Inside the wild world of high frequency trading
DCD speaks to the firms chasing the last nanosecond
Compute | New York 2025
Connecting the hyperscale and enterprise IT community to deploy scalable, efficient IT hardware for AI-driven workloads
AI workloads are fundamentally reshaping IT infrastructure, putting huge demands on densities, processing power and networks.
The DCD>Connect | Compute event series helps the individuals meeting this challenge to make informed decisions faster, through tailored networking, technology-discovery and best-practice sharing.
In New York, you'll join 400+ IT infrastructure, AI and HPC leaders, from enterprise and hyperscale, set to share their vision for the hardware driving computing forward.
Learn more about the Compute experience
“I attend DCD>Connect every year and I encourage my colleagues to as well. The interactions with industry professionals can't be beat. I get more done in two days at this show than I can with six months’ worth of phone calls and online meetings.”
Associate Director, Verizon
Our Speakers
CEO, Neuron Factory
Vice President - Advanced Technology Innovation, Google
Technical Director - Systems Design, AMD
Head of Compliance and US Gov Network Engineering, Oracle
Global Director of AI & Innovation, Digital Realty
Aryo Kresnadi
Technical Director, Global Network Architecture, FedEx
Chief Evangelist, VP of Business Development, Ampere
Founder & CEO, TensorWave
HPC Division Leader, Los Alamos National Laboratory
CEO, Sutor Group Intelligence and Advisory
Agenda Highlights
-
DCD>Talks: Quantum conundrum: Can AI and quantum computing be integrated effectively?
- —
- Compute Main Stage
- Compute
- Open Session
Speakers
Bob Sutor
CEO, Sutor Group Intelligence and Advisory
Content Director, DatacenterDynamics and SDxCentral
Are quantum computers the “silver bullet” for overcoming the huge computing demands of larger and larger generative AI models? Probably not - at least not in the way many think. So how can quantum technologies and AI models be brought together to create advances in both technologies?
Join us for this deep dive into the convergence of AI and quantum computing.
-
Major Panel: Win the race to scale - How can data centers keep up with rising compute, storage, and networking needs in the AI boom?
- —
- Compute Main Stage
- Compute
- Storage
- Networking
- Open Session
Speakers
Srivatssan Srinivasan
Gen AI Technology Leader, Independent Thought Leader
Founder & CEO, TensorWave
Founder & CEO, Lemurian Labs
Global Vice President, Technology and Innovation - Data Centers, Johnson Controls
Chief Evangelist, VP of Business Development, Ampere
Brand Evangelist, QTS Data Centers
As AI workloads continue to grow, data centers require more memory, more computing power, and lower latency networking, forcing massive refreshes of hardware that risk disrupting regular operations and imposing huge costs. Organizations of all shapes and sizes race to build, train and test AI models for all sorts of purposes, pushing compute and storage capacities to their very limits.
Will AI move too fast for hardware to handle? Will energy supply be the true ceiling? Or will hardware evolution smash all barriers?
Join our first panel of Day 2 as we explore:
- Power Potential: What improvements in computing power are going to maximize performance in the year when inference is king?
- Running on empty: What can the industry do to ahead of the rising energy demand as hardware energy consumption outruns supply?
- Fit to burst: How can you secure scalable storage solutions for ever-higher data volumes that don’t sacrifice reliability, maintainability and fault tolerance?
-
Major Panel: Storage Wars - Optimizing storage for AI, from data ingestion to training and inference
- —
- Compute Main Stage
- Storage
- Open Session
Speakers
VP Partnerships, Hosted.AI
Compute, Storage, and Networking Editor, DatacenterDynamics
Gary Grider
HPC Division Leader, Los Alamos National Laboratory
Technical Director - Systems Design, AMD
Director of Strategic Planning, Solidigm
How am I going to train my new $72,000,000,000 AI model? Where am I going to keep all the data so it’s as secure as can be but hyper-accessible at the same time? Handling storage requirements for modern HPC-AI workloads is a monumental task as higher and higher capacity, speed and reliability are needed for adequate speed to market for AI.
Can your storage hardware withstand the oncoming surge in data volume? How can enterprises with more stringent regulatory standards around data management stay competitive? Will your storage stumble at the AI inference hurdle?
Join our panel as we discover:
- Forging Resilience: How can you bolster your storage to accommodate the increasing demand for large workloads whilst reducing data loss and downtime?
- Embedding Agility: Can your storage hardware provide the low latency and rapid access needed to test new models?
- Ensuring Security: How can you ensure your data is protected from ransomware without impinging on availability for AI?
Actionable solutions to the challenges dominating the headlines
-
-
US gov't to award reduced CHIPS Act funding to Intel
Company will receive $7.9bn
-
Hard drives at the heart of AI innovation
The future of AI hinges on storage
Connect with:
Filter:
