Data Acquisition Ethics
The conversation delves into the complexities of data acquisition and ethical considerations in model development. Emphasizing the importance of principled data usage, the discussion highlights the challenge of balancing performance metrics with fairness, especially in multilingual contexts. The aim is to create deployable models that businesses can trust, which naturally influences their approach to data handling.In this clip
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Machine Learning Street Talk (MLST)
Cohere co-founder Nick Frosst on building LLM apps for business
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