We’ve been here before. Think about the seemingly obscure and ever-evolving infrastructure technologies that have been introduced over the years that only few interact with, learn, and even see, but are always expected to work and are foundational to our digitalized world.

In my early days as a sales engineer, one of my favorite opening lines with friends and family was “the cloud really is a place.” Just because we store our data out of sight and out of mind doesn’t mean it’s vanished from the planet. That data is stored on a well-thought-out infrastructure in a well-planned data center facility that makes it accessible anywhere. And just like “the cloud”, AI runs in a real location, on a fully-configured infrastructure, where it’s deployed and secured by people. Well, many people.

So, you see, we really have been here before. In this new AI Jam series, we always aim to “keep it real with AI”. And despite the artificial and surreal vocabulary used today, AI workloads, just like the cloud, still need specialized hardware, software, and networking to make it a reality.

Join us for our next talk about Implementing your AI Breakthrough Effectively - The infrastructure to you’re AI. We’ll dive into the spectrum of use cases and infrastructure considerations that are challenging businesses today. As you know, different use cases and stages in a development cycle require different configurations. Infrastructure configurations and capacity for fine-tuning LLMs are not the same as what’s needed for inference, retrieval augmented generation (RAG), or even small language models.

So how best to get started? Do you need access to large training clusters which could be very challenging for anybody to deploy? And what type of budget do you need, as the common statement you hear about AI projects is that it’s going to be expensive!

Fortunately, this is not always the case. In fact, at HPE we help customers get started every day with AI by removing complexity. Large-sized clusters for training large language models are not the only entry point to enabling AI in your organization. If you are stuck between a use case and how to get started, this interactive session will help you navigate how operational improvements can help you get started today.

We’ll also discuss how to show value to your organization today that will help enable a successful transformational AI adoption over time. So, Data Engineers, bring your IT Ops Manager, grab some coffee, and join us for this AI Jam session, where we discuss different AI infrastructure environments and software options to help get your use case started.