This podcast episode explores the capabilities and limitations of Large Language Models (LLMs). The speaker introduces a mental model comparing LLM capabilities to those of a recent college graduate with general knowledge but no specialized training. The episode then details several limitations: knowledge cutoffs (LLMs only know information up to their training data), hallucinations (fabricating information), input/output length restrictions, and difficulties handling structured data. Finally, the speaker addresses potential biases and the output of harmful content, emphasizing the ongoing efforts to improve LLM safety. Listeners gain a practical understanding of LLMs' strengths and weaknesses to better utilize this technology.
Sign in to continue reading, translating and more.
Continue