23.8K
STFrom rack to inference in 41 minutes.
The XE7740 pairs Xeon 6, Gen5 storage, and accelerator flexibility into a platform designed for scalable enterprise AI.
The details matter.
#EnterpriseAI #AIHardware #datacenter
@storagereview
#Xeon Processor Intel
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SKLeave no stone unturned when chasing record-breaking performance
Peter from @asusrog R&D shows their W890 test motherboard for Intel Xeon 600 series processors
More info on the records: https://newsroom.intel.com/intel-products/intel-launches-new-intel-xeon-600-processors-for-workstation
@skatterbencher
84
CO๐๐ข๐ฌ๐๐จ๐ฏ๐๐ซ ๐ ๐ง๐๐ฐ ๐๐ซ๐ ๐จ๐ ๐ก๐ฒ๐ฉ๐๐ซ๐๐จ๐ง๐ฏ๐๐ซ๐ ๐๐ ๐ข๐ง๐๐ซ๐๐ฌ๐ญ๐ซ๐ฎ๐๐ญ๐ฎ๐ซ๐ ๐ฐ๐ข๐ญ๐ก ๐ญ๐ก๐ ๐ข๐ง๐๐ฎ๐ฌ๐ญ๐ซ๐ฒโ๐ฌ ๐๐ข๐ซ๐ฌ๐ญ ๐ญ๐ซ๐ฎ๐ ๐ฆ๐ฎ๐ฅ๐ญ๐ข-๐ฏ๐๐ง๐๐จ๐ซ ๐๐๐ ๐๐ฉ๐ฉ๐ฅ๐ข๐๐ง๐๐.
The ๐๐๐ง๐จ๐ฏ๐จ ๐๐ก๐ข๐ง๐ค๐๐ ๐ข๐ฅ๐ ๐
๐ ๐๐๐ซ๐ข๐๐ฌ is built for flexibility, giving you the power to scale and evolve your IT environment without costly hardware replacements.
โ๏ธ Choose the HCI software stack that aligns with your business goals
โ๏ธ Seamlessly transition and convert workloads across supported ISVs
โ๏ธ Streamline operations with appliance-grade deployment, lifecycle management, and centralized monitoring
Future-ready infrastructure starts here: https://www.lenovo.com/us/en/servers-storage/sdi/thinkagile-fx-series/?linkId=899289146
For More information, Reach out to our Product managers
Thilina Dharmarathna | thilina@connexit.biz | +94 71 988 2955
Koshitha Pahalanayaka | koshitha@connexit.biz | +94 76 929 8335
@connexinformationtechnologies
2.8K
SYNVIDIA NVLink Fusion is a high-bandwidth, low-latency interconnect that lets multiple GPUs behave like a single accelerator.
Unlike PCIe, NVLink provides:
โข Direct GPU-to-GPU memory access
โข Massively higher bandwidth (TB/s class links)
โข Lower latency for distributed AI workloads
NVLink Fusion extends this by enabling heterogeneous scaling โ GPUs, CPUs, and custom accelerators sharing memory coherently across nodes.
Thatโs how LLMs, digital twins, and trillion-parameter models scale without bottlenecks.
๐ AI isnโt limited by compute anymore. Itโs limited by interconnects.
Follow for deep-tech explained simply โก
Save this if youโre into AI hardware & chip architectures
Source: NVIDIA
#NVIDIA #NVLink #AIHardware #GPUs #DataCenter
@systologix.ai
156
ELThe AI infrastructure game just changed.
NVIDIA NVLink Fusion introduces a breakthrough in silicon innovation โ empowering hyperscalers to build hybrid ASIC AI architectures with unmatched scale-up performance.
Powered by NVIDIAโs industry-proven NVLink and rack-scale architecture, this technology unlocks next-level bandwidth, ultra-low latency, and seamless GPU-to-ASIC integration.
This isnโt just evolution.
Itโs AI infrastructure redefined.
Follow ๐ @electroonix for more!
#NVIDIA #NVLink #cloudcomputing #Hyperscale #technology
@electroonix
124
GR๐ค NVIDIA MEETS INTEL!
๐ THE FULL STORY:
In a surprising industry shift, NVIDIA is reportedly preparing to use Intel Foundry nodes for its future 'Feynman' AI GPU architecture. While core chips will still rely on TSMC's 1.6nm process, up to 25% of the silicon value will be built on Intel 18A or 14A nodes. This move follows NVIDIA's recent 5% equity stake in Intel, signaling a desire to insulate its supply chain from geopolitical risks. The collaboration marks a massive win for Intel's foundry business, which aims to compete with TSMC on US soil.
