Coherence vs. Knowledge
The conversation explores the distinction between coherence and knowledge in AI models, emphasizing the importance of calibrating these models with internal company data. Without proper training on specific documents, users may encounter "confidently inaccurate" results. The potential for custom-trained language models to enhance search capabilities and adapt to a company's unique language is highlighted as a key focus for future developments.In this clip
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The AI Podcast
Glean Founders Talk AI-Powered Enterprise Search on NVIDIA Podcast - Ep. 190
Related Questions
What challenges are faced in training large language models (LLMs) as discussed in the episode Jennifer Prendki Interview - Agile Machine Learning - TWiML Talk #46 and the clip Monitoring NLP Models?
What challenges are faced in training large language models (LLMs) as discussed in the episode Jennifer Prendki Interview - Agile Machine Learning - TWiML Talk #46 and the clip Monitoring NLP Models?