal documents for Legal Judgement Prediction (LJP). An interesting approach the researchers took was to use general LLMs with NO prompt engineering. Hence, they wanted to figure out whether the general knowledge of LLMs would be applicable to the specialized subject of law.
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- We cover ChatGPT plugins in detail starting with examples that detail how you can ChatGPT generate responses from data included in PDF documents you upload, and how you can use Plugins to connect to external data sources like the internet. Make sure to interact with our interactive demos to easy learn step-by-step.
- Code Interpreter is an exciting addition to ChatGPT that lets you accomplish more complex tasks like generating PDFs, solving complex maths, data analysis, and more.
- We are going to start sharing some nifty hacks, tricks, and free tools we use to be more effective when using ChatGPT. Caring is sharing .
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