MLOps Reading Group
# Generative AI
# Claude
# Hierarchical Taxonomy
Which Economic Tasks are Performed with AI? Evidence from Millions of Claude Conversations
We break down key insights from the paper, discuss what these findings mean for AI’s role in the workforce, and debate its broader implications. As always, our expert moderators guide the session, followed by an open, lively discussion where you can share your thoughts, ask questions, and challenge ideas with fellow MLOps enthusiasts.



Sophia Skowronski, Adam Becker & Valdimar Eggertsson · Apr 9th, 2025
Popular topics
# AI Agents
# RAG
# Generative AI
# LLMs
# AI
# Kubernetes
# Synthetic Data
# Google Cloud
# AWS
# LlamaIndex
# MLOps
# Machine Learning
# AI infrastructure,
# DSPy
# ML
# Google
# Innovation
# Microsoft
# Continual.ai
# Robotics



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Adam Becker, Nehil Jain, Matt Squire & 1 more speaker · Mar 6th, 2025
We dive deep into this groundbreaking paper, breakdown its key insights, and discuss what makes DeepSeek-R1 so special. Our expert moderators guide the session, followed by a lively round-robin discussion where everyone shares their thoughts, asks questions, and debates the implications with fellow MLOps enthusiasts.
This is the reading group for anyone passionate about MLOps, from seasoned practitioners to the AI-curious. We meet every month on the second Thursday, and trust us—you don’t want to miss this one.
# DeepSeek
# AI
# MLOps



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Nehil Jain, Adam Becker, Valdimar Eggertsson & 1 more speaker · Dec 27th, 2024
In the December Reading Group session, we explored A Taxonomy of Agents for Enabling Observability of Foundation Model-Based Agents. Key participants discussed the challenges of building agentic AI systems, focusing on four key capabilities: perception, planning, action, and adaptation. The paper highlighted issues like lack of controllability, complex inputs/outputs, and the difficulty of monitoring AI systems. Early-stage insights drew on DevOps and MLOps practices, and the need for improved tools and evaluation strategies for agent observability. The session fostered a collaborative exchange of ideas and practical solutions.
# AI Agents
# Observability
# AI Systems



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Valdimar Eggertsson, Sophia Skowronski, Adam Becker & 1 more speaker · Dec 2nd, 2024
This November Reading Group conversation covers advanced retrieval techniques, strategies like iter-drag and hyper-drag for complex queries, and the impact of larger context windows on model performance. The Reading Group also examines challenges in generalizing these methods.
# Long-Context RAG
# Inference Scaling
# iter-drag and hyper-drag complex queries



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Korri Jones, Valdimar Eggertsson, Sophia Skowronski & 2 more speakers · Nov 5th, 2024
October 2024 MLOps reading group session explores the role and relevance of small language models in an era dominated by large language models (LLMs). The author of a recent survey paper on small models joins to discuss motivations for using smaller models, including resource constraints, efficiency, and unique capabilities they bring to certain tasks. Key discussion points include the advantages of small models in specific contexts (e.g., edge devices and specialized tasks), their role in complementing large models, and emerging techniques for leveraging small models to enhance model efficiency and mitigate issues like out-of-vocabulary words. The group also touches on methods for compressing models and the challenges in balancing model size with generalization and task-specific performance.
# LLMs
# Small Language Models
# Specialized Tasks



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Nehil Jain, Sonam Gupta, Matt Squire & 2 more speakers · Sep 30th, 2024
In our September 12th MLOps Community Reading Group session, live-streamed at the Data Engineering for AI/ML Virtual Conference, we covered the paper "Hybrid RAG: Integrating Knowledge Graphs and Vector Retrieval for Information Extraction." The panel discussed using hybrid RAGs to pull information from unstructured financial documents. The paper's approach combines knowledge graphs with vector-based retrieval for better results. We critiqued the context-mixing methods and lack of graph pruning techniques. Overall, it was a solid session with great insights on improving financial data extraction using hybrid models.
# RAG
# Knowledge Graphs
# Vector Retrieval



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Korri Jones, Sonam Gupta, Nehil Jain & 1 more speaker · Aug 26th, 2024
# Long Context Language Models
# RAG
# SQL

Ben Wilson · Mar 7th, 2022
MLOps Reading Group meeting
Reading Group Session about Ben Wilson's Machine Learning Engineering in Action book.
https://www.manning.com/books/machine-learning-engineering-in-action
https://www.amazon.com/Machine-Learning-Engineering-Action-Wilson/dp/1617298719
# Presentation
# ML Engineering
# databricks.com