The Utility of Interpretability — Emmanuel Amiesen
Latent Space: The AI Engineer Podcast
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Navigating Complexities of Language Models
This chapter explores the intricate workings of large language models (LLMs), particularly in tasks like medical diagnosis and their interpretability. It discusses concepts such as adversarial training, multilingual representations, and the implications of biases in language processing. The dialogue also delves into multimodality, examining how different forms of data are integrated while questioning the effectiveness of current methods.
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