Core Functionality - DDN data intelligence platform unifies and harmonizes data, extracting its value and efficiently orchestrating every stage of the AI pipeline [1] - DDN accelerates performance securely and reliably [1] Integration and Compatibility - DDN integrates simply and seamlessly with NVIDIA Enterprise AI factory [1] - DDN accelerates advanced workflows like life science with RAG [1] Performance Enhancement - DDN accelerates performance to reliably meet modern AI demands and scale into the future [1] - DDN enables lightning fast search and low latency object access [1]

Pharmaceutical Industry Challenges - Bringing a new drug to market is a complex process requiring significant data processing, primarily write-intensive simulations [1] - The pharmaceutical industry needs an AI infrastructure and data intelligence platform to run complex simulations at massive scale [2] DDN's Solution - DDN provides a fast and efficient data intelligence platform for complex simulations [2] - DDN has over a decade of experience in deploying and optimizing these types of constructs, powering hundreds of sites [2]

Infinia Platform Overview - Infinia is a data intelligence platform, not just a traditional storage product, offering S3 object interface, CSI, Cinder, and file system interfaces [1] - The platform is designed for large-scale deployments, already tested at almost an exabyte in size across approximately 1,000 nodes [1][2] - Infinia is a pure software product that can be integrated into the cloud, with a system already running at GCP for testing [2] Key Features and Capabilities - Infinia supports extensive metadata tagging, allowing tens of thousands of metadata attributes per object for enhanced data discovery and enrichment [1][3] - The system is highly multi-tenant, enabling service providers to manage large-scale systems efficiently while providing SLAs for individual end-users [1][2] - Infinia offers quality of service (QoS) at the application level, allowing prioritization of performance for critical tasks [2] - The platform supports online upgrades, capacity expansion, and reduction without downtime [2] Data Intelligence and AI Workloads - Infinia can serve as a Lakehouse on-premise, providing object, block, and parallel file system access to the same data [2][3] - Remote bucket support allows Infinia to pull metadata from existing data sets, enabling querying and caching of data from external sources [2] - Native library support and SDK can provide up to 10x performance improvement for data ingestion with frameworks like Spark [3] Performance and Scalability - The system is designed for very large scale, with deployments reaching almost an exabyte of capacity [1][2] - Infinia can deliver millions of object operations per second with single-digit millisecond latency [4] - Client-side data reduction and erasure coding eliminate east-west traffic, improving overall performance [3] Resilience and Availability - The system demonstrated high resilience by maintaining operation with only a short IO delay (10-15 seconds) after an entire rack of 480 drives went offline [4]

AI Infrastructure & Market Trends - Modern AI applications are expanding across various sectors like finance, energy, healthcare, and research [3] - The industry is evolving from initial LLM training to Retrieval Augmented Generation (RAG) pipelines and agentic AI [3] - Vulture is positioned as an alternative hyperscaler, offering cloud infrastructure with 50-90% cost savings compared to traditional providers [4] - A new 10-year cycle requires rethinking infrastructure to support global AI model deployment, necessitating AI-native architectures [4] Vulture & DDN Partnership - Vulture and DDN share a vision for radically rethinking the infrastructure landscape to support global AI deployment [4] - The partnership aims to build a data pipeline to bring data to GPU clusters for training, tuning, and deploying models [4] - Vulture provides the compute infrastructure pipeline, while DDN offers the data intelligence platform to move data [4] Scalability & Flexibility - Enterprises need composable infrastructure for cost-efficient AI model delivery at scale, including automated provisioning of GPUs, models, networking, and storage [2] - Elasticity is crucial to scale GPU and storage resources up and down based on demand, avoiding over-provisioning [3] - Vulture's worldwide serverless inference infrastructure scales GPU resources to meet peak demand in different regions, optimizing costs [3] Performance & Customer Experience - Improving customer experience requires lightning-fast and relevant responses, making time to first token and tokens per second critical metrics [4] - Consistency in response times is essential, even with thousands of concurrent users [4] - The fastest response for a customer is the ultimate measure of customer satisfaction [4] Data Intelligence Platform - DDN's Exascaler offers high throughput for training, with up to 16x faster data loading and checkpointing compared to other parallel file systems [5] - DDN's Infinia provides low latency for tokenization, vector search, and RAG lookups, with up to 30% lower latency [5] - The DDN data intelligence platform helps speed up data response times, enabling saturated GPUs to respond quickly [6]

Product Overview - Infinia is a software-defined, next-generation data intelligence platform designed to support both structured and unstructured data, integrating diverse data sources into a unified platform [1] - Infinia aims to reduce complexity in AI deployments and can be deployed on various hardware configurations, including cloud, data centers, reference architectures, and OEM solutions [1] - Infinia operates on the premise of SLAs for capacity, performance, and resilience, abstracting away traditional storage management complexities like volumes and IOPS capping [1] Key Features and Capabilities - Infinia focuses on simplifying data ingestion with low-latency access, emphasizing data tagging for categorization and retrieval in complex environments with billions of objects [1] - Infinia addresses limitations in existing storage solutions by offering unlimited metadata scalability, allowing for thousands of tags per object to refine data definition [1] - Infinia includes capabilities for filtering data at the edge, enabling efficient transfer of relevant data to the core data center for analytics [2] - Infinia offers a software development kit (SDK) to enable customers and service providers to accelerate their applications by using a high-performance interface into Infinia [2] Performance and Efficiency - Infinia achieved a 22x speedup in an indexing and ingest workload on AWS by integrating Nvidia GPUs and utilizing Infinia's S3 interface, resulting in a 70% reduction in GPU resource consumption [1][2] - The company demonstrated a factor of 600 speedup in certain workloads related to identifying data for training AI models [1] Architecture and Integration - Infinia implements data services on top of a key-value store, providing different views onto the data through protocols like S3, file interfaces, and SQL interfaces [2] - Infinia includes a massively distributed SQL server, allowing native access to data and metadata stored in the key-value store through SQL queries [2]

Strategic Partnerships & Market Positioning - The AI market is highly competitive, necessitating strong partnerships with GPU providers who advocate for customers and offer enterprise-grade infrastructure [1] - Nebius aims to position itself as a global AI company by partnering with leading players like DDN in the data intelligence platform space [3] - Synergy between Nebius and DDN is seen as a recipe for success, providing access to enterprise and sovereign AI customers [2] Customer Needs & Solutions - Many customers are new to AI and seek guidance on ROI, facing challenges with expensive and confusing data center infrastructure investments [1] - Customers require assistance in navigating the complexities of AI deployment, seeking solutions for large-scale training that are not limited to hyperscalers or on-premise deployments due to high capital expenditure (capex) and megawatt requirements [2] - Nebius addresses these challenges by providing preemptive data center solutions, eliminating on-demand deployment constraints [2] Product Development & Adaptation - Nebius is continuously adapting its product based on feedback from partners like DDN and their enterprise clients to meet industry needs [4] - Data management platforms are crucial for customers to ensure reliability as they scale their cloud infrastructure [3]