AI's real deal: no more plumbing, just power

[JoannStarke]

Explore how to move AI projects from lab to production with HPE Private Cloud AI and bridge the gap between experimentation and real-world results. Download the ESG technical validation to see how to transform your AI initiatives.

Forget incremental change. AI is rewriting how we all operate.

Think about it: the AI boom feels like it's been around forever, but it's just a few years old. ChatGPT's 2022 debut, with its 100 million users in two months, was a wake-up call. Then, 2023 became a massive sandbox for generative AI, like Llama 2, as everyone jumped in to experiment. 2024? That was the year companies tried to turn those experiments into reality, investing big in the necessary tools and people. But here's the kicker: most of those projects, around 90%, never made it out of the lab.

The path to successful AI implementation is fraught with challenges. First, there's the monumental task of data management. AI thrives on vast datasets, but ensuring the security of sensitive intellectual property and customer information within these mountains of data is paramount. Then comes the crucial decision of model selection and hosting. Navigating the complexities of the model lifecycle—from development to deployment and maintenance—requires careful planning and expertise.

Next, the sheer volume of AI tools introduces another layer of complexity. These tools, often demanding significant hardware resources, can be difficult to integrate and maintain. Managing the continuous evolution of these toolsets throughout their lifecycle is a significant undertaking.

You've got the AI engine running, but can it handle the rush hour? Scaling is the make-or-break moment. Can it handle a surge in users? Can it adapt as your business evolves? Now, you're staring down the build-or-buy dilemma. Go it alone? That's a high-stakes gamble. You'll need serious expertise, and you'll likely be reacting to problems instead of anticipating them. Plus, let's face it, those days of throwing money at everything. Those days are over.

A better approach to AI

Want AI that works, long term? You need to have the right foundation. That's what NVIDIA AI Computing by HPE gives you: serious muscle and scalability for those heavy-duty data pipelines. And here's the best part: HPE Private Cloud AI. It's not a reference architecture; it's the real deal. A single, integrated solution that takes care of everything—compute, storage, networking, and the whole AI software stack. Forget about piecing things together; you can roll out AI, fast, to everyone in your company.

Plumbing isn’t sexy. No one wants to look at it, they want it to just work. The same is true with AI infrastructure. There isn’t much to look at but it sure is important. At its core, HPE Private Cloud AI is a solution designed to accelerate AI adoption. It’s made for people that want to make AI happen in their business.

One day. That's all it takes to go from shipping crate to AI with HPE Private Cloud AI. It's pre-integrated, so you don't have to be a tech wizard. Just log into HPE GreenLake, set up your users and roles, and let the system work its magic. Everything else happens behind the curtain—user provisioning, access control, you name it.

Need to add a user? Send an invite, and you're done. Manage permissions and keep everything locked down, all from one place. The built-in software stack, HPE AI Essentials Software, handles the heavy lifting, so you can get straight to innovation.

What if your data engineers could say goodbye to infrastructure struggles and data wrangling? With HPE AI Essentials, they can. They get a streamlined, self-service experience with all their trusted tools—Airflow, EzPresto, Superset—right at their fingertips. And it gets better: these are the full, open-source community versions, no compromises. Plus, adding your own tools is a snap. Just click 'import framework' and you're good to go.

Remember setting up users and roles in GreenLake? Well, that security follows your data everywhere. So, watch this: a data engineer builds a pipeline that takes a CSV file, processes and transforms it, and turns it into Parquet. Then, Spark kicks in, building the actual data pipeline. They just grab the DAG from Airflow and launch Spark. The job finishes, and they can dive right into the results. That's because everything's integrated, and security's baked right in.

Data scientists, your playground awaits. A self-service catalog offers a comprehensive toolkit for AI solution development, spanning the entire model lifecycle. You'll find a rich selection of open-source tools, custom applications, as well as a self-service catalog for built-in NVIDIA AI Enterprise, and NVIDIA NIMs all designed to streamline development of AI applications faster than ever.

Data scientists, your workflow just got a whole lot easier. Dedicated Kubeflow notebooks are automatically set up for each user, with pre-mounted storage and a shared folder for teamwork. And the best part? You can pause these notebooks without losing anything. Running a resource-intensive experiment? No problem. Just pause your notebook to free up those GPUs for a production patch, then jump right back in once it's done. It's about giving you the flexibility and control you need.

The explosive growth of RAG and GenAI has outpaced the availability of skilled professionals, leading to a critical shortage of individuals with the combined data science, software engineering, and advanced AI knowledge required. HPE AI Essentials Software addresses this challenge with solution accelerators. These accelerators significantly reduce development time by pre-assembling key components like embeddings, vector databases, and RAG agents, eliminating the need for complex, manual integration. Nevertheless, these accelerators are designed for development and proof-of-concept stages, not production, as they currently lack the necessary guardrails and direct API/agent interfaces.

RAG Essentials streamlines RAG application deployment with a ready-to-use combination of NVIDIA engine, models, and RAG agents. Eliminate the need for intricate integrations and build your RAG application quickly using our intuitive three-step, low-code interface.

From streamlining data engineer workflows to empowering data scientists with seamless model development, HPE Private Cloud AI is built to accelerate your AI journey. With pre-integrated solutions and low-code simplicity, you can move from concept to deployment faster than ever. But don't just take our word for it. Gain confidence in your AI strategy by exploring an independent technical validation.

Download the ESG technical validation of HPE Private Cloud AI and see the real-world results for yourself.

Learn more of HPE Private Cloud AI

Joann Starke
Hewlett Packard Enterprise

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