Topic / AI & Data
AI & Data
The next level of AI advancement, agentic AI, uses LLMs, machine learning, and corporate automation to do complicated, multi-step operations without human interaction. It lets smart computers understand context, adapt to new knowledge, and work with humans to solve complex problems.
80 resources for “AI & Data”
May 4, 2026
AI Tips: Efficient management of long inference AI sessionsComparing solutions offered by KV-Cache offload and Google TurboQuant The rapid diffusion of large language models (LLMs) and the explosion of agentic AI have created a critical infrastructure…|
Blogby Andrea Fabrizi (AI Storage Solutions Product Manager)Apr 19, 2026
Integrating Dagster as a modern data orchestration framework in HPE Private Cloud AIHPE Private Cloud AI (PCAI) provides a curated set of pre‑integrated orchestration and machine‑learning (ML) frameworks, including Airflow, Kubeflow, Spark and Ray, to streamline the development and…|
Blogby Guoping JiaApr 3, 2026
AI DevCon 2026: Why the future of enterprise AI is a data and storage engineering problemAI DevCon 2026, held on 12–13 March 2026 at the NIMHANS Convention Centre in Bengaluru, brought together developers, data engineers, platform architects, DevOps leaders, and AI practitioners working…|
Blogby Madhukar RupakumarMar 17, 2026
Implementing a local LLM using S3-based model storage and vLLM in HPE Private Cloud AIDeploying a local Large Language Model (LLM) architecture using S3‑compatible object storage and vLLM as the inference engine provides a scalable, cost‑efficient, and secure foundation for enterprise…|
Blogby Guoping JiaMar 6, 2026
LLM observability and cost management on HPE Private Cloud AILLM (Large language Model) observability and cost management are critical for deploying reliable, secure, and financially sustainable AI applications. By tracking metrics like token usage, latency…|
Blogby Santosh Nagaraj & Claudio CalderonFeb 25, 2026
Building an MCP server to take advantage of OpsRamp monitoring - A Step-by-Step Implementation Guide Part 2Introduction In my previous article, I explored the Model Context Protocol (MCP) as the universal connector for AI applications. Now, let's roll up our sleeves and dive into the actual implementation…|
Blogby BalaSubramanian VetrivelFeb 16, 2026
AI Tips: Why is storage important for KV cache?Although KV (Key-value) cache is usually described as an LLM inference optimization, it is actually best understood as a specialized, high‑performance storage layer that holds intermediate attention…|
Blogby Andrea Fabrizi, Product manager for Storage for AI Dec 3, 2025
Bringing AI assistants to GreenLake with MCP ServersOverview Modern cloud platforms generate vast amounts of operational data. GreenLake customers often find themselves toggling between multiple interfaces, running complex API queries, and piecing…|
Blogby Vandewilly SilvaSep 9, 2025
AI agents as the meeting whisperersPart 7 of our Gen AI for PM series Introduction Meetings often move fast, ideas overlap, action items get lost, and key insights can slip through the cracks. This is where AI agents step in as the…|
Blogby Dinesh R Singh, Nisha Rajput, Varsha ShekhawatAug 30, 2025
Multi-agent systems for multi-stakeholder projectsPart 4 of our Gen AI for PM series Intro Large projects often involve multiple stakeholders, each with different priorities, risks, and information needs. Managing all of these moving parts with a…|
Blogby Dinesh R Singh, Nisha Rajput, Varsha ShekhawatAug 28, 2025
Experimenting with the Model Context Protocol and Chapelexternal blog|
Blogby Daniel FedorinAug 28, 2025
Part 12: AgentOS - The invisible conductor of enterprise AIScene one: The orchestra without a conductor Picture an orchestra hall. The violinist plays beautifully, the percussionist pounds with passion, the flutist adds magic — but there’s no conductor…|
Blogby Dinesh R SinghAug 27, 2025
Your new PM assistant: The rise of Agentic AI in daily task managementPart 2 of our Gen AI for PM series Intro: Project managers juggle endless moving parts—status updates, task assignments, shifting priorities, and the constant chase for clarity. Too often, valuable…|
Blogby Dinesh R Singh, Nisha Rajput, Varsha ShekhawatAug 11, 2025
Part 11: Agentic AI versus AI agentIntroduction Artificial Intelligence (AI) is evolving rapidly, and two terms — Agentic AI and AI agent — are increasingly appearing in business strategy documents, technical roadmaps, and boardroom…|