๐ง KEY TAKEAWAYS:
โข Partial use of Intel 18A/14A nodes.
โข Core IP remains with TSMC A16.
โข Diversification to avoid supply bottlenecks.
๐ WHY IT MATTERS: It creates a more resilient hardware ecosystem for the next generation of trillion-parameter AI models.
๐ฃ๏ธ ENGAGE: Can Intel become a true rival to TSMC?
#NVIDIA #Intel #Semiconductors #AIHardware #GPU TechSupplyChain HardwareNews
@grid7tech
122
AD5 ways the PowerEdge XR8000 thrives anywhere
Thrive at any edge with the Dell PowerEdge XR8000, an ultra-compact, high-performance server designed to deliver lower latency, scalability, and cutting-edge storage capabilities.
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#myasiph #AdvanceSolutionsInc #asi #DellTechnologies #PowerEdge #Server
@advancesolutionsph
176
THYou donโt scale AI with slow storage.
Full NVMe stack โก
Enterprise Micron drives ๐ง
Serious airflow ๐ฅ
Built for speed.
Built the Data Forge way. ๐
#DataForge #ServerBuild #NVMe #TechPower #DataCenter
@thedataforge
288
SYNVIDIA NVLink is a high-bandwidth, low-latency interconnect designed for direct GPU-to-GPU communication.
Unlike PCIe, which routes traffic through the CPU and shares bandwidth across devices, NVLink creates a dedicated high-speed bridge between GPUs โ dramatically increasing data throughput and memory coherence.
๐น PCIe Gen5 x16 โ ~128 GB/s (bidirectional)
๐น NVLink (latest gen) โ 900+ GB/s per GPU pair
This means faster tensor exchange, larger model parallelism, and near-linear scaling in AI clusters.
Thatโs why large language models and HPC workloads rely on NVLink fabrics instead of traditional PCIe bottlenecks.
Follow @systologix.ai for deep tech breakdowns in 60 seconds.
Source: Nvidia (YT)
#NVIDIA
#NVLink
#GPUComputing
#ArtificialIntelligence
#AIInfrastructure
@systologix.ai
91
ITStop letting lag kill your innovation. ๐ข๐ซ
When you are training large language models, time is literally money. Legacy hardware just canโt keep up with todayโs demands. Itโs time to switch to the NVIDIA H100 and experience massive memory bandwidth and speed.
Don't wait for results. Create them.
๐
https://itctshop.com/ ๐ +971504650867
#NVIDIA #H100 #AI #Datacenter #Tech
@itct.shop
50
NEAI and server demand continue to outpace supply at Texas Instruments, keeping lead times extended across key power and logic families. Most parts are running 16โ20 weeks, with automotive grade devices especially constrained as production remains focused on higher end enterprise programs. Want more weekly industry insights? Sign up for NewPowerโs NewPointsยฎ from the link in our bio.
#NewPoints #NewPowerWorldwide #AI #ArtificalIntelligence #Server
@newpowerww
1
STHereโs Why Intel Struggles to Reclaim Its Throne:
Intel (INTC) is facing a tough climb back to relevance, with its stock recently dropping 17% to $45.07 after a weak Q1 2026 forecast. The company reported Q4 2025 revenue of $13.7 billion, beating expectations by $300 million, but its Q1 guidance of $12.2 billion fell $350 million short. Adding to the disappointment, Intel projected breakeven EPS for Q1, well below the expected $0.08. The root of the problem? A blunder to cut production capacity for older CPUs, just as demand from AI powerhouses like OpenAI and AWS surged. This misstep left Intel unable to fulfill orders for its Emerald Rapids and Granite Rapids processors, costing it a golden opportunity in the AI-driven data center market.
Intel is banking on its 18A manufacturing technology and high-profile partnerships to stage a comeback. Deals include a $15 billion contract with Microsoft for custom chips and a multibillion-dollar agreement with AWS for AI-focused Xeon processors. Intelโs foundry unit reported a staggering $10.3 billion operating loss in 2025, and analysts remain skeptical about its ability to compete with TSMCโs advanced N2 chips. With its stock hovering near critical support levels of $40.90 and $32.50, Intelโs future hinges on the success of its new AI products and its ability to regain investor confidence.
Disclaimer: This summary is for informational purposes only and should not be considered financial advice. Past performance of any of the mentioned stocks does in this post does not guarantee future results. Always consult with a financial advisor before making investment decisions.
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โจ #Xeon Processor Intel Discovery Guide
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