Mlops

Data Analytics & AI for Engineers | Altair RapidMiner

Data Analytics & AI for Engineers | Altair RapidMiner

A detailed walkthrough of the Altair RapidMiner platform, demonstrating how to build a complete predictive maintenance solution. The session covers low-code data preparation and visualization, automated machine learning with AutoAI, text analytics using both traditional methods and generative AI, and culminates in the creation of a sophisticated AI agent for operator support.

Designing AI Agents for the Complex Realities of Healthcare

Designing AI Agents for the Complex Realities of Healthcare

Dr. Sarah Gebauer presents a clinical framework for deploying AI agents in healthcare, drawing a powerful analogy between AI agents and medical residents. She outlines the critical risks, validation strategies, and post-deployment monitoring required to make agents useful, safe, and credible in high-stakes clinical environments.

Building Multi-Player AI Systems (and why it’s SO hard)

Building Multi-Player AI Systems (and why it’s SO hard)

MeshAgent introduces a multiplayer AI paradigm, shifting from single-user systems to collaborative 'Rooms' where teams of humans and agents can work together with shared context. This talk explores the platform's architecture, developer tools, and its approach to solving real-world collaborative tasks.

AI Needs Memory - Here's How It Works

AI Needs Memory - Here's How It Works

A deep dive into the architectural and economic foundations of memory for AI agents. The talk explores the core tradeoffs between classical data storage and dynamic agent behavior, introduces a human-inspired framework for memory, and discusses practical strategies and future directions for building reliable, evolving AI systems.

Trust at Scale: Security and Governance for Open Source Models // Hudson Buzby // MLOps Podcast #338

Trust at Scale: Security and Governance for Open Source Models // Hudson Buzby // MLOps Podcast #338

Hudson Buzby from JFrog discusses the critical security, governance, and legal challenges enterprises face when adopting open-source AI models. He highlights the risks lurking in repositories like Hugging Face and argues for a centralized, curated AI gateway as the essential framework for enabling safe, scalable, and cost-effective AI development.

Catastrophic agent failure and how to avoid it // Edward Upton // Agents in Production 2025

Catastrophic agent failure and how to avoid it // Edward Upton // Agents in Production 2025

Edward, a founding engineer at Asteroid, discusses the critical challenge of managing catastrophic failures in agentic browser solutions, particularly in high-stakes domains like healthcare and insurance. He shares real-world examples of agent failures and outlines a practical framework for building more reliable, predictable, and accountable agents by scoping their capabilities, implementing robust human-in-the-loop tooling, and employing independent evaluation systems.