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Nvidia Economics: Make $5-$7 for Every $1 Spent on GPUs
June 30, 2024
Nvidia is saying that companies could make $5 to $7 for every $1 invested in GPUs over a four-year period. Customers are investing billions in new Nvidia hardwa Read more…
Highlights from GlobusWorld 2024: The Conference for Reimagining Research IT
June 11, 2024
The Globus user conference, now in its 22nd year, brought together over 180 researchers, system administrators, developers, and IT leaders from 55 top research Read more…
Google Making Major Changes in AI Operations to Pull in Cash from Gemini
April 4, 2024
Over the last week, Google has made some under-the-radar changes, including appointing a new leader for AI development, which suggests the company is taking its Read more…
The Generative AI Future Is Now, Nvidia’s Huang Says
March 19, 2024
We are in the early days of a transformative shift in how business gets done thanks to the advent of generative AI, according to Nvidia CEO and cofounder Jensen Read more…
Forrester’s State of AI Report Suggests a Wave of Disruption Is Coming
February 28, 2024
The explosive growth of generative artificial intelligence (GenAI) heralds opportunity and disruption across industries. It is transforming how we interact with Read more…
New Alternative AI Model: 10-100x Less GPUs, but Same Results
January 29, 2024
Before the market turned the Eye of Sauron onto GenAI (e.g., ChatGPT), traditional neural networks were receiving most of the attention. These types of neural networks are characterized by having some "short-term" memory and are called Recurrent Neural Networks or RNNs. Read more…
OpenAI CEO Sam Altman Wants to Be the King of Chip-Making but Challenges Await
January 24, 2024
OpenAI's CEO Sam Altman survived an attempt to oust him as the AI company's chief. Now, the maverick wants to establish his own chip-making factories. Altman Read more…
Intel’s Strategy to Free Server Capacity by Pushing AI Inference to PCs
January 18, 2024
AI is here to stay and is becoming a larger part of the workload processed on servers and PCs. That's why Nvidia is seeing success as a chipmaker, and there is excitement around large language models such as Meta's open-source Llama. An eager audience wants to get a handle on such models... Read more…
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From Hallucination to Reality
As Federal agencies navigate an increasingly complex and data-driven world, learning how to get the most out of high-performance computing (HPC), artificial intelligence (AI), and machine learning (ML) technologies is imperative to their mission. These technologies can significantly improve efficiency and effectiveness and drive innovation to serve citizens' needs better. Implementing HPC and AI solutions in government can bring challenges and pain points like fragmented datasets, computational hurdles when training ML models, and ethical implications of AI-driven decision-making. Still, CTG Federal, Dell Technologies, and NVIDIA unite to unlock new possibilities and seamlessly integrate HPC capabilities into existing enterprise architectures. This integration empowers organizations to glean actionable insights, improve decision-making, and gain a competitive edge across various domains, from supply chain optimization to financial modeling and beyond.
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Why IT Must Have an Influential Role in Strategic Decisions About Sustainability
Data centers are experiencing increasing power consumption, space constraints and cooling demands due to the unprecedented computing power required by today’s chips and servers. HVAC cooling systems consume approximately 40% of a data center’s electricity. These systems traditionally use air conditioning, air handling and fans to cool the data center facility and IT equipment, ultimately resulting in high energy consumption and high carbon emissions. Data centers are moving to direct liquid cooled (DLC) systems to improve cooling efficiency thus lowering their PUE, operating expenses (OPEX) and carbon footprint.
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