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Crypto Trends

Amazon to Spend $10 Billion on North Carolina Data Centers for AI Expansion

by admin June 5, 2025



In brief

  • Amazon is investing $10 billion in North Carolina to build data centers supporting AI infrastructure, creating at least 500 high-skilled jobs.
  • The company is also reportedly developing humanoid robots for delivery tasks, testing them in a new “humanoid park” at its San Francisco office.
  • An expert told Decrypt the scale of Amazon’s investment highlights how rising infrastructure costs risk putting AI innovation solely in the hands of Big Tech.

Amazon announced on Wednesday that it is committing $10 billion to build new data centers in North Carolina as part of its effort to expand artificial intelligence and cloud computing infrastructure.

The investment is expected to anchor new compute-intensive workloads and help scale Amazon’s capacity to support businesses building with AI, the company said in a statement.

“Amazon’s investment is among the largest in state history and will bring hundreds of good-paying jobs and an economic boost to Richmond County,” North Carolina Governor Josh Stein said.

The $10 billion investment is part of Amazon’s push to compete with other tech giants like Google, Microsoft, and Meta in building the infrastructure needed to support large-scale AI models.

The company said the funds “will support the future of AI from AWS data centers in the Tar Heel State,” creating at least 500 high-skilled jobs in the process.

As part of the new buildout, Amazon will fund technician training programs at community colleges, STEM education in K-12 schools, and career pathways in fiber broadband infrastructure. 

It also launched a $150,000 Richmond County Community Fund to support local projects in workforce development, sustainability, and public health.

“The expansion of AI infrastructure is positive news for the industry, but it highlights a key problem of this industry: cost,” Leo Fan, co-founder of blockchain-based AI infrastructure firm Cysic, told Decrypt. 

“An investment of $10 billion demonstrates the high cost of building, expanding, and maintaining AI infrastructure,” Fan said. “This prices out smaller-scale developers or companies that may not have the funds to access the infrastructure and hardware needed to provide the necessary computing power, disincentivising innovation.”

Fan said the investment brings economic benefits but warned it could lead to “the stronger concentration of all innovative AI work in the hands of Big Tech,” which he believes could stall broader innovation.

Amazon Builds ‘Humanoid Park’

The company is developing AI software for humanoid robots that could eventually handle delivery tasks, according to a report by The Information, citing an unnamed source. 

Amazon has reportedly built a “humanoid park,” an indoor obstacle course inside one of its San Francisco offices, where the robots will be tested. 

While the company hasn’t commented publicly, Amazon allegedly plans to use third-party hardware during early trials.

“Amazon’s move validates what the crypto-AI space has been building towards: permissionless intelligence backed by powerful infrastructure,” Abhay, founder and CEO of DappLooker AI told Decrypt.

Amazon’s AI ambitions have also extended into media, with the company finalizing a multi-year licensing deal last Thursday with The New York Times to bring its journalism, recipes, and sports content to Alexa and its proprietary AI models.

Edited by Sebastian Sinclair

Generally Intelligent Newsletter

A weekly AI journey narrated by Gen, a generative AI model.



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June 5, 2025 0 comments
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Shell DCL Fluid S3
Gaming Gear

Shell introduces DLC Fluid S3 as data centers turn to liquid cooling for efficiency and thermal performance gains

by admin June 4, 2025



  • Shell launches new cooling fluid to meet AI data center demands
  • DLC Fluid S3 cools high-performance components like CPUs and GPUs
  • The propylene glycol blend is formulated for safety and cooling effectiveness

Direct liquid cooling is gaining traction in data centers as traditional air-based systems struggle to manage the demands of modern computing.

Shell, one of the world’s largest oil and gas companies, has launched a new direct liquid cooling fluid aimed at meeting the thermal demands of AI and high-performance computing.

Shell DLC Fluid S3 is a propylene glycol-based solution designed to cool high-density server hardware by directly targeting heat-generating components such as CPUs and GPUs. It meets the latest Open Compute Project PG25 standards, making it compatible with a broad range of server architectures.


