Collaboration is key for aligning on intents before implementation, to ensure the best results for the problem we are trying to solve. Collaboration does the glue work to ensure a consistent and streamlined workstream between data scientists, data engineers, designers, etc.
For example, when implementing a human-centered approach for GenAI, joint decision making and sharing of practices and technologies helps ensure the development of the right prompts that answer the customers’ needs and ethical requirements.
Interested in learning more?
Check out this 9 minute demo that covers MLOps best practices for generative AI applications.
View this webinar with QuantumBlack, AI by McKinsey covers the challenges of deploying and managing LLMs in live user-facing business applications.
Check out this demo and repo that demonstrates how to fine tune an LLM and build an application.