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Business technology leaders in construction, travel, retail, healthcare and energy say AI is already improving productivity and changing customer behavior. But they are also sorting through its high costs and limitations.

It is hard to keep a model of datacenter infrastructure spending in your head at the same time you want to look at trends in cloud and on-premises spending as well as keep score among the key IT suppliers to figure out who is winning and who is losing. And so we have built a model that does this, and we are calling it the Datacenter Infrastructure Report Card.

Companies covered in this report are Intel Corporation (US), Advanced Micro Devices, Inc. (US), Apple Inc. (US), IBM (US), Marvell (US), MediaTek Inc. (Taiwan), NVIDIA Corporation (us), Achronix Semiconductor Corporation (US), Ranovus (Canada), and ASE Technology Holding Co., Ltd. (Taiwan). Apart from this, Netronome (US), Cadence Design Systems, Inc. (US), and Synopsys, Inc. (US), SiFive, Inc. (US), ALPHAWAVE SEMI (UK), Eliyan (US), Ayar Labs, Inc. (US), Tachyum (US), X-Celeprint (Ireland), Kandou Bus SA (Switzerland), NHanced Semiconductors (US), Tenstorrent (Canada), Chipuller (China) and Rain Neuromorphics (US)

The US has earmarked $3 billion in funding it hopes will drive US leadership in advanced packaging technologies, seen as a key part of the future semiconductor industry.

Europe’s leading supercomputer will use a new quad Grace Hopper node with the GH200 combined ARM GPU when it is installed next year.

Since the ‘AI made in Europe’ strategy launched in February 2020, the US has pulled further ahead. The EU’s problem is a lack of scale and focus. The answer is to adopt CERN’s approach to running large, coordinated and highly ambitious projects

The artificial intelligence (AI) industry could consume as much energy as a country the size of the Netherlands by 2027, a new study warns.

This surge in computational strength is not just for bragging rights. Chinese government recognizes the crucial role of advanced computing in various sectors, notably in finance and the educational realms.

Traditional cloud infrastructure wasn’t designed to support large-scale artificial intelligence. Hyperscalers are quickly working to rebuild it.

Many companies say the cloud is their go-to when it comes to training and running large AI applications—but today, only a small portion of existing cloud infrastructure is actually set up to support that. The rest is not.

As the demand for data booms, hyperscaling explodes in conjunction with that demand. Here are the Top 10 data centre hyperscalers across the planet.

Data centres are the backbone of the digital economy, providing the infrastructure necessary to store, process and transmit vast amounts of data. Hyperscale data centres are massive facilities built by companies with vast data processing and storage needs.

Generative AI is poised to unleash the next wave of productivity. We take a first look at where business value could accrue and the potential impacts on the workforce.

KEY HIGHLIGHTS/ TRENDS. Shift Towards Sustainable Measures to Reduce Carbon Emissions. The increasing data center power consumption and the need to decrease carbon emissions have prompted many service providers to purchase clean, renewable energy sources to power their current and new facilities.

After a flurry of new competitors in 2022 at the top of the TOP500 list of the world’s most powerful supercomputers, the first list of 2023 – issued here in Hamburg this morning at the ISC conference – reveals the same top 10 systems in the same order.

Rapidly expanding data needs accelerate growth and drive investor interest, even as headwinds persist

The need for data centres is growing but powering these is a challenge of economy. How are data centres finding energy efficiencies and cutting costs?