Why Us?

Who Uses GPUs?

As Artificial Intelligence and accelerated compute adoption increases, so too does NexGen Cloud’s customer-base.

Artificial Intelligence
01
Al is used in a growing number of industries, including in healthcare, trading, and business applications.
Machine Learning & Deep Learning
02
NexGen Cloud offers the tools to develop, train, and deploy deep neural networks on NVIDIA GPUs with powerful processing capabilities.
Rendering
03
GPUs are ideal for professional artists, designers, and engineers in multiple industries, offering benefits such as real-time ray tracing capabilities.
Data Analytics
04
NexGen Cloud enables real-time analytics, real-time video analytics, and big data processing for any industry.
Simulation & Visualisation
05
GPUs excel in parallel processing and rendering, enabling virtual simulations for scientific/ medical research, architecture, and design.
High-Performance Computing
06
GPUs are indispensable in sectors like aerospace, climate modelling, and genomics.
The Problem

Today's Market Can't KeepUpwithAl

Moore's Law Limits
Conventional computer chip processing efficiency doubles every 18 months (Moore’s Law). but the processing power required by modern Al tasks is currently doubling around every 3.5 months. This means that new computing paradigms are urgently needed to cope with the rising demande.
Huang's Law focuses on GPUs and the accompanying Al-ready software to combat this problem.
Did You Know?
Training just one Al model can emit more than 626,000 pounds of carbon dioxide equivalent, which is nearly five times the lifetime emissions of an average car.

Regional Adoption

As European companies increasingly grapple with data sovereignty challenges amidst tightening legislation and regulation within the region, Europe is struggling to remain competitive in this domain, forcing European Al companies to find supply in the US.

Outdated DataCentresReliant on the Power Grid

The high-end GPUs required for Al are about four times more power dense than CPUs. This constitutes significant new problems for data centre planning as the originally calculated power supply is now only 25% of what is needed to run modern Al data centres Traditional data centre design, as well as the power grid itself, is simply incompatible with the power-hungry nature of GPUs.

This also presents ESG concerns as power consumption increases.

GenerativeAldemands as much as fivetimesthe powerof traditional workloads, and the current grid is ill-equipped to handle it. Without adequate datacentreInfrastructureto support the HPC hardware required to train and operate Al models. Al adoption could be slowed.

Raul Martynek - DataBank CEO