In this interview, Nick Frosst from Cohere discusses his experiences working with Geoff Hinton at Google Brain, Cohere's focus on bringing language model technology to enterprise, and the nuances of training models for specific use cases. He touches on the limitations of scaling laws and the importance of data quality, synthetic data, and the role of benchmarks. Frosst also shares his perspective on the hype around AGI, the potential impact of AI on the workforce and income inequality, and the balance between open and closed AI models. The conversation explores the future of user input methods, Cohere's fundraising journey, competition in the AI space, and the significance of sovereign AI models, ending with quick-fire questions about the AI landscape and Frosst's personal views.
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