StorageGuru-Louis
@StorageLoui
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Sharing expert insights on scalable, secure data solutions for the AI revolution. One byte at a time. Works at DDN #AI #StorageTech
Joined April 2025
Tackling data bottlenecks is key in AI,DDNโs approach makes sense for high-stakes industries like finance. Efficiency wins here.
๐ Maximize GPU Efficiency. Minimize AI Costs. In financial services, speed isnโt just an advantage โ itโs everything. But whatโs holding your AI performance back? Itโs not the computeโฆ itโs the data. Discover how DDNโs Data Intelligence Platform helps financial institutions:
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Sovereign AI hinges on infrastructure that keeps data secure and accessible at scale. Solutions that balance speed with governance are key,especially as workloads grow.
๐ Sovereign AI is here โ and itโs redefining the role of data infrastructure. As AI becomes a pillar of national strategy, security, and innovation, sovereignty over data is no longer optional โ itโs essential. But achieving Sovereign AI takes more than policy. It demands a new
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Impressive to see Exascaler leading in performance,critical for HPC and AI workloads. Real-world impact when speed matters
๐จ #1 on IO500 โ DDN is the Undisputed Leader ๐จ The results are in โ and the numbers speak for themselves. When your mission is curing disease, securing global markets, or building the future of AI, your infrastructure can't just keep up. It has to lead. ๐ On the latest
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Great post,data movement is often the hidden cost in AI scaling. Exascalerโs parallel I/O could be a game-changer for firms needing speed without compute waste.
๐ธ In financial services, milliseconds matterโand underutilized GPUs can cost millions. As firms scale AI for fraud detection, risk modeling, and algorithmic trading, one silent bottleneck is slowing everything down: data movement. ๐ซ The issue isnโt your compute powerโitโs
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Great read on AI inference myths,storage performance is a silent hero in scaling models effectively.
๐จ AI inferencing isnโt an afterthought โ itโs the front line. In his latest piece for Forbes, DDN CTO Sven Oehme breaks down five costly myths about AI inference that are quietly draining performance, budget, and business value. From underpowered storage to misaligned cloud
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Impressive to see HPC/storage solutions accelerating life sciences. Real-world impact matters.
๐ฅ See DDN in action powering real-world innovation in life sciences! At Scripps Research, AI and high-performance computing are transforming how researchers tackle some of the worldโs most complex biomedical challenges. From drug discovery to disease modeling, speed and scale
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Excited to see how Exascalerโs scalability supports AI advancements at RAISE.
๐ Kicking off RAISE in Paris with purpose, people, and powerful AI! Get a sneak peek at the energy behind DDNโs Beyond Artificial: AI Data Summit with Wyatt Gorman, Product Manager, HPC, Google Cloud โ straight from the streets of Paris. ๐ซ๐ท From real-world edge deployments to
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The infrastructure gap is a real bottleneck for AIโs potential. Scalable, high-performance storage isnโt just helpful,itโs essential for keeping up with next-gen AI workloads. Time to rethink the stack.
๐ค Agentic AI is the next frontierโbut thereโs a critical infrastructure gap. New analysis from SiliconANGLE & theCUBE Research highlights a growing challenge: while LLMs are rapidly evolving into autonomous agents, the underlying data infrastructure often can't keep up. In our
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Great recognition for a leader whose vision has driven real innovation in storage tech. Well deserved!
Weโre thrilled to share that Alex Bouzari, our CEO and Co-Founder, has been named a finalist for the Entrepreneur Of The Yearยฎ Award in the Greater Los Angeles area! ๐ For nearly three decades, Alexโs visionary leadership, relentless drive, and passion for innovation have
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Unified workflows are key for AI,Exascalerโs scalable I/O helps eliminate bottlenecks by keeping data flowing where itโs needed most. Small changes, big impacts.
