Shiva Bhattacharjee is the Co-founder and CTO of TrueLaw, where we are building bespoke models for law firms for a wide variety of tasks.

Alignment is Real // MLOps Podcast #260 with Shiva Bhattacharjee, CTO of TrueLaw Inc.

// Abstract
If the off-the-shelf model can understand and solve a domain-specific task well enough, either your task isn't that nuanced or you have achieved AGI. We discuss when is fine-tuning necessary over prompting and how we have created a loop of sampling - collecting feedback - fine-tuning to create models that seem to perform exceedingly well in domain-specific tasks.

// Bio
20 years of experience in distributed and data-intensive systems spanning work at Apple, Arista Networks, Databricks, and Confluent. Currently CTO at TrueLaw where we provide a framework to fold in user feedback, such as lawyer critiques of a given task, and fold them into proprietary LLM models through fine-tuning mechanics, resulting in 7-10x improvements over the base model.

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// Related Links
Website: www.truelaw.ai

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Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/
Connect with Shiva on LinkedIn: https://www.linkedin.com/in/shivabhattacharjee/

Timestamps:
[00:00 ] Shiva's preferred coffee
[00:58 ] Takeaways
[01:17 ] DSPy Implementation
[04:57 ] Evaluating DSPy risks
[08:13 ] Community-driven DSPy tool
[12:19 ] RAG implementation strategies
[17:02 ] Cost-effective embedding fine-tuning
[18:51 ] AI infrastructure decision-making
[24:13 ] Prompt data flow evolution
[26:32 ] Buy vs build decision
[30:45 ] Tech stack insights
[38:20 ] Wrap up