Preetam Joshi Breaks Down ML, LLMs, AI Agents, and Governance Challenges

Episode notes

How do you make sense of security, governance, and risk in an age of black-box AI? This week, Raj is joined by Preetam Joshi , founder of Aimon Labs and machine learning veteran with experience at DRDO , Yahoo , Netflix , and Thumbtack . Together, they break down the technical evolution behind large language models (LLMs), explore the real challenges of explainability, and discuss why GRC teams must rethink risk in the age of autonomous reasoning systems. Preetam brings a rare mix of hands-on ML expertise and practical experience deploying LLMs in enterprise environments. If you’ve been wondering how transformers work, what explainability really means, or why AI governance is still a mess - this episode is for you. 5 Key Takeaways: - From DRDO to Netflix to Aimon Labs - Preetam’s career journey shows the intersection of machine learning, security, and entrepreneurship. -How Transformers Work - A simple breakdown of encoder/decoder architecture, embeddings, and attention mechanisms. -Explainability in AI - What it meant in traditional ML... and why it’s nearly impossible with today’s LLMs.

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