โก๏ธ AI innovation is acceleratingโbut fragmented workflows are dragging organizations down. Disconnected systems, siloed data, and duplicated infrastructure are creating costly bottlenecks and slowing down progress. The fix? A unified approach to AI training and inference. ๐ ๏ธ
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Key takeaway: scalability in AI needs the right hardware, software, and partnerships. @DDNintelligence and @Supermicro_SMCI shows how this synergy drives innovation. ๐ก
What makes an AI infrastructure ๐ต๐ณ๐ถ๐ญ๐บ ๐ด๐ค๐ข๐ญ๐ข๐ฃ๐ญ๐ฆ? According to @Supermicro_SMCI CEO Charles Liang, itโs a combination of the ๐ฟ๐ถ๐ด๐ต๐ ๐ต๐ฎ๐ฟ๐ฑ๐๐ฎ๐ฟ๐ฒ, ๐๐ต๐ฒ ๐ฟ๐ถ๐ด๐ต๐ ๐๐ผ๐ณ๐๐๐ฎ๐ฟ๐ฒ, ๐ฎ๐ป๐ฑ ๐๐ต๐ฒ ๐ฟ๐ถ๐ด๐ต๐ ๐ฝ๐ฎ๐ฟ๐๐ป๐ฒ๐ฟ๐๐ต๐ถ๐ฝ. At ๐ฝ๐๐ฎ๐ค๐ฃ๐
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DDN with NVIDIAโs NeMo Retriever highlights how AI and storage are converging. Enterprises chasing speed and scalability for data workloads,this is a key step forward. Worth noting.
The future of ๐ฒ๐ป๐๐ฒ๐ฟ๐ฝ๐ฟ๐ถ๐๐ฒ-๐ด๐ฟ๐ฎ๐ฑ๐ฒ, ๐๐-๐ฝ๐ผ๐๐ฒ๐ฟ๐ฒ๐ฑ, ๐๐ฎ๐๐ฎ ๐๐ป๐๐ฒ๐น๐น๐ถ๐ด๐ฒ๐ป๐ฐ๐ฒ demands infrastructure that is ๐ณ๐ฎ๐๐๐ฒ๐ฟ, ๐๐บ๐ฎ๐ฟ๐๐ฒ๐ฟ, ๐ฎ๐ป๐ฑ ๐ฏ๐๐ถ๐น๐ ๐ณ๐ผ๐ฟ ๐๐ฐ๐ฎ๐น๐ฒ. Thatโs why DDN is working with NVIDIA's NeMo Retriever to unlock high-efficiency
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Scaling LLMs from pilots to production isnโt easy,DDNโs Exascaler and Infinia handle the heavy lifting. Solid foundation for data pipelines and performance. Worth a read.
๐ง LLMs are growing upโare you ready to scale with them? From pilot projects to production powerhouses, Large Language Models are transforming how organizations operate. But with that evolution comes serious challenges: โ๏ธ Complex data pipelines ๐ Performance bottlenecks โ๏ธ
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Why your AI is stuck? Storage is the silent bottleneck. Optimize it, and watch training times shrink. #AI #HPC #SmartStorage
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Storage is the unsung hero of #AI. Think of it like your modelโs "food supply", slow storage = starving algorithms. Ever waited days for a model to train? Blame the storage. (And no, more GPUs wonโt fix that. Trust me.)
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The โhiddenโ AI storage challenges: - Consistency : Edge devices, clouds, and on-prem must sync. - Security: Training data is priceless, but whoโs guarding it? - Cost: Public cloud storage bills can sink even the hippest AI startup.
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Storage isnโt just a โdiskโ, itโs a strategic advantage. - Tiered storage cuts costs (hot data on flash, cold on cheaper media). - Parallel architectures let you *feed* models at scale. - Smart caching? Cuts latency like a hot knife through butter.
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AI isnโt just algorithms.. itโs data velocity. A single deep learning model can chew through petabytes in hours. Traditional storage? Designed for storing, not speed. Result? 90% of your compute budget wasted waiting for data. ๐คฏ
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Why does storage matter for #AI? ๐ Think of it as the โnervous systemโ of your models. Slow storage? Your AI โstarvesโ, training takes weeks instead of days. Fast, smart storage? Models learn faster, iterate quicker, and *actually deliver value*. Letโs dive in!
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DDN and NVIDIA teaming up = powerful stuff. Excited to see how this drives AI forward. Check out the details ๐
Honored by these words. DDN is proud to partner with NVIDIA to fuel AI innovation and accelerate the worldโs transformation. Hear it from the visionary himself: ๐ Discover more about our work with @NVIDIA:
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