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Intel plans to ship an AI chip by the end of this year that uses cheaper memory and cooling technology than rival offerings from Nvidia and AMD, as the US chipmaker seeks to capitalize on a sharp turnaround in its fortunes. Kevork Kechichian, who leads Intel’s data center group, told the FT that the company […]
Intel: Our upcoming AI chip will be cheaper, run cooler than Nvidia, AMD options Read More »
LG is currently engaged in exploratory discussions with NVIDIA concerning physical AI, data centres, and mobility. Following a meeting in Seoul between LG CEO Ryu Jae-cheol and Madison Huang, Senior Director of Product Marketing for Omniverse and Robotics at NVIDIA, the core operational dependencies required to run complex automated systems are becoming apparent. While the
What LG and NVIDIA’s talks reveal about the future of physical AI Read More »
Getting stalled enterprise AI rollouts in the EMEA region moving again will require CIOs to aggressively audit their systems. Over the past 18 months, AI deployments across Europe advanced far beyond initial testing. Companies poured capital into large language models and machine learning, expecting heavy operational upgrades. IDC research reveals that boards are slowing down,
At the Google Cloud Next conference, Google and NVIDIA outlined their hardware roadmap designed to address the cost of AI inference at scale. The companies detailed the new A5X bare-metal instances, which run on NVIDIA Vera Rubin NVL72 rack-scale systems. Through hardware and software codesign, this architecture aims to deliver up to ten times lower
NVIDIA and Google infrastructure cuts AI inference costs Read More »
Models like Google Gemma 4 are increasing enterprise AI governance challenges for CISOs as they scramble to secure edge workloads. Security chiefs have built massive digital walls around the cloud; deploying advanced cloud access security brokers and routing every piece of traffic heading to external large language models through monitored corporate gateways. The logic was
Strengthening enterprise governance for rising edge AI workloads Read More »
Run Google’s Gemma 4 models on your own hardware while exposing them via public API using Clarifai Local Runners. Apache 2.0 licensed, multimodal support, and production-ready.
Run Gemma 4 Locally: Deploy Frontier AI on Your Hardware with Public API Access Read More »
An enterprise-ready AMD MI355X guide covering AI inference, LLM training, memory scaling, performance trade-offs, and deployment strategies.
Why GPU Costs Explode as AI Products Scale | Real Drivers Explained Read More »
Learn how to access Ministral 3 via the Clarifai API. Explore open-weight 3B and 14B reasoning models, benchmark performance, and integrate them using Python and Node.js.
Explore NVIDIA GH200 Grace Hopper superchip—architecture, AI use cases, benchmarks, and a decision guide for large-scale LLMs, HPC, and enterprise AI.
Explore NVIDIA GH200 Grace Hopper superchip—architecture, AI use cases, benchmarks, and a decision guide for large-scale LLMs, HPC, and enterprise AI.
NVIDIA GH200 GPU Guide: Use Cases, Architecture & Buying Tips Read More »
