AI workloads relying on vector databases are hitting a new speed record. By offloading Milvus indexing to NVIDIA L40S GPUs using cuVS, and accelerating data movement with Cloudian S3 + RDMA, indexing time dropped from 2 hours to just 16 minutes. This breakthrough removes one of AI’s biggest data bottlenecks — making real-time RAG and vector search faster and more efficient than ever. 👉 Read how it’s done: https://bit.ly/3KYMRHD #AI #VectorSearch #RAG #GPUAcceleration #NVIDIA #Cloudian #Milvus #DataPerformance #AIStorage #AIinfrastructure #StorageforAI #AIindexing

AI workloads relying on vector databases are hitting a new speed record. By offloading Milvus indexing to NVIDIA L40S GPUs using cuVS, and accelerating data movement with Cloudian S3 + RDMA, indexing time dropped from 2 hours to just 16 minutes. This breakthrough removes one of AI’s biggest data bottlenecks — making real-time RAG and vector search faster and more efficient than ever. 👉 Read how it’s done: https://bit.ly/3KYMRHD #AI #VectorSearch #RAG #GPUAcceleration #NVIDIA #Cloudian #Milvus #DataPerformance #AIStorage #AIinfrastructure #StorageforAI #AIindexing

AI workloads relying on vector databases are hitting a new speed record. By offloading Milvus indexing to NVIDIA L40S GPUs using cuVS, and accelerating data movement with Cloudian S3 + RDMA, indexing time dropped from 2 hours to just 16 minutes. This breakthrough removes one of AI’s biggest data bottlenecks — making real-time RAG and vector search faster and more efficient than ever. 👉 Read how it’s done: https://bit.ly/3KYMRHD #AI #VectorSearch #RAG #GPUAcceleration #NVIDIA #Cloudian #Milvus #DataPerformance #AIStorage #AIinfrastructure #StorageforAI #AIindexing

AI workloads relying on vector databases are hitting a new speed record. By offloading Milvus indexing to NVIDIA L40S GPUs using cuVS, and accelerating data movement with Cloudian S3 + RDMA, indexing time dropped from 2 hours to just 16 minutes. This breakthrough removes one of AI’s biggest data bottlenecks — making real-time RAG and vector search faster and more efficient than ever. 👉 Read how it’s done: https://bit.ly/3KYMRHD #AI #VectorSearch #RAG #GPUAcceleration #NVIDIA #Cloudian #Milvus #DataPerformance #AIStorage #AIinfrastructure #StorageforAI #AIindexing

AI workloads relying on vector databases are hitting a new speed record. By offloading Milvus indexing to NVIDIA L40S GPUs using cuVS, and accelerating data movement with Cloudian S3 + RDMA, indexing time dropped from 2 hours to just 16 minutes. This breakthrough removes one of AI’s biggest data bottlenecks — making real-time RAG and vector search faster and more efficient than ever. 👉 Read how it’s done: https://bit.ly/3KYMRHD #AI #VectorSearch #RAG #GPUAcceleration #NVIDIA #Cloudian #Milvus #DataPerformance #AIStorage #AIinfrastructure #StorageforAI #AIindexing

AI has become deeply embedded in our daily lives. The next crucial step is optimization — reducing resource consumption without losing performance. The future will belong to those who can compress and adapt AI models for autonomous use on standard computing power — without relying on supercomputers or specialized GPUs. 👉 The race is not only about building bigger and smarter models, but about making them lighter and more efficient.

Today we unveiled HP's first offering in a brand-new category of devices purpose built for AI development: the ZGX Nano AI Station. Powered by NVIDIA G10 Grace Blackwell Superchip, this tiny powerhouse delivers supercomputer performance to run large AI models locally and accelerate time to results with the exclusive ZGX Toolkit. And yes—it fits in your backpack. Coming this fall. #ZGXNano #AIStation #EdgeAI #NVIDIA

Fujitsu announced an expanded strategic collaboration with NVIDIA to create full-stack AI infrastructure that integrates AI agents. The initiative aims to bolster enterprises’ competitive edge through AI, while preserving their autonomy in AI utilisation. The collaboration will focus on co-developing and delivering an AI agent platform tailored for industry-specific AI agents in sectors such as healthcare, manufacturing, and robotics, along with an AI computing infrastructure that seamlessly integrates the FUJITSU-MONAKA CPU series and NVIDIA GPUs via NVIDIA NVLink Fusion. #AI #GPUs #fullstack #infrastructure #sectors https://lnkd.in/gUeU9bCb

AI Factories power the world’s most ambitious AI deployments—but without the right data platform, pipelines stall, GPUs sit idle, and millions are wasted. Backed by an eight-year NVIDIA partnership, DDN delivers faster time-to-insight, lower costs, and a durable competitive edge. Ready to put every GPU to work?

Jensen at Citadel Securities conference: >We're only at "a few hundred billion" of infrastructure vs. trillions needed annually >Meta recovered "billions of market cap decline" using NVIDIA GPUs to fix AI attribution data lost from Apple >Digital labor + robotics = $100T addressable market >100% of NVIDIA chip designer/engineer now AI-augmented with Cursor >One rack-scale GPU: 2 tons, 120k watts, $3M >AI accelerating healthcare: Understanding proteins (AlphaFold), cells (EVO 2 partnership with ARC); Can now "talk to a cell like you could talk to a chatbot"