Blogby Dinesh R SinghJul 21, 2025
Part 5: Agentic AI: Team coordination mode in actionOne of the most transformative patterns in Agentic AI is team-based orchestration — a collaborative approach where specialized agents work together to fulfill complex goals. In this edition, we…|
Blogby Dinesh R SinghJul 9, 2025
Part 2: What makes AI agents truly intelligentIn the first part of this series, I discussed the shift from passive large language models to more capable, action-oriented AI. Now, I will provide a closer look at what actually powers this…|
Blogby DINESH R SINGHJul 3, 2025
From generative to agentic AI: Tracing the leap from words to actionsAI has come a long way from simply finishing our sentences. Today, it’s not just generating content — it’s actively solving problems, making decisions, and executing complex tasks. This blog post…|
Blogby DINESH R SINGHMay 9, 2025
From data centers to centers of data: Navigating the pull of data gravity“Son, when I don’t have the data—people die.“ The room fell silent as a highly decorated Army colonel spoke about supporting frontline combat operations with real-time IT. His point landed hard: in…|
Blogby Denis VilfortMar 16, 2025
Using structured outputs in vLLMGenerating predictable and reliable outputs from large language models (LLMs) can be challenging, especially when those outputs need to integrate seamlessly with downstream systems. Structured outputs…|
Blogby Ismael Delgado MuñozFeb 20, 2025
Deploying a Small Language Model in HPE Private Cloud AI using a Jupyter NotebookDeploying new language models for users to interact with can be challenging for beginners. HPE developed Private Cloud AI to help users set up and implement AI solutions quickly and easily. In this…|
Blogby Dave Wright and Elias AlagnaJan 10, 2025
Why Private AI?Everybody’s getting into AI. The visceral experience of using ChatGPT in professional or personal lives can raise a lot of concern. Concerns about the future of work, creativity... even civilization's…|
Blogby Jordan NanosNov 14, 2024
Getting started with Retrieval Augmented Generation (RAG)Keeping up with AI technology and understanding more about Generative AI and LLM (Large Language Models) is quickly becoming an imperative. If you are like me, curious but not that much of a data…|
Blogby Didier LalliNov 13, 2024
How to Pick a Large Language Model for Private AINote: this blog is based on a video and slide deck available here on YouTube. As organizations continue to explore the potential of generative AI, choosing the right Large Language Model (LLM) is…|
Blogby Jordan NanosOct 31, 2024
Implementing your AI Breakthroughs Effectively – The Infrastructure to your AIWe’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…|
Blogby Audrey ScribnerOct 9, 2024
Distributed Tuning in Chapel with a Hyperparameter Optimization Exampleexternal blog|
Blogby Lydia Duncan, Michelle StroutOct 3, 2024
Small Language Models: The Next Frontier with Private Cloud AIText|
Blogby Brian GruttadauriaSep 26, 2024
Keeping it Real with a new AI Jam SeriesIt wasn’t that long ago we used to say “Artificial Intelligence". Now we just say A.I. These words are so pervasive in conversation that we are now down to the acronym. But what I have been hearing is…|
Blogby Audrey ScribnerJul 9, 2024
Integrating K8sGPT to empower Kubernetes with AI in HPE GreenLake for Private Cloud EnterpriseThis blog post describes the process to integrate K8sGPT serving a local large language model (LLM) as an artificial intelligence (AI) backend to Kubernetes (K8s) in HPE GreenLake for Private Cloud…|
Blogby Guoping JiaMay 20, 2024
Demystifying machine learning at scale: HPE Ezmeral Unified Analytics in actionIn 2024, businesses are scuffling to seek innovative ways to leverage Generative AI to elevate customer experiences and streamline operational workflows. Traditional machine learning workflows, tools…|
Blogby Alex Ollman Mar 13, 2024
Announcing GenAI studio: Your generative AI playground built on DeterminedExternal Blog|
Blogby Isha GhodgaonkarDec 20, 2023
Mixtral 8x7B could pave the way to adopt the "Mixture of Experts" modelOn December 8th, 2023, Mistral AI released Mixtral 8x7B, a high-quality sparse mixture of experts model (SMoE) with open weights (ref: Mistral AI). What is this Mixtral 8x7B? Very simply, it takes 8 x…|
Blogby SOON HENGSep 15, 2023
