A 23-year-old ex-OpenAI researcher just raised $1.5B predicting AGI by 2027—with zero investment experience. History shows fever dreams burn billions while real breakthroughs start small. Are we watching the next Amazon or the next Theranos?
Albania just appointed the world's first AI government minister to handle all public procurement. Diella promises corruption-free contracts as the country races toward EU membership by 2027. But can algorithms resist human manipulation?
Good Morning from San Francisco, Microsoft and OpenAI just signed a truce. After months of heated negotiations that nearly triggered
The rapid expansion of artificial intelligence is creating an unexpected casualty: public health. A study found that data centers caused $5.4 billion in health-related costs between 2019 and 2023.
These facilities consume massive amounts of electricity. Most run on fossil fuels, releasing pollutants that cause cancer, asthma, and breathing problems. The worst part? They're usually built in poorer neighborhoods where land is cheap and complaints are fewer.
Google leads the pack in health-related costs, with its facilities accounting for $2.6 billion of the total. Microsoft follows at $1.6 billion, while Meta's operations have generated $1.2 billion in health expenses. The EPA built a model that turns air pollution into dollar signs—and the numbers aren't pretty.
It's getting worse fast. Health costs hit $1.5 billion in 2023 alone—up 20% from 2022. That timing isn't coincidental. AI companies are racing to build bigger, hungrier models that need more computing muscle.
California sees what's happening. State lawmakers want data centers to report their energy use and hit efficiency targets. They're dangling tax breaks for companies that switch to clean power. Goal: stop electricity costs from crushing regular customers.
Tech companies aren't just sitting there. Meta teamed up with Entergy on carbon capture in Louisiana to offset emissions from new gas-powered centers. Exxon thinks data centers could grab 20% of the carbon capture market by 2050. But nobody knows if these fixes actually work at scale or cost too much.
The challenge extends beyond mere numbers. As AI becomes central to daily life, demand for data center capacity grows exponentially. Companies face mounting pressure to balance technological progress with environmental responsibility.
Why this matters:
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Large U.S. companies just hit the brakes on AI—adoption fell from 14% to 12% in two months, the first decline since tracking began. MIT research explains why: 95% of enterprise pilots deliver zero ROI. The gap between AI hype and workflow reality is widening.
Students embrace AI faster than schools can write rules. While 85% use AI for coursework, institutions stall on policy—and tech giants step in with billions in training programs to fill the vacuum. The question: who gets to define learning standards?
First survey of 283 AI benchmarks exposes systematic flaws undermining evaluation: data contamination inflating scores, cultural biases creating unfair assessments, missing process evaluation. The measurement crisis threatens deployment decisions.
Tech giants spent billions upgrading Siri, Alexa, and Google Assistant with AI. Americans still use them for weather checks and timers—exactly like 2018. Fresh YouGov data reveals why the utility gap persists.
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