Exploring AI Studio and PRF Flow: Streamlining Enterprise AI Application Development
Join Heni Wong, Software Engineer Lead at Microsoft AI, as he explores how organizations can truly begin leveraging Gen-T AI in 2024, highlighting the importance of tracing, evaluation, and monitoring with tools like Azure AI Studio and PR Flow.
- Heni Wong, software engineer lead at Microsoft, discusses how organizations are beginning to use and derive value from Gen T AI in 2024
- AI is not just plug-and-play; it requires integration with domain-specific knowledge and tools, content safety filters, careful evaluation, and continuous monitoring for effective operation
- Microsoft has developed a suite of comprehensive tools for building AI applications efficiently:
- 1. AI Studio: development hub for building AI applications, with pre-trained API services, machine learning capabilities, and end-to-end trustworthy, safe, and secure tools
- 2. PRF (Preferred Repo Framework) Flow: open-source SDK, CI/CD extensions, and developer tools to streamline the end-to-end development cycle of AI applications
- 3. Both products support tracing, instrumentation, evaluation, and monitoring for effective AI application building
- Real-world example: chatbot app built with AI Studio and PRF Flow for an outdoor equipment company to answer SE data questions, using the Assistant API and two tools (NL question to SQL query translat
- Tracing & Instrumentation: capturing events from applications for insights into possible issues; evaluation capabilities for improving application quality and safety; monitoring abilities for proactiv
- PRF Flow has three superpowers:
- 1. Tracing & instrumentation: capture events and gain insights
- 2. Evaluation capabilities: improve application quality and safety
- 3. Monitoring abilities: be proactive and have visibility into production workloads
- Example of a PRF Flow evaluation for the chatbot's sales data inside tool, including test data set generation and using evaluators for content safety, execution time error rate, and SQL similarity sco
- The evaluate function and built-in evaluators (such as the Content Safety Evaluator) help ensure high-quality AI applications
- Continuous monitoring is important after deployment to ensure the application always runs as expected
- PRF Flow can be integrated with Microsoft Application Insights for collecting traces, usage metrics, and feature metrics in a dashboard for detailed insights.
Source: AI Engineer via YouTube
❓ What do you think? What are your thoughts on the ideas shared in this video? Feel free to share your thoughts in the comments!