Executive roundtable series

The Frontier Circle

As agents move from generating answers to running continuous loops, the bottleneck shifts from GPU power to the CPU and networking layer keeping those GPUs fed.

For AI research infrastructure, ML platform, engineering and technology leaders.

Region
APAC, six cities
Dates
October to November 2026
Access
By invitation
The premise

The GPUs are waiting.

// utilisation is a data path problem

Accelerators are rarely the thing that is slow. They are the thing that is idle, waiting on a data path, a scheduler, or a virtualisation layer that was never meant to carry this shape of workload.

That is the starting point for this series. Not a product session, and not a briefing. A table of senior people working through where their own utilisation actually goes, how much of it is lost to overhead they did not choose, and what bare metal changes.

Six cities across APAC, between October and November 2026. Each table runs under the Chatham House Rule.

The evidence
10k+ Latest generation GPUs deployed as a launch partner for new silicon platforms
20B Projected US AI infrastructure market size in US dollars for 2026

Lambda announcements at NVIDIA GTC 2026 and industry analysis cited across 2026 coverage. The market figure is third party and should be verified or removed before go live.

What the table will cover

Three questions on the table.

Each table works through the same three questions, shaped by what the room brings to them.

Where utilisation actually goes

The first question is instrumentation: how much of each organisation’s accelerator time is productive, how much is overhead, and whether anyone has the visibility to answer honestly.

// tension: idle accelerators are the most expensive thing you own

What virtualisation costs at this scale

This session looks at the trade between the convenience of managed abstraction and the throughput of direct hardware access, and where each organisation has landed.

// differentiator: bare metal access without virtualisation overhead

Feedback loops change the shape

Reinforcement style workloads with tool use and code execution stress different parts of the system than pure training. The table works through what that has broken in their environment.

// context: agentic reinforcement workloads on frontier clusters
The series

Six cities. One frontier.

Each city is its own table with its own room, confirmed independently. Registration of interest is open now, with dates and venues confirmed city by city.

Lambda’s mission is to expand humanity’s energy and computational capacity.

Stephen Balaban Co-founder and CEO, Lambda
Before you register

Background reading.

Published Lambda material behind the questions on the table. Share your details once to unlock all three.

Platform Bare metal and GPU cloud infrastructure Solution Infrastructure for frontier model training Blog Lambda engineering and benchmarking writing
Request an invitation

Join us at the table.

Tell us which city suits you and we will come back to confirm your spot.

Require private transfer?
Who is convening this

About the hosts.

Lambda

Lambda started by building workstations for machine learning researchers, which is an unusual origin for a cloud provider and explains its bias toward direct hardware access over managed abstraction.

The company provides GPU cloud compute and bare metal instances used by AI research teams, and now positions itself as the Superintelligence Cloud.

Innovatus Media

Innovatus Media is a Sydney based B2B events agency that runs invitation-only executive roundtable series across APAC, EMEA and North America.

We convene senior decision makers for closed door conversations on the problems they are actually working on, and produce every element of the series end to end, from the room and the table to the follow up.

Questions first

Talk to the team.

Connect for more details on the series.