Machine Learning

Last week, I had the privilege of attending a leadership meetup in Dallas organized by This Dot Labs and to be on the panel discussing the “Impact of AI on Organizations”. I was lucky enough to be in the same room with some seriously brilliant people. The discussions we had were refreshing and a big learning experience for me. What got me fascinated was the kind of applications where AI is being put to use. While I cannot disclose the specific applications discussed, the common thread was on leveraging AI to analyze and interpret vast quantities of data. ...

Speech-to-text models are the magic behind converting spoken language into written text. From dictating documents and emails to transcribing meetings, their applications are vast. Personally, I rely on this feature to send hands-free messages and control my smart home devices. While those everyday uses are great, I recently discovered an even more powerful application for speech-to-text. When you combine speech recognition with the power of LLMs, things get really interesting. We’re talking Q&A documents, meeting summaries, and even enhancing RAG models. ...

I’m no expert in AI/ML. I’m trying to self-learn and haven’t built anything significant, until now! To learn something, I need a problem to apply and practice what we learned. I was missing that. I didn’t have a use case for anything related to AI/ML and I wanted a pet project for AI/ML. The beginnings Yeah! Let’s talk about that. I started with this – Basic classification: Classify images of clothing. Yeah, why not. Jump into the deep end and figure out the basics as you progress. That has been my way of learning new things. This time, it did not work. My effort to learn ML and build a basic classification system spans 2-3 years 🤷🏾‍♂️. At the pace at which technology progresses, that’s a lifetime. ...