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Distilling 200+ Hours of NeurIPS: What’s Next for AI // Nikolaos Vasiloglou // MLOps Podcast #336

Distilling 200+ Hours of NeurIPS: What’s Next for AI // Nikolaos Vasiloglou // MLOps Podcast #336

Nikolaos Vasiloglou, VP of Research ML at RelationalAI, shares his extensive analysis of the 2023 NeurIPS conference, distilling over 200 hours of content. Key themes include the dominance and evolution of agentic AI, the state of open-source vs. frontier LLMs, the first signs of deep learning models outperforming XGBoost on tabular data, and the critical rise of verification systems. He also explores the future of AI with data attribution for monetization and the concept of composable, LEGO-like language models.

Multi Agent AI and Network Knowledge Graphs for Change — Ola Mabadeje, Cisco

Multi Agent AI and Network Knowledge Graphs for Change — Ola Mabadeje, Cisco

A product manager from Cisco's incubation group, Outshift, details a solution that uses a multi-agent AI system combined with a dynamic network knowledge graph to solve critical issues in IT change management. The system integrates with ITSM tools like ServiceNow to automate impact assessment, test plan generation, and pre-production validation in a "digital twin" environment, significantly reducing production failures.

How Grounded Synthetic Data is Saving the Publishing Industry // Robert Caulk

How Grounded Synthetic Data is Saving the Publishing Industry // Robert Caulk

Robert from Emergent Methods discusses how grounded synthetic news data can solve the publisher revenue crisis in the AI era. He details the process of 'Context Engineering' news into token-optimized, objective data for high-stakes AI agent tasks, covering their open-source models for entity extraction and bias mitigation, and the on-premise infrastructure that protects publisher content.