🧠AI Is Rotting Everyone’s Brain, and We’re Just Getting StartedPlus: 🧠AI Is Rotting Everyone’s Brain, and We’re Just Getting Started
📰 AI News and Trends
The AI Energy Crisis - The Problem and Possible Solutions
Data centers consume 6% of UK/US electricity, 3x the global average, and AI is the culprit. In just two years, AI has driven global data center energy consumption up 15%. The International Data Centre Authority warns that community backlash becomes “significant” once a country’s data centre footprint hits 5% of national grid consumption. The UK and US have already crossed that threshold. But the hidden scandal is that 13% of US datacenters’ power is “zombie services”, unused apps still running in the background, wasting 3+ GW annually. That’s electricity equivalent to powering millions of homes, consumed by code nobody remembered to shut down. This means higher energy bills for regular people, strain on water supplies, and a new justification for keeping fossil fuel plants online. Solutions exist and are scaling fast. Liquid cooling technology can allegedly reduce data centre energy use by 40% and water consumption by up to 96% compared to traditional air cooling. The technology works by circulating dielectric coolant directly over the hottest components, removing nearly all the heat instead of letting it dissipate wastefully. On the software side, companies are helping organizations eliminate “zombie” cloud resources, idle instances, orphaned storage, and forgotten load balancers that continue consuming costs without delivering any value. Studies suggest that up to 30% of enterprise cloud spending is wasted this way, and cleanup efforts generate significant returns. The scale of the problem means the infrastructure gets built anyway, but now the choice is either old air-cooled systems that waste energy or new liquid-cooled systems that don’t. Either way, the AI boom is coming. The question is whether we build it sustainably. 📚Learning CornerAI Is Rotting Everyone’s Brain, and We’re Just Getting Started
Developers report that using AI to write code is making them dumber. They produce working output but can’t understand how it works or fix what breaks. Research shows developers who fully delegate to AI perform 17% worse on conceptual tasks afterward. Scale that across billions of knowledge workers, add teenagers using TikTok and AI simultaneously, and you’re looking at a structural collapse in human cognition nobody planned for. Human attention span has collapsed from 12 seconds in 2000 to 7.6 seconds in 2026, a 36% erosion in 26 years. Children with 4+ hours of daily screen time show 34% steeper attention declines. The deeper problem is that when children encounter coding, writing, or problem-solving for the first time while delegating to AI, they never develop the neural pathways to understand it. There’s no muscle to atrophy because the muscle was never built. Meanwhile, AI models themselves degrade from exposure to low-quality viral social media, creating a feedback loop where both humans and AI are fed the same junk. Tech executives brag about AI writing 75% of Google’s code and 95% of Microsoft’s by 2030, but these gains translate into mass layoffs, not better products or shorter work weeks. Some guardrails are emerging, human-in-the-loop approaches, screen time limits, and refusing core thinking tasks to AI. But they’re not solutions; they’re just guardrails. By most metrics, AI will rot everyone’s brains. Are we going to notice in time to build systems or institutions that protect human cognitive development, or will we optimize for productivity until we wake up having outsourced the thinking itself? 🧰 AI Tools of The Day4 Tools to avoid Brain Rot
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