With GPU demand far outstripping supply, enterprises are looking beyond NVIDIA to control cost and risk: alternate accelerators, on-prem GPU clusters, and creative scheduling policies for training versus inference. This session interrogates the “NVIDIA + X” future: performance parity, ecosystem maturity, operational complexity, and what happens to your AI roadmap if you don’t diversify. Key Questions: – How should enterprises frame vendor concentration risk around GPUs and AI accelerators? – What’s the real operational cost of adding a second accelerator stack (tooling, drivers, frameworks, talent)?…
Large enterprises face a fundamental choice: consume frontier models via APIs or invest in private AI infrastructure to run (and potentially tune) models closer to their data and controls. This panel compares both paths using real-world constraints—security, compliance, latency, reliability, cost, and strategic differentiation—and leaves attendees with a pragmatic way to decide what to rent, what to own, and what to keep hybrid.
As enterprises adopt agentic AI, they face a new class of adversary: autonomous, goal-seeking agents that probe controls, data, and policies at machine speed. Building on ideas like “Digital Darwinism” and adversarial agents competing to optimize infrastructure, this session asks: what happens when attackers weaponize agents—and how do we respond? Key Questions: – How will adversarial agents change red-teaming, penetration testing, and threat modeling? – What defensive patterns are emerging for agent endpoint protection, data controls, and PII sensitivity mitigation? – Where do AI guardrails,…
Agentic AI overlays promise networks that sense, reason, and act—but the real challenge is treating AI agents as first-class identities in the network. Building on ONUG’s A2A and Agentic Overlay concepts, this session explores how to standardize identity, trust, and messaging among agents, and how those agents interact with the underlying network fabric. Key Questions: – What should an A2A reference architecture look like in a large enterprise (broker vs. mesh, policy dialects, schemas)? – How do we provide Zero-Trust identity and least-privilege capability routing…
Enterprise AI is moving from experimentation to production—and infrastructure teams now control whether their companies win or fall behind. We are living in a moment of exponential progress driven by AI, where capabilities accelerate rapidly and traditional planning cycles no longer apply. As agentic systems take on Tier 1 and Tier 2 operations, generative infrastructure designs itself, and governance frameworks mature, a new reality is emerging: AI is driving a workload repatriation wave—as data gravity, IP protection, control, and security concerns force new architectural and…
Join our Emcees to hear all about the upcoming keynotes and sessions that will explore how to unleash the power of AI in enterprise infrastructure and applications. Get ready for 2 full days of thought leadership from industry leaders across a wide range of major industries.
