Model choices: business use cases for SLMs and LLMs
For many years, businesses and their data science teams valued accuracy above all else when it came to a model’s performance. Increasingly, however, other factors and trade-offs have come into play depending on the business context of models. From biases buried in training data to the costs associated with runtime and resourcing services underpinned by… … continue reading
