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.
Sy Brand, author of "Building a Debugger," and Tim Misiak explore how implementing a debugger is one of the most effective ways to gain a deep understanding of operating systems, compilers, and hardware. They delve into the unexpected complexities of core features like stack unwinding and code stepping, the challenges posed by legacy APIs like ptrace and debug formats like DWARF, and the future of debugging with advancements in time travel debugging and tools for optimized code.
A discussion on a new report detailing how people use ChatGPT, the global AI adoption trends from Anthropic's Economic Index, the future of AI agent economies, and the practicality of emerging AI wearables like AlterEgo and Meta's smart glasses.
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.
This talk explores a data science approach to identifying high-risk subpopulations for multimorbidity in sub-Saharan Africa, contrasting traditional hypothesis-driven analysis with a discovery-driven method that automatically uncovers non-obvious patterns in health data.
Brendan Foody, CEO of Mercor, discusses the critical role of AI evaluations (evals) in model improvement, detailing how his company achieved unprecedented growth by supplying high-skilled experts to top AI labs. He explores the shift to Reinforcement Learning from AI Feedback (RLAIF), the future of work in an AI-driven economy, and why he believes the path to AGI is paved with better evals, not just more data.