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From Neural Networks to GPU Fabrics – Networking for Modern AI:ML Infrastructure

Michael Witte, a principal architect at Worldwide Technology, discusses the fundamental shift in data center networking required to support large-scale AI and machine learning workloads. The presentation transitions from the basic biological inspiration behind neural networks to the physical and electrical realities that necessitate high-bandwidth GPU fabrics. Witte explains that because neural networks have grown […]

NetAI GraphIQ Demo with Irfan Lateef

In this functional architecture deep dive, Irfan Lateef, Sales Engineering and Business Development lead, demonstrates the practical application of NetAI’s graph neural network (GNN) for large-scale networking. Lateef details the platform’s multi-layered ingestion process, which pulls configuration data via SSH CLI to build a comprehensive graph of the network, alongside real-time telemetry from SNMP, Syslogs, […]

NetAI Graph Neural Network Deep Dive with Deepak Kakadia

In this session, Dr. Deepak Kakadia, founder and CEO of NetAI, discusses the technical architecture of NetAI’s graph neural network (GNN) and how it provides deterministic root cause analysis for autonomous network operations. Kakadia leverages his experience at Sun Microsystems, Verizon Labs, and Google to explain why traditional AIOps and Large Language Models (LLMs) often […]

NetAI Deterministic Root Cause for Autonomous Network Operations

In this session, Mike Hoffman, co-founder of NetAI, discusses the critical role of deterministic root cause analysis as a prerequisite for safe autonomous network operations. He explains why current AIOps solutions still necessitate manual intervention and how NetAI’s graph neural network (GNN) technology provides a verifiable diagnostic layer that bridges the gap between observability and […]

Selector 2026 Roadmap and Q&A

Selector AI introduces an AI-powered network observability platform designed to unify multi-domain signals into actionable root cause analysis (RCA). The platform focuses on reducing the Mean Time to Repair (MTTR) by addressing the alert storm and fragmented data silos that plague modern network operations centers (NOC). By employing a three-layered approach of collection, correlation, and […]

Selector Platform Diagnosis Demo

Selector AI introduces an AI-powered network observability platform designed to unify multi-domain signals into actionable root cause analysis (RCA). The platform focuses on reducing the Mean Time to Repair (MTTR) by addressing the alert storm and fragmented data silos that plague modern network operations centers (NOC). By employing a three-layered approach of collection, correlation, and […]

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