Understanding Limitations of Large Language Models

Understanding Limitations of Large Language Models

In this episode of 'Case by Case', Justin Waltrip and Jagriti Pandey discuss the impact of AI, particularly large language models (LLMs), on the legal industry. They explore the limitations of LLMs, including their inability to perform accurate mathematical calculations, the challenges posed by outdated information, and the difficulties in handling specific domain knowledge. The conversation also covers the importance of dynamic legal contexts, the integration of function calling to enhance LLM capabilities, and the need for maintenance and evaluation of AI systems. Additionally, they address when to use AI versus traditional tools, the implications of memory in AI systems, and the importance of transparency and privacy in regulated industries.

Building Trustworthy AI for Legal Workflows

In the inaugural episode of the Case by Case podcast, hosts Justin Waltrip and Jag discuss the evolution of AI in the legal industry, highlighting the transition from traditional AI to more specialized legal AI solutions. They identify gaps in the current market, emphasizing the need for reliable and user-friendly AI tools tailored for legal professionals. The conversation covers the limitations of existing AI technologies, the design philosophy behind their platform, and their vision for the future of legal AI as a dependable coworker in the legal environment.