Optimizing Storage for AI Workloads with Solidigm
In this presentation, Ace Stryker from Solidigm discusses the company’s unique value proposition in the AI data infrastructure market, focusing on their high-density QLC SSDs and the recently announced Gen 5 TLC SSDs. He emphasizes the importance of selecting the right storage architecture for different phases of the AI pipeline, from data ingestion to archiving. […]
The Energy Crunch Is Not a Future Problem with Solidigm
In the presentation by Solidigm at AI Data Infrastructure Field Day 1, Manzur Rahman emphasized the critical issue of energy consumption in AI and data infrastructure. He referenced quotes from industry leaders like Sam Altman and Mark Zuckerberg, highlighting the significant challenge energy poses in scaling AI operations. Rahman discussed findings from white papers by […]
Optimizing Data Center TCO An In Depth Analysis and Sensitivity Study with Solidigm
Manzur Rahman from Solidigm presented an in-depth analysis of Total Cost of Ownership (TCO) for data centers, emphasizing its growing importance in the AI era. TCO encompasses acquisition, operation, and maintenance costs, and is crucial for evaluating cost-effective, high-performance hardware like GPUs, storage, and AI chips. Rahman highlighted the need for energy-efficient solutions and the […]
How Data Infrastructure Improves or Impedes Al Value Creation with Solidigm
Ace Stryker from Solidigm presented on the critical role of data infrastructure in AI value creation, emphasizing the importance of quality and quantity in training data. He illustrated this with an AI-generated image of a hand with an incorrect number of fingers, highlighting the limitations of AI models that lack intrinsic understanding of the objects […]
Next Gen Data Protection and Recovery with Infinidat
Infinidat’s presentation on next-generation data protection and recovery emphasizes the critical need for robust cyber-focused strategies to safeguard corporate infrastructure and critical data assets. Bill Basinas, the Senior Director of Product Marketing, highlights the importance of moving beyond traditional backup and recovery methods to a more proactive approach that prioritizes business recovery. Infinidat’s solutions are […]
AI Workloads and Infinidat
Infinidat’s presentation at AI Data Infrastructure Field Day 1, led by Bill Basinas, focused on the company’s strategic positioning within the AI infrastructure market. Basinas emphasized that Infinidat has been closely monitoring the AI landscape for over a year to identify where their enterprise storage solutions can best serve AI workloads. He acknowledged the rapid […]
Infinidat InfuzeOS for Hybrid Multi Cloud
Infinidat’s InfuzeOS is a versatile operating system designed to support both on-premises and hybrid multi-cloud environments. Initially developed for on-premises solutions, InfuzeOS has been extended to work seamlessly with major cloud providers like AWS and Microsoft Azure. This extension allows customers to experience the same ease of use and robust functionality in the cloud as […]
Infinidat Products – InfiniBox G4 and InfiniBox SSA
Infinidat’s presentation at AI Data Infrastructure Field Day 1, led by Bill Basinas, Sr. Director of Product Marketing, focused on their latest storage solutions, the InfiniBox G4 and InfiniBox SSA. Basinas highlighted the unique software-defined architecture of Infinidat’s products, which leverage commodity hardware components to deliver high performance and resilience. The core of their technology, […]
Revolutionizing Enterprise Storage with High Performance and Unmatched Customer Support from Infinidat
Infinidat, a company founded in 2011 with deep roots in enterprise storage, has established itself as a critical player in the IT storage infrastructure for some of the world’s largest companies. The company’s founder, who previously created EMC Symmetrix and sold XIV to IBM, has leveraged this extensive experience to build Infinidat into a provider […]
Streamline AI Projects with Infrastructure Abstraction from HPE
In this presentation, Alex Ollman from Hewlett Packard Enterprise (HPE) discusses the transformative potential of infrastructure abstraction in accelerating AI projects. The focus is on HPE’s Private Cloud AI, a solution designed to simplify the management of complex systems, thereby allowing data engineers, scientists, and machine learning engineers to concentrate on developing and refining AI […]
Building a Generative AI Foundation with HPE
Join Hewlett Packard Enterprise’s product team for a deep dive into the AI architecture and infrastructure needed to deploy generative AI at enterprise scale. We’ll explore the essential components—from high-performance compute and storage to orchestration—that power these models. Using real-world case studies, we’ll uncover the intricacies of balancing computational resources, networking, and optimization. Discover how […]
A Step-by-Step Guide to Build Robust AI with Hewlett Packard Enterprise
Generative AI holds the promise of transformative advancements, but its development requires careful planning and execution. Hewlett Packard Enterprise (HPE) leverages its extensive experience to navigate the intricacies of building enterprise-grade generative AI, covering aspects from infrastructure and data management to model deployment. Alexander Ollman, a product manager at HPE, emphasizes the importance of integrating […]
Managing Google Cloud Storage at Scale with Gemini
In the presentation, Manjul Sahay from Google Cloud discusses the challenges and solutions for managing vast amounts of data in Google Cloud Storage, particularly for enterprises involved in data-intensive activities like autonomous driving and drug discovery. He highlights that traditional methods of data management become ineffective when dealing with billions of objects and petabytes of […]
Google Cloud Vertex Al & Google Cloud NetApp Volumes
Rajendraprasad Hosamani from Google Cloud Storage presented on the integration of Google Cloud Vertex AI with Google Cloud NetApp Volumes, emphasizing the importance of grounding AI agents in bespoke, enterprise-specific data. He highlighted that AI workloads are diverse and that agents can significantly enhance user experiences by providing interactive, personalized, and efficient data sharing. For […]
Google Cloud Storage for AI ML Workloads
In his presentation on Google Cloud Storage for AI ML workloads, Dave Stiver, Group Product Manager at Google Cloud, discussed the critical role of cloud storage in the AI data pipeline, particularly focusing on training, checkpoints, and inference. He emphasized the importance of time to serve for machine learning developers, highlighting that while scalability and […]
Workload and AI-Optimized Infrastructure from Google Cloud
Sean Derrington from Google Cloud’s storage group presented on the company’s efforts to optimize AI and workload infrastructure, focusing on the needs of large-scale customers. Google Cloud has been working on a comprehensive system, referred to as the AI hypercomputer, which integrates hardware and software to help customers efficiently manage their AI tasks. The hardware […]
A Demonstration of the MinIO Enterprise Object Store – The AI-Centric Feature Set
MinIO’s AI feature set is expansive, but there are core features that allow enterprises to operate at exascale. Those include observability, security, performance, search and manageability. In this segment, MinIO goes from bucket creation to RAG-deployment, emphasizing each core AI feature and why it matters to enterprises with data scale challenges that run from PBs […]
Why MinIO is Winning the Private Cloud AI Battle
Many of the largest private cloud AI deployments run on MinIO and most of the AI ecosystem is integrated or built on MinIO, from Anyscale to Zilliz. In this segment, MinIO explains the features and capabilities that make it the leader in high-performance storage for AI. Those include customer case studies, the DataPod reference architecture […]
Why AI is All About Object Storage with MinIO
Almost every major LLM is trained on an object store. Why is that? The answer lies in the unique properties of a modern object store – performance (throughput and IOPS), scale and simplicity. In this segment, MinIO details how AI scale is stressing traditional technologies and why object storage is the de facto storage standard […]