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Optical technology enabling the growth of artificial intelligence

CIO

Artificial intelligence (AI) has a pivotal role to play. But in order for AI to expand, we need new networking technology that boosts transmission speeds and improves responsiveness. What are Large Language Models (LLMs)? Learn more about IOWN here. The answer? Innovation

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Swiss energy services company uses machine learning to see the future

CIO

Swiss energy services company IWB has a vision of a world with a fully renewable, climate-friendly energy supply. For many years, IWB’s distribution grid supplied customers with electricity exclusively produced by large, centralized power plants. If you want to look into the future, sometimes you have to be able to predict it.

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Know before you go: 6 lessons for enterprise GenAI adoption

CIO

That quote aptly describes what Dell Technologies and Intel are doing to help our enterprise customers quickly, effectively, and securely deploy generative AI and large language models (LLMs).Many That makes it impractical to train an LLM from scratch. Training GPT-3 was heralded as an engineering marvel.

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ASUS unveils powerful, cost-effective AI servers based on modular design

CIO

For successful AI deployments, IT leaders not only need the latest GPU/CPU silicon, they also need artificial intelligence (AI) servers that establish a foundation. Performance boost technology ASUS developed three capabilities to further improve processor performance. To learn more, visit [link] Artificial Intelligence

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Powering the future: How Gen AI and AI illuminate utility companies

CIO

While international conflict, economic uncertainty and climate change are affecting businesses of all kinds, energy companies and utilities are also dealing with aging infrastructure, constant cyberattacks, increased regulation and rising customer expectations. Meeting all these requirements places a tremendous burden on energy companies.

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Gen AI without the risks

CIO

On top of that, Gen AI, and the large language models (LLMs) that power it, are super-computing workloads that devour electricity.Estimates vary, but Dr. Sajjad Moazeni of the University of Washington calculates that training an LLM with 175 billion+ parameters takes a year’s worth of energy for 1,000 US households.

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Dairyland powers up for a generative AI edge

CIO

Previously head of cybersecurity at Ingersoll-Rand, Melby started developing neural networks and machine learning models more than a decade ago. We just came out of the gates fast, and we just kept solving problems,” the CIO says, noting that his team was experimenting with Azure LLMs before they were on the market. “We