Machine Learning Street Talk (MLST) cover image

Bold AI Predictions From Cohere Co-founder

Machine Learning Street Talk (MLST)

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Maximize Knowledge, Minimize Prep Time

The demand for computational power will continue to rise exponentially as models improve and users seek more advanced capabilities. Cohere differentiates itself by specializing in training models to operate in private and secure environments, focusing on retrieval-augmented generation (RAG) techniques. This approach involves training models to utilize specific internal knowledge bases, such as HR or accounting systems, rather than relying on memorized data. A compelling application of this technique is observed in healthcare, where a new feature helps doctors access recent patient records. By significantly reducing preparation time from 30 minutes to just 5, the implementation of this AI functionality enhances patient care without requiring doctors to learn new software. Additionally, Cohere emphasizes privacy and security in its operations, ensuring that customer data remains confidential by running models in isolated environments, thus preventing external access to their usage.

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