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Kison Patel & Demetrios Brinkmann · May 16th, 2025
The intersection of M&A and AI, exploring how the DealRoom team developed AI capabilities and the practical use cases of AI in dealmaking. Discuss the evolving landscape of AI-driven M&A, the factors that make AI companies attractive acquisition targets, and the key indicators of success in this space.
# AI
# M&A
# Dealmaking
# DealRoom

Maria Vechtomova · May 13th, 2025
The world of MLOps is very complex as there is an endless amount of tools serving its purpose, and it is very hard to get your head around it. Instead of combining various tools and managing them, it may make sense to opt for a platform instead. Databricks is a leading platform for MLOps. In this discussion, I will explain why it is the case, and walk you through Databricks MLOps features.
# MLOps
# Databricks
# Marvelous MLOps

Robert Schwentker · May 13th, 2025
At a packed Microsoft Reactor event in SF, CrewAI, LlamaIndex, and Lambda laid out how agents are quietly becoming core enterprise infrastructure. From scaling headaches to state management, cost tradeoffs to hallucination risks, this wasn’t a hype fest - it was a hands-on look at what it really takes to get agents into production.
# AI Agents
# Open Source
# API

Médéric Hurier · May 12th, 2025
This blog introduces GenV (Generative AI for Video Analytics), a practical Python-based agent designed to extract actionable insights from Google Meet recordings using multimodal AI. Built with tools like Google Colab, Google Cloud Storage, and Vertex AI's Gemini models, GenV automates the tedious process of summarizing meetings, identifying action items, and capturing key decisions. The workflow—Locate → Prepare → Analyze → Report—leverages structured Pydantic schemas to ensure consistent and useful outputs such as summaries, project discussions, and technical insights. The result is a powerful demonstration of how focused, agentic AI can streamline knowledge retrieval and improve meeting productivity, especially for professionals in AI and MLOps.
# GenV
# GenAI
# API


Fausto Albers & Demetrios Brinkmann · May 9th, 2025
Demetrios and Fausto Albers explore how generative AI transforms creative work, decision-making, and human connection, highlighting both the promise of automation and the risks of losing critical thinking and social nuance.
# Generative AI
# MCP
# AI Builders Club



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Caleb Baechtold, Hamza Tahir, Simba Khadder & 1 more speaker · May 8th, 2025
Best Practices for Enterprise-Grade MLOps and Governance with Snowflake
Catch this ML expert-led session to learn the best practices for designing and managing enterprise-grade ML development and production systems at scale. You’ll learn how Snowflake ML makes it easy to rapidly develop and prototype new ML projects while ensuring production ML systems deploy and operate in a secure, governed manner.
Laying the Foundation for Enterprise MLOps: Workflow Orchestration with ZenML
Effective ML orchestration is the foundation of successful enterprise AI systems, connecting data processing, training, and deployment into reproducible workflows. This session explores how ZenML provides the critical pipeline infrastructure that enables teams to standardize their ML processes while maintaining flexibility.
Operationalizing Data for Agents and Models with Featureform, MCP, and Iceberg
For years, feature platforms like Featureform have powered classical ML systems—serving features to models, productionizing transformations, and helping ML teams scale. But the rise of LLMs and agentic workflows is fundamentally expanding the surface area of the ML platform, introducing new patterns for how data is consumed and acted on. In this session, we’ll explore the next evolution of the feature platform: one that supports both real-time and batch pipelines, bridges traditional ML and agentic systems, and makes data accessible through interfaces like MCP.
# MLOps
# Iceberg
# Model Registry
# Snowflake


Alon Bochman & Demetrios Brinkmann · May 6th, 2025
Demetrios talks with Alon Bochman, CEO of RagMetrics, about testing in machine learning systems. Alon stresses the value of empirical evaluation over influencer advice, highlights the need for evolving benchmarks, and shares how to effectively involve subject matter experts without technical barriers. They also discuss using LLMs as judges and measuring their alignment with human evaluators.
# AI
# Machine Learning
# RagMetrics

Han Lee · May 6th, 2025
An analysis of the April 2025 GPT-4o sycophancy incident through the lens of MLOps. Learn why prompt changes demand rigorous deployment strategies (Canary, Shadow) and how neglecting MLOps/LLMOps principles impacts AI safety and user trust in Large Language Models (LLMs) and Machine Learning systems.
# MLOps
# LLMs
# Sycophancy Incident


Devansh Devansh & Demetrios Brinkmann · May 2nd, 2025
Open-source AI researcher Devansh Devansh joins Demetrios to discuss grounded AI research, jailbreaking risks, Nvidia’s Gretel AI acquisition, and the role of synthetic data in reducing bias. They explore why deterministic systems may outperform autonomous agents and urge listeners to challenge power structures and rethink how intelligence is built into data infrastructure.
# Open source
# Jailbreaking
# Synthetic data



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Arthur Coleman, Adam Becker, Nehil Jain & 1 more speaker · May 1st, 2025
This paper introduces a novel agentic memory system that dynamically organizes knowledge—going beyond traditional methods by linking memories contextually, adapting over time, and evolving as new information is added. Inspired by the Zettelkasten method, this system allows LLM agents to build a structured yet flexible network of past experiences, improving their ability to tackle complex real-world tasks.
# Agentic Memory
# LLMs
# AI Agents