TL;DR Put the entire population in KN95s and this is all over in 3 months, Omicron or no Omicron. pnas.org/content/118/49/e211…

The world just built a machine that drinks clean water like a river. And nobody is talking about what that actually means. 🚨 🚨 🚨 AI DATA CENTERS WILL CONSUME ENOUGH CLEAN WATER TO SUPPLY 1.3 BILLION PEOPLE BY 2030 — PER A UNITED NATIONS REPORT 🚨 🚨 🚨 A United Nations report just put a number on it. Not a vague warning. Not a projection buried in a footnote. A hard figure: AI data centers will consume enough freshwater to supply 1.3 billion people annually by 2030. That is not a typo. One sector. One cooling system. 1.3 BILLION people's worth of water. THE WEAPON: → Global data center water consumption: 560 billion liters per year right now → Projected consumption by 2030: 1,200 billion liters (IEA) → US AI data centers alone: 17 billion gallons consumed in 2023 → US projection by 2028: 38–73 billion gallons annually → Single large facility withdrawal: up to 5 million gallons per day — the daily need of a city of 50,000 people → Evaporative cooling rate: ~80% of withdrawn water evaporates and is NEVER returned → Per-query footprint: every 100-word AI prompt consumes roughly one 16.9 oz bottle of water → Indirect footprint: electricity generation adds another 60% on top of direct consumption THE TARGET: → Phoenix region alone: data center water use projected to rise 870% — from 385 million to 3.7 billion gallons per year → Google's Council Bluffs facility: 3.9 million gallons withdrawn daily, on average → Hyperscale facilities expected to account for half of all future US AI water consumption THE MATH: → 2021 US data center baseline: 163.7 billion gallons annually → Five years of AI acceleration later: 300% growth for key operators → By 2030: one sector's cooling needs rival or exceed the municipal water supply of entire countries → 1.3 billion people. That is the population of Africa. That is more than the entire Western Hemisphere. Read that again. 💀 There are currently 2 billion people on Earth without reliable access to clean water 💀 AI infrastructure is being built fastest in water-stressed regions — Phoenix, the American Southwest, the Middle East 💀 Once evaporated, that water does not come back — it is not recycled, it is not returned to the aquifer, it is gone ⚠️ The world is already withdrawing freshwater faster than it is being replenished ⚠️ Agriculture uses 70–80% of global freshwater — AI is now the fastest-growing new competitor for what remains ⚠️ This is not a future problem. 560 billion liters are being consumed right now, today, this year. They're showing you the AI boom. They're NOT showing you what is being drained to power it — the aquifers that took thousands of years to fill, the rivers already running low, the municipal systems already competing with server farms for the same water table. You don't build a machine that evaporates 80% of everything it drinks in a water-stressed world and call it progress. You don't scale that machine by 300% in five years and assume the water will keep showing up. You do that when you have decided, consciously or not, that the output is worth more than the resource that keeps 8 billion people alive. I'll keep you updated. Turn on notifications. 🚨

Two economists just published a mathematical proof that AI will destroy the economy. Not might. Not could. Will — if nothing changes. The paper is called "The AI Layoff Trap." Published March 2, 2026. Wharton School, University of Pennsylvania. Boston University. Peer reviewed. Mathematically modeled. The conclusion is one sentence. "At the limit, firms automate their way to boundless productivity and zero demand." An economy that produces everything. And sells it to nobody. Here is how you get there. A company fires 500 workers and replaces them with AI. A competitor fires 700 to keep up. Another fires 1,000. Every company is behaving rationally. Every company is following the incentives correctly. And every company is building a trap for itself. Because the workers who were fired were also customers. When they lose their jobs faster than the economy can absorb them, they stop spending. Consumer demand falls. Companies respond by cutting costs — which means automating more workers — which means less spending — which means more falling demand — which means more automation. The loop has no natural exit. The researchers tested every proposed solution. Universal basic income. Capital income taxes. Worker equity participation. Upskilling programs. Corporate coordination agreements. Every single one failed in the model. The only intervention that worked: a Pigouvian automation tax — a per-task levy charged every time a company replaces a human with AI, forcing them to price in the demand they are destroying before they pull the trigger. No government has implemented this. No major economy is seriously discussing it. Meanwhile the numbers are already tracking the curve. 100,000 tech workers laid off in 2025. 92,000 more in the first months of 2026. Jack Dorsey fired half of Block's workforce and said publicly: "Within the next year, the majority of companies will reach the same conclusion." Nobody is doing anything wrong. Companies are following their incentives perfectly. That is exactly the problem. Rational behavior. At scale. Simultaneously. With no mechanism to stop it. Two economists built the math. The math leads to one place. Source: Falk & Tsoukalas · Wharton School Boston University ·

