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Navigating Language Model Evolution
This chapter explores the evolving terminology and testing practices in the realm of large language models (LLMs), emphasizing the need for innovative approaches like semantic testing. It chronicles the speaker's journey from software engineering to machine learning, reflecting on the historical context and the transition towards open-source solutions. Additionally, it distinguishes between legitimate open-source offerings and those that misrepresent their capabilities, highlighting the importance of scalability and efficiency in the competitive landscape of Gen AI.