MIPRO and DSPy with Krista Opsahl-Ong! - Weaviate Podcast #103
Weaviate Podcast
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Exploring In-Context Learning and Model Optimization
This chapter delves into the complexities of in-context learning, contrasting many-shot and few-shot learning while examining their implications on model performance. The speakers also explore the architecture of information processing systems and the potential of language models in generating effective designs. Additionally, the discussion touches on self-improving AI systems, the challenges of prompt tuning, and the role of Bayesian optimization in enhancing model selection and efficiency.
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