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#Nvidia Server Rack
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2.0K
HUNvidia just dropped Vera Rubin basically an entire AI supercomputer squeezed into one rack 🖥️
Here's what's packed inside:
6 custom chips all working together
Vera CPU + Rubin GPU combo
50 petaflops per GPU (that's 2.5x faster than before)
6th gen NVLink switches
Can scale up to 72 Rubin GPUs
Pretty wild design changes too:
No cables, no hoses, no fans at all
Needs liquid cooling to survive
Claims 10x cheaper AI inference (so ChatGPT and Claude could get way cheaper to run)
But here's the crazy part: each rack uses 350 kilowatts that's enough power for 350 homes.
Microsoft, Amazon, and Google are already scrambling to get these deployed in 2025.
Nvidia's not just making chips anymore. They're building the entire infrastructure for AI. The arms race is getting real 🚀
#nvidia #veraRubin #aiSupercomputer #aiInfrastructure #gpuComputing #techNews #dataCenter #aiHardware #cloudComputing #ai2016
@humanness.ai
22
11.0K
HAServer Going CRAZY 🤖
#HardwarePlug 🔌 🔌 🔌
#ai #artificialintelligence #tech #ram
@hardwareplug
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FINVIDIA introduced Vera Rubin, its next-generation AI platform and successor to Blackwell. Named after astronomer Vera Rubin, the system combines a custom Arm-based Vera CPU with a Rubin GPU featuring 288GB of HBM4 memory and up to 50 petaflops of AI performance.
The platform is designed to dramatically improve efficiency, potentially cutting inference costs and reducing the number of GPUs needed to train large models by as much as 75%. Major cloud providers including Microsoft, Google, and Amazon are among the first planning deployments.
Source: NVIDIA
Follow @firstprinciplesconsult for more content like this.
@firstprinciplesconsult
17.5K
DONvidia is a technology company founded in 1993 that originally became famous for making graphics cards (GPUs) for gaming. Its early success came from powering high-performance PC games with its GeForce series, which helped shape modern gaming as we know it.
However, Nvidia’s biggest breakthrough wasn’t just gaming — it was realizing that GPUs could handle massive amounts of calculations at the same time. This made them perfect for artificial intelligence, machine learning, and data processing. The company developed CUDA, a platform that allowed developers to use Nvidia GPUs for advanced computing tasks beyond graphics. That decision positioned Nvidia at the center of the AI revolution.
Today, Nvidia designs some of the world’s most powerful AI chips, such as the A100 and H100, which are used by major tech companies to train large AI models. Because AI systems require enormous computing power, demand for Nvidia’s chips has surged, making it one of the most valuable companies globally in recent years.
#Nvidia #ArtificialIntelligence #AIRevolution #TechNews #FutureOfTechnology
@dout.ai
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FANVIDIA hasn’t literally erased whole data centers, but what the company is doing is transforming how huge data centers work by building extremely powerful, super-dense computing systems that combine thousands of CPUs, GPUs, memory, and ultra-fast networking into what looks and acts like a single AI-supercomputer this is possible thanks to advanced architectures like NVIDIA’s Vera Rubin platform and MGX modular design which put massive GPU clusters, high memory CPUs and high-bandwidth interconnects (like NVLink and InfiniBand) into rack scale systems drastically increasing AI processing power and efficiency compared to older multi-server setups so companies can now run enormous AI training and inference workloads in smaller physical footprints with better speed and lower total operational cost essentially consolidating an entire data-center’s worth of compute power into a few ultra-high-performance machines.
🚀 Deep Tech Explained! 🤖
🔥 NVIDIA turning data centers into ONE mega-machine 💻
📈 AI power unlocked
👍 Like | ↗️ Share | 💬 Comment | ➕ Follow for more
#nvidia #cpu #chatgpt #ai #technology
@factpro.ai
512.5K
HA8 x GPU Ai Server 🤖
Nvidia A100 💥
#HardwarePlug 🔌 🔌 🔌
#ai #artificialintelligence #aiartist #datacenter #datacenters #it #crypto #armenian #managedserviceprovider #tech
@hardwareplug
62.4K
AINVIDIA RTX PRO Servers are enterprise data center systems powered by RTX PRO 6000 Blackwell Server Edition GPUs, designed to accelerate AI, graphics, and scientific computing workloads.
Built on Blackwell architecture, they feature up to eight GPUs per server, each with 96GB of ultra-fast GDDR7 memory, fifth-generation Tensor Cores delivering 3x faster AI performance, and fourth-generation RT Cores for ray tracing.
Available in 2U, 4U, and 6U configurations from Dell, HPE, Lenovo, Supermicro, and Cisco, these passively-cooled servers support applications spanning agentic AI, LLM inference, digital twins, 3D rendering, and industrial simulation. They integrate NVIDIA AI Enterprise software, support multi-instance GPU for isolated workloads, and offer up to 600W configurable power consumption per GPU with PCIe Gen 5 connectivity.
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Source: NVIDIA on Youtube
#AI #Tech #ChatGPT #Nvidia #FutureOfAI #openai #grok #google #meta #claude #anthropic #xai
@ai.blends
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MRThe Nvidia technology that replaces an entire data center.
@mr.devlooper
3.6K
ROGPU ऐसा होता है कूलिंग सिस्टम | ai |GPU |Nvidia |imd #ai #gpu #nvidia #imd #artificialintelligence
@roshangaurjourno
125
MIIs Ai dying? #nvidia #nvidia #pcgaming
@mizochris
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