Luddite Studies

Luddite Studies To promote discussion and awareness of Luddite History and Politics.

https://www.reuters.com/business/energy/big-tech-data-centers-are-driving-up-power-bills-americas-rust-belt-factories-20...
08/07/2026

https://www.reuters.com/business/energy/big-tech-data-centers-are-driving-up-power-bills-americas-rust-belt-factories-2026-07-07/?utm_source=Facebook&utm_medium=Social&fbclid=IwY2xjawS66bNleHRuA2FlbQIxMQBzcnRjBmFwcF9pZBAyMjIwMzkxNzg4MjAwODkyAAEeWPCMsAdxYN4Yx7pEy-vFmYO3Rg0JePYkfZ6LHzZxtvpy-Jy_24W7rzaIisI_aem_P5ejAADDhB6GsqPY0rx9Tg

For years, electricity costs for the Belden Brick Company in Sugarcreek, Ohio, had been relatively stable. Last year, they surged by 90% — largely because of rising power demand from data centers in the region.

THE BEST WAY TO DESTROY AI...ACCORDING TO AI  (AND NON OF IT INVOLVES HAMMERS):   Destroying or effectively neutralizing...
26/04/2026

THE BEST WAY TO DESTROY AI...ACCORDING TO AI (AND NON OF IT INVOLVES HAMMERS):
Destroying or effectively neutralizing artificial intelligence can be approached through physical, digital, and regulatory methods, depending on whether the goal is to stop an individual system or the technology as a whole.
Physical and Resource Neutralization
Cutting Power and Cooling: Large-scale AI systems require massive amounts of electricity and complex cooling infrastructure to function. Disrupting the electrical grid or local power supply is the most immediate way to "kill" an active system.
Hardware Destruction: Destroying the physical servers, GPUs, and TPUs where the models are hosted and trained effectively terminates the AI. This includes using targeted Electromagnetic Pulses (EMPs) to fry delicate electronic circuits without physically destroying the building.
Limiting Compute Access: Preventing the acquisition of specialized chips (like those from NVIDIA) can stall the development of more advanced AI models.
Digital and Technical Sabotage
Data Poisoning: You can "break" an AI's accuracy by feeding it corrupted, biased, or highly non-linear data that it cannot generalize from. Introducing "poisoned" datasets during training can create hidden backdoors or cause the model to fail in specific scenarios.
Adversarial Attacks: Using inputs specifically designed to confuse neural networks (e.g., adding invisible noise to images or slightly rotating objects) can cause high-performance systems to make catastrophic errors.
Targeting Learning Algorithms: A digital "scorched earth" campaign can involve hacking into systems to find and delete the core learning algorithms or the weights of a trained model, effectively wiping its "knowledge".
Policy and Human Resistance
Regulatory Bans: Governments can implement strict laws to ban AI research in specific fields, limit funding, or require "kill switches" for all deployed models.
Digital Boycotting: Users can move away from AI-heavy platforms to authentic, human-created content and deliberately use non-AI tools (e.g., using physical notebooks or search engines that do not use generative AI).
Disabling Software Features: Most consumer AI can be turned off via system settings. For example, disabling "Smart Features" in Google Workspace or turning off Microsoft Copilot in Windows.

AMERICAN STUDENTS' LUDDITE CLUB REJECTS AI IMPOSITION IN COLLEGE.
04/04/2026

AMERICAN STUDENTS' LUDDITE CLUB REJECTS AI IMPOSITION IN COLLEGE.

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