Today, I reviewed the results of my experiments from the past few days. I focused on identifying patterns in how the models responded to different types of inputs and documented my findings. This reflection was important as it helped me consolidate my learning and prepare for the more complex task of working with the Whisper model, which I planned to start later in the week.
Related Posts
CXOs’ Guide to SDLC: Processes, Models, and Best Practices
Globally, it’s estimated that $3.4Tn would be spent annually by organizations on digital transformation initiatives, with cloud, AI,…
Adding Middleware to .NET Desktop Applications
Middleware is a common pattern in web development for handling cross-cutting concerns like logging, authentication, and error handling.…
Building a “Legal Killer”: An AI Agent Architecture Without the Margin for Error
In this article, we’ll explore how to build a local legal risk analysis system that doesn’t “hallucinate” text,…