Retrieval-Augmented Generation puts pressure on storage in new ways. Indexing, freshness, and latency all compete.
DDN
Software Development
Chatsworth, CA 94,537 followers
The Global Leader in AI and Data Intelligence Solutions.
About us
DDN is the world’s leading AI and data intelligence company, powering the world’s most demanding AI workloads by keeping GPUs fed, efficient, and productive—at massive scale—so organizations can train, checkpoint, and infer faster with less footprint and power while achieving tremendous ROI from their AI investments. From hyperscalers and next-gen cloud builders to enterprises, governments, and research institutions, DDN delivers proven data intelligence at exabyte scale across hundreds of thousands of GPUs—so customers can deploy AI with confidence, accelerate time-to-value, and realize outsized returns.
- Website
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https://bit.ly/4lonBqM
External link for DDN
- Industry
- Software Development
- Company size
- 1,001-5,000 employees
- Headquarters
- Chatsworth, CA
- Type
- Privately Held
- Specialties
- Artificial Intelligence, Data Storage, Machine Learning, Analytics, Enterprise AI, High-Performance Computing, Genomics, Security, Data Science, Generative AI, and NVIDIA Preferred Partner – AI & Data Infrastructure
Locations
Employees at DDN
Updates
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What a week at #PEARC26! 👏 From the AI Factory on Wheels to standout conversations across the research community, DDN showed how AI Infrastructure is powering the future of research. Explore the photos and relive the best moments from PEARC26 ⬇️ PEARC Conference Series
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Keep GPUs productive and AI economics moving at AI4. ⚡ DDN’s Brian McCloskey, VP of Strategic Accounts, will present “The Data Engine Powering the AI Economy” at the Vultr Theatre during Ai4 - Artificial Intelligence Conferences . He will share how enterprises, AI-native labs, and sovereign AI programs can improve GPU utilization, reduce cost per token, and turn AI Infrastructure into a profitable, productive asset. 🗓️ Tuesday, August 4 🕟 4:30 PM PDT 📍 Vultr Theatre ➡️ Join the session to learn how the right data engine can accelerate AI performance, efficiency, and scale.
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That's a wrap on day two at #PEARC26! 👏 Thank you to everyone who stopped by Booth #504, toured the DDN AI Factory on Wheels, and joined today’s sessions with Philip and Morris! We’ll see you back at the bus tomorrow for the last day. 🔗 Book a meeting → bit.ly/4ghZtqV
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Smarter AI starts with smarter infrastructure. 💡 Thanks to everyone who joined Morris Skupinsky's session at #PEARC26 to learn how effective LM Cache can reduce recompute, minimize token waste, expand context windows, and help maximize GPU efficiency. If you missed the session, stop by Booth #504 to continue the conversation or stay tuned on our YouTube channel for the full replay. 🔗 Book a meeting → bit.ly/4ghZtqV
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Day two is underway at #PEARC26 🚌 Stop by Booth #504 to tour the DDN AI Factory on Wheels and see how scalable AI and HPC infrastructure helps research teams move from data to discovery. And don’t miss today’s upcoming DDN session: 🗓️ 12:45 PM CDT Philip A.: “Performance at Scale: How DDN Helps Higher Education Meet Growing Research Data Demands” 🔗 Book a meeting → bit.ly/4ghZtqV
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That’s a wrap on a great first day at #PEARC26 👏 Thanks to everyone who stopped by Booth #504 and toured the AI Factory on Wheels. We’ll be back tomorrow at the bus and leading two sessions you won’t want to miss: 🗓️ 10:25 AM CDT Morris Skupinsky: “Reduce Recompute and Token Waste by Enabling Effective LM Cache with DDN” 🗓️ 12:45 PM CDT Philip A.: “Performance at Scale: How DDN Helps Higher Education Meet Growing Research Data Demands” 🔗 Book a meeting → bit.ly/4ghZtqV
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DDN reposted this
Jensen's framing is spot on, and the implication runs deeper than models. Every serious AI system now runs as a pipeline, not a prompt. Weights, data, caches, retrieval, agents calling other agents across a fleet. That pipeline is the attack surface. At DDN we power more than a million GPUs, and I'll say plainly what we see: compromise reaches the infrastructure long before it reaches the model. Which is why open matters — not as ideology, as engineering. You cannot defend what you cannot inspect. A defensive stack built entirely on systems no one outside can examine is one company's mistake away from becoming everyone's incident. We watched that happen this month. The next decade of AI will be built by the nations and enterprises that demand three things at once: frontier capability, full inspectability, and sovereign control. Not as a trade-off. As a baseline. That is what we are building toward at DDN. Fantastic to see NVIDIA putting real tooling behind this rather than a statement of principles. #OpenSecureAIAlliance #AISecurity #FrontierAI #OpenModels #OpenWeights #OpenSource #SovereignAI #AIInfrastructure #DataInfrastructure #DDN #NVIDIA #AIFactory #Cybersecurity #CyberDefense #AgenticAI #Inference #GPU #DataEngine #EnterpriseAI #CriticalInfrastructure #NationalSecurity #TokenEconomics #AICompute #TrustworthyAI #AIGovernance
Attackers have frontier AI. Defenders need a frontier AI ecosystem—the best open and closed models, force-multiplied by a global community. During the Hugging Face incident, closed AI blocked essential forensics. An open-weight frontier model helped contain the intrusion. That’s why we created the Open Secure AI Alliance. https://lnkd.in/g-sP-xb7
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Minneapolis, your next AI breakthrough just pulled up. 🚌 Day one of #PEARC26 is underway, and the DDN AI Factory on Wheels is ready for visitors at booth #504 (you can't miss us). Step aboard to see how scalable AI and HPC infrastructure helps research teams turn complex data into discovery. Stop by the bus, meet the DDN team, and explore the AI Infrastructure powering what comes next: bit.ly/4ghZtqV PEARC Conference Series
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