So multimodal I think is a necessity in order for enterprises to really benefit from AI. And so with multimodal metadata tagging and the ability to move the metadata part of it becomes essential. That's otherwise the economics simply don't work out.There isn't enough data center space in the world. There isn't enough power in the world to get it done like that. That's so the metadata attributes are very key.And when we started out with Infinia, that was one of the things we focused on. We said it has to be ...

Solution Overview - DDN provides a one-click high-performance RAG (Retrieval-Augmented Generation) pipeline for enterprise use, deployable across various environments [1] - The RAG pipeline solution incorporates NVIDIA NIM within the NVIDIA Nemo framework, hosting embedding, reranking, and LLM models, along with a MILV vector database [2] - DDN Infinia cluster, with approximately 0.75 petabytes capacity, serves as the backend for the MILV vector database [3] Technical Details - Infinia's AI-optimized architecture, combined with KVS, accelerates NVIDIA GPU indexing [3] - The solution utilizes an NVIDIA AI data platform reference design to facilitate the creation of custom knowledge bases for extending LLM capabilities [4] - The one-click RAG pipeline supports multiple foundation models for query optimization [7] Performance and Benefits - Integration between DDN Infinia and NVIDIA Nemo retriever, along with NVIDIA KVS, results in faster response times, quicker data updates, and rapid deployment of custom chatbots [9] - The RAG pipeline enables detailed and accurate responses to specific queries, as demonstrated by the Infinia CLI hardware management features example [8][9]

the great work that we do together in this new product line that you have. The thing about Infinia is using accelerated computing and using artificial intelligence to uh learn from all of the the data that you have uh transform the raw data into data intelligence. Yeah.embedding the intelligence into the model, extracting uh from all of your data, the semantic of it, the intelligence of it, the information of it. Now, instead of serving raw data, you serve metadata, the knowledge, the the intelligence, the ...

Product Overview - Infinia is a ground-up developed product intended as more than just an object store, offering multiple data interfaces [1] - The system provides database access through an SQL interface and can be used as a notification bus, critical for AI workflows [2] - It is a pure software product designed to solve complicated problems, making it attractive for service providers [3] Key Features & Capabilities - Built-in architectural capabilities around multi-tenancy provide technology as a service [4] - Deep integration capabilities through an SDK enable customers to accelerate applications and AI workflows [4] Ecosystem & Partnerships - DDN has ongoing partner development with ecosystem partners to accelerate technology adoption through the Infinia SDK [4]

Overview - DDN Infinia 在 Oracle Cloud Infrastructure (OCI) 上的性能展示，但强调这仅为技术预览，未来可能发生变化 [1] - Infinia 架构提供广泛的数据管理能力，包括多种数据 IO 路径、核心存储组件（如 scale-out KV 存储、always-on 加密和数据缩减）、原生多租户等 [2] - Infinia 完全软件定义和容器化，可在物理或虚拟化硬件上运行，适用于云部署 [2] Technical Details & Performance - 在 OCI 内部测试使用了 6 个 BM dense ioe5 计算实例作为 Infinia 集群的主机，以及 6 个 BM standard E5.192% 实例作为客户端，客户端实例具有单个 100 GB 连接 [2] - 在 dense ioe5 实例中，Infinia 软件仅使用了 128 个可用核心中的 32 个 [2] - 使用 warp 在分布式基准测试模式下进行 IO 生成，确保每个客户端并发地向所有 Infinia 集群节点发送操作，并在所有客户端和所有 Infinia 集群节点之间创建完整的 IO 网格 [3] - Put 操作的吞吐量约为 28 GB/s 到 30 GB/s，每个客户端和每个 Infinia 节点平均处理速度约为 4800 MB/s (约 5 GB/s) [5] - Get 操作的吞吐量约为 35 GB/s 到 37.5 GB/s，负载均匀分布在所有客户端和 Infinia 节点上，约为 6100 MB/s (约 6.5 GB/s) [6] - 实现了 5 毫秒的 time to first byte，对于 S3 对象 IO 来说非常出色 [6] Conclusion - 软件定义的 Infinia 不仅可以在云中的 Oracle 计算基础设施上运行，而且即使是小型六节点集群也能实现出色的性能 [7]

AI Infrastructure Vision - Infinia initiated a new product development in 2017, driven by the need for a different architecture for AI, diverging from existing solutions [1] - The company aimed for an architecture that scales efficiently for training and offers very low latency [1] - Infinia envisioned a distributed, on-premise, and multi-cloud solution where data payloads (images, video) do not move due to cost, relying instead on metadata and tagging [2] Challenges and Innovation - The initial architectural concept for AI was met with skepticism, deemed impossible by some [2] - Infinia adopted a problem-solving approach that disregarded past constraints like file systems [3] - The development process took seven years [3]

AI Infrastructure Challenges - Scaling AI deployments faces data challenges, not just compute limitations [1] DDN Infinia Solutions - DDN Infinia guarantees consistent performance under heavy AI loads [1] - DDN Infinia prevents tenant interference and enforces intelligent QoS (Quality of Service) [1] - DDN Infinia provides full visibility and control across dynamic, multi-tenant environments [1] Session Highlights - The session includes a live demo of DDN Infinia's capabilities [1] - A live expert Q&A session is available for attendees [1]

Good afternoon everybody. So it's really all about customer success and actually we've we've been welcome to GTC 25 it's a year already. Uh by the way I know some of you guys have experienced some of the elevators on building but we should invent some AI controlled elevators at some point.Some people waking up about 30 minutes to get into elevators. So we got something there. Anyway, uh so it's all about customer success and and in a few minutes rebat already yesterday and today uh I tell you we're having a ...

AI Infrastructure & Partnership - Super Micro is positioned as the largest AI OEM infrastructure provider globally [1] - The partnership between Super Micro and DDN aims to provide world-class technology and proven solutions for AI deployment at scale [2][4] - A key focus is on providing support capabilities throughout the investment lifecycle for customers [3] - The collaboration seeks to minimize customers' time to online by integrating solutions in Super Micro's factory and deploying them securely [4] Data Management & Software Solutions - AI development leads to a significant increase in data, and DDN offers expertise in managing this data environment [3] - DDN's shift to a software model with Infinia creates opportunities for flexible deployment leveraging Super Micro technology [5] - Super Micro is capable of integrating Exoscala as a total solution and supporting its deployment [5] Strategic Goals - The shared objective is to capture more market share and support customers in solving significant business challenges through technology [5]

[Music] My name is Dave Mooney. I'm the VP of worldwide data management sales at Lenovo Corporation. The challenges we help our customers overcome is to help them take an idea that they would like to drive and how they could enhance their business with AI and get it implemented first in experimentations and into fast starts all the way into full production.And we can do that from the pocket to the cloud and the data center. We but we're focusing on the enterprise customers. That's where we see the opportuni ...