Alignment is Real // Shiva Bhattacharjee // #260
Episode description
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 fine-tuning is necessary over prompting and how we have created a loop of sampling, collecting feedback, and 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.
// MLOps Jobs board
// MLOps Swag/Merch
https://mlops-community.myshopify.com/
// Related Links
Website: www.truelaw.ai
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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