Closing the gap between High-Performance Computing (HPC) and artificial intelligence (AI)Scientists and engineers face a number of technical hurdles to utilizing artificial intelligence (AI) techniques alongside high-performance scientific computing applications. Recently, a…|
Blogby Philipp Offenhäuser & Christopher Williams Jun 16, 2023
End-to-end, easy-to-use pipeline for training a model on Medical Image Data using HPE Machine Learning Development EnvironmentIn this blog post, we’ll be covering how HPE Machine Learning Development Environment can add value to your machine learning workflow, as well as how to utilize HPE Machine Learning Development…|
Blogby Isha GhodgaonkarJun 16, 2023
Production-ready object detection model training workflow with HPE Machine Learning Development Environment This in-depth blog tutorial is divided into five separate sections, where I will recount the seamless user experience one has when working with HPE Machine Learning Development Environment, pointing…|
Blogby Andrew MendezSep 29, 2022
HPE GreenLake delivers NVIDIA AI as a serviceBuilding the infrastructure required for AI solutions can be an expensive and daunting undertaking. That’s why an as-a-service option that supports customer flexibility makes so much sense. With…|
Blogby Dale RensingAug 8, 2022
ML Ops – Deploying an ML model in HPE GreenLake Platform ML Ops serviceOverview HPE GreenLake Central is an advanced software-as-a-service platform that provides you with a consistent cloud experience for all your applications and data on-premises or off-premises. It…|
Blogby Thirukkannan MMay 3, 2022
Deep Learning Model Training – A First-Time User’s Experience with Determined – Part 2Determined is an open-source training platform that aims to simplify deep learning (DL) model development and experimentation for data science teams by providing tools like distributing training…|
Blogby Denis ChoukrounApr 14, 2022
Deep Learning Model Training – A First-Time User’s Experience with Determined - Part 1Determined is an open-source deep learning training platform that helps data science teams train models more quickly, easily share GPU resources, and collaborate more effectively. The open-source…|
Blogby Denis ChoukrounFeb 11, 2022
Writing Deep Learning Tools for all Data Scientists, Not Just UnicornsMachine learning (ML) is exploding in popularity, and, as it does, ML tooling is frantically trying to keep up. Tools for everything you can imagine are popping up: data versioning, experiment…|
Blogby By Neil Conway and Alex PutnamNov 4, 2021
Build Transformative AI Applications at Scale with HPE Machine Learning Development EnvironmentBuilding and training optimized machine learning (ML) models at scale is considered the most demanding and critical stage of ML development. Doing it well requires researchers and data scientists to…|
Blogby Alex PutnamFeb 5, 2021
Kubernetized Machine Learning and AI Using KubeFlowEditor’s Note: MapR products and solutions sold prior to the acquisition of such assets by Hewlett Packard Enterprise Company in 2019 may have older product names and model numbers that differ from…|
Blogby Rachel SilverFeb 5, 2021
End-to-End Machine Learning Using ContainerizationEditor’s Note: MapR products and solutions sold prior to the acquisition of such assets by Hewlett Packard Enterprise Company in 2019 may have older product names and model numbers that differ from…|
Blogby Rachel SilverFeb 3, 2021
The Challenges of Sharing GPUs and How to Solve Thempinkish image 4 run ai post Editor’s Note – HPE Ezmeral Container Platform is now HPE Ezmeral Runtime Enterprise. For more information on why the name was changed, please click here. Whether…|
Blogby Raz HalevaJan 22, 2021
Top Trends: Machine Learning, Microservices, Containers, Kubernetes, Cloud to Edge. What are they and how do they fit together?Editor’s Note: MapR products and solutions sold prior to the acquisition of such assets by Hewlett Packard Enterprise Company in 2019 may have older product names and model numbers that differ from…|
Blogby Carol McDonaldJan 22, 2021
Association Rule Mining – Not Your Typical Data Science AlgorithmEditor’s Note: MapR products and solutions sold prior to the acquisition of such assets by Hewlett Packard Enterprise Company in 2019 may have older product names and model numbers that differ from…|
Blogby Kirk BorneJan 15, 2021
