Page 61 - Red Hat PR REPORT - MAY 2024

5/13/24, 3:00 PM Red Hat Saddles Up For The Wide Open GenAI Horizons
control costs. They’re becoming equally viable to their
cloud counterparts.”

The industry model has been to send AI workloads to
the cloud, where the massive compute power can churn
through the data and return the information. For
enterprises, that is getting more difficult to do. Moving
data back and forth between on-premises datacenters
and the cloud can get expensive and, for security,
privacy, and regulatory compliance reasons, some data
can’t be sent to the cloud, particularly as they use
methods like retrieval-augmented generation (RAG) to
infuse AI models with sensitive and proprietary
corporate data.

“There’s rapid evolution across all the platforms and the
type of tooling that’s being made available,” Huels said.
“There’s always a new methodology that’s being
presented for customers to be able to infuse their data
into different models. Customers are looking to be able
to perform inference across cloud, on-prem and edge.
As these models have gotten more efficient, processors
are starting to pick up in the capabilities they have, and
hardware at the edge is becoming more available. This
isn’t going to be centrally datacenter-driven for their
entire AI workload. They may train on the datacenter,
but then they want to be able to deploy across multiple
platforms.”

Like other platform vendors, Red Hat over the past few
years has been integrating AI capabilities into its
products and services, such as Ansible. However, at
Red Hat Summit, the company is looking to showcase
what it already has and what is coming. Red Hat is
expanding the use of its Lightspeed AI assistant tool,
which was first introduced last year with the Ansible
automation platform and is now coming to both
OpenShift container platform and Red Hat Enterprise
Linux (RHEL) operating system, with future plans to
extend it to other products, according to Gunnar
Hellekson, vice president and general manager of the
RHEL Business Unit.

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