The West Has Already Lost the Drone War. It Just Hasn’t Noticed Yet. Here is something that should ruin your Monday. A Ukrainian AI drone engineer has gone on record to explain, calmly and with considerable evidence, that Western military planning is not behind the times. It is not lagging. It is not in need of reform. It is dead. Obsolete. A relic propped up by expensive acronyms and men in uniforms who still think the tank is the apex predator of land warfare. Yaroslav Azhnyuk, founder of AI drone company The Fourth Law, has done the maths. FPV drones now account for somewhere between 70 and 80 percent of frontline casualties in Ukraine. Not artillery. Not missiles. Not the armoured columns that NATO has spent forty years and several fortunes preparing to counter. Small, cheap, autonomous flying machines that cost about as much as a decent restaurant dinner and kill with the precision of a surgeon. But here is where it gets genuinely terrifying. China can produce four billion FPV drones per year. Ukraine, a country that has been at war for three years and is building faster than anyone in the West, manages four million. That is the kind of number that makes you want to lie down on the floor and stare at the ceiling for a while. The West is not losing the AI arms race because it lacks the technology. It is losing because it is still arguing about procurement frameworks while the future arrives, uninvited, at four hundred kilometres per hour with a shaped charge attached. Latest 👇 gandalv.substack.com/p/ukrai…

He used to fix pipes. Now he reads the Russian army’s mind. Meet the Ukrainian plumber who became an intelligence analyst. Callsign “Lys” — “Fox” — is a plumber and gas welder by trade. Today he sits in a small room near Ukraine’s front line and listens to Russian radio traffic. He hears Russian assault troops asking their commanders for water and being told to crawl forward instead. He hears wounded Russian soldiers being abandoned by their own. He predicts Russian assaults before they begin — by listening to the silence between the words. He works alongside commander “Shonni,” whose unit has suppressed nearly 11,800 Russian drones in a single year with mostly homemade equipment. ArmyInform spent time with them. This is what the radio war actually sounds like. 🧵

A massive new hyperscale data center project called Stratos is planned for Box Elder County, Utah. If built, it would demand up to 9 gigawatts of electricity, more than twice the total power consumption of the entire state. But the real shock comes from the waste heat. According to Utah State University physics professor Robert Davies, the facility would generate an additional 7 to 8 gigawatts of heat, creating a total thermal output of roughly 16 gigawatts concentrated in one location. That energy release, Davies calculated, is comparable to detonating 23 atomic bombs per day in Hansel Valley, a high desert basin near the shrinking Great Salt Lake that naturally traps heat like a bowl. The project’s energy footprint would also be roughly equal to that of 40,000 Walmart Supercenters. Local temperatures could rise by about 5°F (2.8°C) during the day and a staggering 28°F (15.6°C) at night. Ecologists warn that such dramatic warming would stress an already fragile ecosystem, worsen toxic dust from the drying lakebed, and disrupt plants, wildlife, and water resources. As the backbone of artificial intelligence, data centers are essential for every AI query, image, and training run. The Stratos project now raises a critical question: Can the massive infrastructure behind AI expand without permanently transforming, and overheating, the communities and landscapes where it’s built? ["‘So much worse than I even thought’: Utah’s ‘hyperscale’ data center could create massive heat island near Great Salt Lake." The Salt Lake Tribune]

Study: Presence and Persistence of Andes Virus RNA in Human Semen "We demonstrate that the ANDV genome persists within the reproductive tract for at least 71 months.... Taken together, our results show that ANDV has the potential for sexual transmission. PMC pmc.ncbi.nlm.nih.gov/article…

A study suggests that many older adults who died of COVID-19 weren’t close to death before infection. In fact, 28% would likely have lived at least another 5 years if they hadn't contracted the virus. Read more: ow.ly/j4V150YXREy

Just published: @WHO Technical note for the management of contacts of Andes virus (ANDV) cases from the MV Hondius cruise ship. who.int/publications/m/item/…

Colorado just told 1.5 million people they can't water their lawns. The state is still green-lighting AI data centers that each drink as much water as a town of 50,000 people. Reservoirs at historic lows. One Colorado Springs utility has 95,000 acre-feet of total water access. Ten data centers are in line asking for up to 117,000. If every project gets approved, the utility has to more than double its entire water supply. None of those data centers exist yet. The inquiries already exceed what the system holds. On March 16, Governor Polis activated Phase 2 of the state's Drought Response Plan. First time in nearly six years. Nine days later, Denver Water declared Stage 1 drought and put mandatory watering restrictions on 1.5 million customers. First time since 2013. Federal managers ranked this year's snowpack 45th out of 46 years on record. Two days before the Denver Water vote, the only bill that would have required data centers to publicly report water use died in a Colorado Senate committee. The state has 56 small data centers today. QTS Realty Trust is building Colorado's first hyperscale east of Denver. It qualified to build in Aurora because city code now prohibits new evaporative cooling. Denver has no equivalent rule. A single hyperscale pulls as much water as a town of 50,000 people for cooling. The power plants behind it pull more. On-site water use across five Western states is projected at 21,600 acre-feet by 2035. Counting upstream electricity generation, it climbs to 89,700. Xcel projects Colorado data centers will need 8.5 gigawatts by 2040. Roughly another Denver metro's worth of power. Global AI bought 400 acres near Windsor for a campus targeting 1,000 megawatts. Colorado's alfalfa farms used 394 billion gallons last year. The water budget was already overdrawn before the cooling towers came online. Disclosure was the floor. The bill still died.

Most of what we know about how the #AndesHantavirus transmits comes from a NEJM study of an outbreak in Argentina in 2018-19. Here’s an interview I produced with the study’s senior scientist: cbc.ca/9.7192895 People can be infectious for 48 hrs before symptom onset. #WHO

They’ve known the whole time.