Making AI a Reality data drive ai Main body of this blog post was originally published on H2O.ai blog. Published here with permission. Do you want to make AI a part of your company? You can’t just mandate AI. But you can…|
Blogby Ellen FriedmanDec 9, 2020
Types of Machine Learning – Part #2 in the Intro to AI/ML SeriesEditor’s Note: MapR products and solutions sold prior to the acquisition of such assets by Hewlett Packard Enterprise Company in 2019, may have older product names and model numbers that differ from…|
Blogby Saira KennedyNov 25, 2020
Apache Spark Machine Learning TutorialEditor’s Note: MapR products and solutions sold prior to the acquisition of such assets by Hewlett Packard Enterprise Company in 2019, may have older product names and model numbers that differ from…|
Blogby Carol McDonaldNov 25, 2020
Demystifying AI, Machine Learning and Deep LearningEditor’s Note: MapR products and solutions sold prior to the acquisition of such assets by Hewlett Packard Enterprise Company in 2019, may have older product names and model numbers that differ from…|
Blogby Carol McDonaldNov 12, 2020
Artificial Intelligence and Machine Learning: What Are They and Why Are They Important?Editor’s Note: MapR products and solutions sold prior to the acquisition of such assets by Hewlett Packard Enterprise Company in 2019, may have older product names and model numbers that differ from…|
Blogby Saira KennedyOct 28, 2020
Streaming Machine learning pipeline for Sentiment Analysis using Apache APIs: Kafka, Spark and Drill - Part 1Editor’s Note: MapR products and solutions sold prior to the acquisition of such assets by Hewlett Packard Enterprise Company in 2019, may have older product names and model numbers that differ from…|
Blogby Carol McDonaldOct 21, 2020
Fast data processing pipeline for predicting flight delays using Apache APIs: Kafka, Spark Streaming and Machine Learning (part 1)Editor’s Note: MapR products and solutions sold prior to the acquisition of such assets by Hewlett Packard Enterprise Company in 2019, may have older product names and model numbers that differ from…|
Blogby Carol McDonaldAug 14, 2020
Building Dynamic Machine Learning Pipelines with KubeDirectorEditor’s Note – HPE Ezmeral Container Platform is now HPE Ezmeral Runtime Enterprise. For more information on why the name was changed, please click here. Imagine that you’re a data scientist who’s…|
Blogby Joel Baxter & Kartik Mathur & Don WakeJul 8, 2020
Tips and Best Practices to Take Advantage of Spark 2.xOriginal post information: Editor’s Note: MapR products referenced are now part of the HPE Ezmeral Data Fabric. With Apache Spark 2.0 and later versions, big improvements were implemented to enable…|
Blogby Carol McDonaldJul 3, 2020
Spark 101: What Is It, What It Does, and Why It MattersOriginal post information: In this blog post, we will give an introduction to Apache Spark and its history and explore some of the areas in which its particular set of capabilities show the most…|
Blogby Carol McDonaldMar 21, 2018
Why we created HPE Deep Learning CookbookA history behind the Cookbook In the beginning of 2014, when Hewlett Packard Labs (still HP Labs back then, within Hewlett-Packard), embarked on its journey towards Memory Driven Computing and The …|
Blogby Natalia Vassilieva, Sergey SerebryakovNov 26, 2017
CPUs for GPU-enabled deep learningA role of CPUs in Deep Learning pipelines and how many CPU cores is enough for training on a GPU-enabled system How CPUs are typically used in deep learning pipelines Although GPUs are the main engine…|
Blogby Sergey SerebryakovNov 26, 2017
Scaling deep learning workloadsData parallelism, weak and strong scaling, and what you need to know to scale a single training job to multiple CPUs or GPUs Training of many state-of-the-art deep neural networks is a very compute…|
Blogby Sergey Serebryakov|
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PlatformMultimedia
Sustainably Scaling AI Adoption
HPE Private Cloud AI Technical Demo
Developing and deploying AI in the enterprise
LLM Agentic Tool Mesh – Democratizing Gen AI
Enhancing NLP with Retrieval-Augmented Generation: A Practical Demonstration
A new era of software development using large language model tools like ChatGPT
Get Real with AI: Cool AI Use Case, Now What?
Unleashing AI Innovation: A Deep Dive into the HPE Private Cloud AI Software Stack
The open-source advantage: Exploring machine learning through thought leadership
Machines learn from data to be artificially intelligent