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 […]

Scality Presents at AI Field Day 8

Scality Presents at AI Field Day 8

Be among the first to learn about Scality ADI, its newly announced Autonomous Data Infrastructure, at AI Field Day 8, where Scality will discuss how AI is changing what enterprises need from their data infrastructure. As AI, cyber resilience and data sovereignty converge at the data layer, Scality will share the market forces and customer […]

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 […]

One View, Total Clarity with Selector

Selector AI is an AI-powered network observability platform that unifies signals across multi-domain environments to provide intelligent outcomes and root cause analysis (RCA). The platform helps networking and infrastructure operation teams lower their Mean Time to Repair (MTTR) and improve operational efficiency by addressing the challenges of fragmented data and tool sprawl. Through a three-layered […]

Netris Day Zero Demo with Alex Saroyan

This presentation provides a technical demonstration of the Netris controller’s capabilities in automating and simulating large-scale AI networking environments. The demonstration highlights the platform’s Day Zero functionality, where network engineers can model complex topologies and validate designs before physical hardware even arrives. By utilizing Terraform and the Netris CloudSim, Saroyan illustrates how a controller can […]

Consuming AI Networks with Netris

This presentation focuses on the consumption model of AI networks, specifically helping network engineers enable self-service capabilities for AI factory and neocloud operators. Alex Saroyan argues that while network engineers manage complex physical infrastructures, the consumers, such as compute orchestration products, require a simplified cloud-like abstraction. Netris achieves this through its Network Automation, Abstraction, and […]

Netris and the Lifecycle of AI Networking

Alex Saroyan, CEO and co-founder of Netris, provides insights from the company’s experience in deploying and automating large-scale GPU clusters. This second part of the presentation focuses specifically on the life cycle of AI networking, emphasizing that sustainable AI business strategies require architecting for long-term growth and newer GPU generations rather than single-cluster deployments. Saroyan […]

Netris Introduction and Overview with Alex Saroyan

CEO and co-founder Alex Saroyan discusses the evolution of network engineering in the era of AI. Saroyan highlights that AI networking significantly differs from traditional data center networking due to the massive scale of GPU clusters, ranging from 1,000 to over 50,000 GPUs, and the sheer density of network switches involved. Netris introduces the concept […]

Upscale AI’s Point of View with Aravind Srikumar

Upscale AI distinguishes between two critical domains: scale-up networking, which creates a large compute environment within a rack where multiple GPUs see a flat, unified memory, and scale-out networking, which connects these domains through memory copy operations. The presentation highlights that the network has become the backplane of a distributed ecosystem, moving from a standard […]

Upscale AI and the AI ASIC Landscape

Upscale AI posits that traditional data center networking is a round peg in a square hole for AI, as existing infrastructures were designed for general-purpose web traffic rather than the massive, synchronized communication required by billions of parameters and trillion-token models. By focusing exclusively on AI traffic and removing the bloat of legacy enterprise features, […]

Upscale AI Networking – What Has Changed with AI

Upscale AI argues that traditional cloud and front-end networks, which are largely based on a client-server architecture, are fundamentally ill-suited for the unique demands of AI workloads. While standard web traffic is connection-oriented and tolerant of latency, AI clusters rely on collective communication where GPUs perform synchronized all-to-all data exchanges. This shift results in a […]

AI Changes in the Norm with Upscale AI

Upscale AI, founded in 2025, recently emerged from stealth as a unicorn following $300 million in combined seed and Series A funding. With a team of industry veterans, Upscale AI is focused on building a clean sheet networking architecture specifically for the backend and lean front-end of AI clusters. The speakers emphasize that traditional data […]

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