A survey on the different methodologies used to generate structured output from LLMs, from model fine-tuning, to domain specific language, and schema engineering.
Translating responsible AI principles to create VerifyML. User feedback, design decisions and architecture choices in creating our responsible AI solution.
Fairness is messy and complicated. Attempts to distil it down to a single metric is unhelpful and counter-productive. As business owners and model developers we should embrace the struggle in trying to apply fairness in artificial intelligence and data analytics models.