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Powering the future of digital infrastructure

Data centers currently account for an estimated 2–3% of global power consumption, but Shell claims its new fluid can improve Power Usage Effectiveness (PUE) by up to 27% compared to air cooling, potentially reducing the need for energy-intensive air conditioning.

The company also highlights the fluid’s extended service life, corrosion protection across a variety of metals, and fluorescent dye for easier leak detection.

“With Shell DLC Fluid S3, Shell now offers both direct-to-chip and full immersion cooling solutions, and we’re not just keeping data centers cool in the age of AI – we’re powering the future of digital infrastructure,” said Aysun Akik, VP New Business Development and Global Key Accounts, Shell Lubricants.

“Our growing range of advanced liquid cooling solutions is designed to meet the diverse needs of modern data centers both today, and tomorrow – and are backed by the strength of Shell’s global footprint, supply chain and five technology development hubs around the globe.”

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We previously covered how Castrol, a major name in motor lubricants, has also entered this space and is developing dielectric fluids for immersion cooling systems.

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June 4, 2025 0 comments
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Nord Quantique quantum computing
Gaming Gear

Quantum startup claims its 20-square-meter machine will crush HPC giants and rewrite the future of data centers forever

by admin June 2, 2025



  • Nord Quantique promises quantum power without the bulk or energy drain
  • Traditional HPC may fall if Nord’s speed and energy claims prove real
  • Cracking RSA-830 in an hour could transform cybersecurity forever

A quantum computing startup has announced plans to develop a utility-scale quantum computer with more than 1,000 logical qubits by 2031.

Nord Quantique has set an ambitious target which, if achieved, could signal a seismic shift in high-performance computing (HPC).

The company claims its machines are smaller and would offer far greater efficiency in both speed and energy consumption, thereby making traditional HPC systems obsolete.


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Advancing error correction through multimode encoding

Nord Quantique uses “multimode encoding” via a technique known as the Tesseract code, and this allows each physical cavity in the system to represent more than one quantum mode, effectively increasing redundancy and resilience without adding complexity or size.

“Multimode encoding allows us to build quantum computers with excellent error correction capabilities, but without the impediment of all those physical qubits,” explained Julien Camirand Lemyre, CEO of Nord Quantique.

“Beyond their smaller and more practical size, our machines will also consume a fraction of the energy, which makes them appealing for instance to HPC centers where energy costs are top of mind.”

Nord’s machines would occupy a mere 20 square meters, making them highly suitable for data center integration.

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Compared to 1,000–20,000 m² needed by competing platforms, this portability further strengthens its case.

“These smaller systems are also simpler to develop to utility-scale due to their size and lower requirements for cryogenics and control electronics,” the company added.

The implication here is significant: better error correction without scaling physical infrastructure, a central bottleneck in the quantum race.

In a technical demonstration, Nord’s system exhibited excellent stability over 32 error correction cycles with no measurable decay in quantum information.

“Their approach of encoding logical qubits in multimode Tesseract states is a very effective method of addressing error correction and I am impressed with these results,” said Yvonne Gao, Assistant Professor at the National University of Singapore.

“They are an important step forward on the industry’s journey toward utility-scale quantum computing.”

Such endorsements lend credibility, but independent validation and repeatability remain critical for long-term trust.

Nord Quantique claims its system could solve RSA-830, a representative cryptographic challenge, in just one hour using 120 kWh of energy at 1 MHz speed, slashing the energy need by 99%.

In contrast, traditional HPC systems would require approximately 280,000 kWh over nine days. Other quantum modalities, such as superconducting, photonic, cold atoms, and ion traps, fall short in either speed or efficiency.

For instance, cold atoms might consume only 20 kW, but solving the same problem would take six months.

That said, there remains a need for caution. Post-selection – used in Nord’s error correction demonstrations, required discarding 12.6% of data per round. While this helped show stability, it introduces questions about real-world consistency.

In quantum computing, the leap from laboratory breakthrough to practical deployment can be vast; thus, the claims on energy reduction and system miniaturization, though striking, need independent real-world verification.

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June 2, 2025 0 comments
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