Mlops

Tool Calling

Tool Calling

A panel discussion with experts from Arcade, Prosus Group, and MeaningStack who argue that most teams are building agents incorrectly. They dissect the failures of simple API wrappers, the pros and cons of MCP, and the critical role of governance and organizational structure in deploying agents successfully.

The Shadow AI Problem Nobody's Talking About

The Shadow AI Problem Nobody's Talking About

Euro Beinat (Prosus Group) and Mert Öztekin (Just Eat Takeaway.com) discuss the practical challenges of scaling AI, focusing on developer productivity, the role of AI agents in automating the 'long tail' of tasks, and the critical importance of change management and governance to foster an AI-native culture without stifling innovation.

Speed and Scale: How Today's AI Datacenters Are Operating Through Hypergrowth

Speed and Scale: How Today's AI Datacenters Are Operating Through Hypergrowth

Kris Beevers, CEO of NetBox Labs, explores the hypergrowth in AI infrastructure, detailing how teams are compressing the design, build, and deployment cycle from years to months. The discussion covers the primary bottlenecks like power and logistics, the critical need for intent-driven automation, and the role of a standardized data model in managing the immense complexity from physical cabling to logical configuration.

From PhD Side Project to $500M ARR: Will Falcon’s PyTorch Lightning Story

From PhD Side Project to $500M ARR: Will Falcon’s PyTorch Lightning Story

Will Falcon, CEO of Lightning AI, discusses the company's merger with Voltage Park to create a full-stack AI neo-cloud. He delves into the capabilities of Lightning AI Studio, a comprehensive platform for AI development, and recounts the origin story of PyTorch Lightning, from a personal research tool to a world-leading open-source framework.

W&B Models end-to-end demo

W&B Models end-to-end demo

W&B Models is the system of record for the entire model development lifecycle. This guide explores how to monitor training, tune hyperparameters, track artifacts and lineage for reproducibility, and automate MLOps workflows like evaluation and deployment using a central platform.

What is Agent Observability?

What is Agent Observability?

Lior Gavish, CTO and co-founder of Monte Carlo Data, discusses the critical transition from data observability to agent observability. He covers the widespread adoption of AI agents in data teams, the new challenges they introduce for monitoring, and why traditional tools fall short in providing the necessary insights into agent performance, security, and governance.