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cloud computing
Trends
- 1Most data centers refusing to disclose water and electricity useโผMost data centers refusing to say how much water, electricity they use
A Dutch report finds most data centers are refusing to reveal how much water and electricity they consume, raising transparency concerns as AI and cloud computing drive rapid growth in energy demand. Critics say the secrecy makes it impossible for the public and regulators to assess the industry's environmental footprint, while operators typically cite commercial confidentiality.
- 2
Discussion is growing around the business economics of offering large language model inference as a cloud service. Commenters and industry observers are examining why serving AI models to users is so costly, how providers price access, and whether current pricing models are sustainable given the compute demands. The debate touches on GPU costs, margins, and competition among AI service providers.
- 3
Programmers are setting up small local servers, jokingly called 'AI sheds', to run AI coding tools on their own hardware instead of renting expensive cloud capacity. The trend follows a suggestion by Ruby creator David Heinemeier Hansson, who argued developers could save money and keep code private by hosting models at home. Responses have been mixed, with some praising the cost savings and others calling it impractical.
- 4Google's first orbital data center reaches orbitโGoogle's first orbital data center is in orbit https://lemire.me/blog/2026/10/04/googles-first-orbital-data-center-is-in
Google has reportedly placed its first orbital data center into orbit, marking a step toward computing infrastructure in space. The development was highlighted by computer scientist Daniel Lemire on his blog, filed under space and technology. Orbital data centers could offer solar-powered, always-illuminated computing, though questions remain about maintenance, cooling and radiation resilience.
- 5
Hobbyists and independent developers are sharing methods to make AI models run significantly faster on consumer-grade computers, without specialized data-center equipment. The discussion centers on optimization tricks such as quantization, caching and smarter memory use that let large language models run on ordinary laptops and desktops. Commenters are trading benchmarks and configuration tips, with many arguing that capable local AI no longer needs expensive hardware.
- 6Remembering the Cr-48, Google's forgotten first ChromebookโThe forgotten Chromebook that started it all Google didn't even call the first Chromebook a "Chromebook." The Cr-48 had
Google's first Chromebook, the Cr-48, was never sold in stores and did not even carry the Chromebook name. The unbranded, plain black laptop was sent to testers as a pilot device ahead of the 2011 Chromebook launch, serving as a proof of concept for Google's browser-based computing vision. Tech commentators are revisiting the device and its role in shaping Google's later cloud-first laptop lineup.
- 7Researchers Unveil Quasilinear Quantum Computation VerifierโResearchers Build Quasilinear Quantum Computation Verifier
Researchers have built a quasilinear verifier for quantum computations, a tool designed to check that quantum devices produce correct results without requiring exponentially large classical resources. Verification is one of the central unsolved problems in quantum computing, since users cannot directly confirm outputs of machines they cannot simulate. The development is being reported as a step toward trustworthy quantum cloud services and practical certification of quantum hardware.