DDN is bringing to bear some really powerful experiences, products and engineering to bear with deep deep expertise. We are able to bring the best of high performance computing and workloads that we need to process in the cloud as well as onrem. I believe that DDN is at a juncture now where we can add huge value in processing any kind of AI workload.Why. Because we are AI data platform ready. We're ready to go and connect the two whether you're onrem, hybrid or purely in the cloud.We're working with hypersc ...

General Sentiment - The document expresses a feeling of "Heat"[1] Music Industry - The document mentions "Music"[1]

Industry Transformation & Vision - The industry is undergoing a profound and global transformation, impacting work, leisure, health, security, and safety [1] - This transformation represents a pivot of the global economy [1] Enterprise Adoption & ROI - Enterprises need to adopt new technologies at an accelerated pace for the ROI to be effective [2] - Efficient infrastructure in data centers or clouds is crucial for ROI [2] Application Layer Acceleration - Supercharging the application layer is a significant enabler and accelerator [2]

AI Infrastructure Focus - DDN is focused on helping organizations across all industries benefit from AI [2] - DDN's technology is designed to address AI requirements at any scale [3] Technological Advancement - DDN aims to make AI-enabled data centers more efficient, reliable, and cost-effective [2] - DDN targets a 10x improvement in performance and efficiency, while reducing power requirements and footprint by 10x [2] Market Position - DDN powers more than 500,000 GPUs across all industries globally [3] - DDN is solving problems inside the data center and cloud, and above the stack [3] Industry Application - DDN is providing solutions for autonomous driving, manufacturing, and the energy sector [4]

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]

Computing Acceleration - Moore's Law 的放缓促使行业寻求新的加速计算方法 [2] - 公司通过算法重构和并行处理，实现了计算加速，提高了成本和能源效率 [3] - 这种加速使得在计算领域进行机器学习和人工智能成为可能 [4] Technological Innovation - 公司致力于通过 CUDA 来增强应用层 [1] - 公司通过极端的计算方式，让计算机能够自主发现洞察 [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应用与数据 - AI应用正从训练模型转向利用前沿模型解决大型问题[1] - 应用阶段的数据重要性被低估，AI需要访问信息而非原始数据[1] - 行业正在将对象和原始数据的存储重构为数据智能[1] 存储与计算 - 数据智能为全球企业提供AI运行所需的信息结构[1] - 这代表着计算和存储关系的非凡重构[1]

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]

Company Overview - Indosat Ooredoo Hutchison (Indosat) was the first brand to connect Indonesia to the world 57 years ago [1] - Indosat's mission is to help Indonesia with early AI adaptation and democratization [2] AI Initiatives and Results - Indosat has an AI factory that is up and running, showing good early trends [2] - AI is being applied in banking financial services, oil and gas, agriculture, and healthcare [2][3] - AI empowers doctors to improve diagnosis in a country with doctor shortages [3] - AI plays a significant role in telco operators' capital expenditure and network planning [3] - AI helps Indosat achieve more with less capital expenditure [4] Strategic Partnerships and Data Sovereignty - Indosat is committed to building sovereign capability with partners like Nvidia and DDN [5] - Countries are aiming for 40% to 70% sovereign workload, emphasizing data localization [5] - Data within the country must comply with local laws and regulations [5] - A country's intelligence and data are considered strategic natural resources [5]