Water usage has been a hot topic in the AI data center world, but the numbers may surprise you.
According to the Manhattan Institute, data centers use 0.2 percent of daily water usage in the U.S. and that number has dramatically decreased in the past few years due to a new method: liquid cooling.
By moving to 45°C liquid cooling, AI factories in favorable climates can use dry coolers instead of conventional cooling-tower-based systems, cutting facility cooling water use from roughly 2.6M gallons per MW per year to near zero.
Liquid cooling enables AI factories to be both water and energy efficient, while creating opportunities for heat reuse and dispersal to local communities, allowing these factories to become energy grid assets.
Learn more below ⬇️
https://t.co/7WanoPNKTR
More than 40 years ago, I arrived in Chicago in search of an idea. I was a young man looking for purpose, who believed deeply in America, was inspired by the Civil Rights Movement, and wanted to be a part of something larger. The America I believed in was one where everyone has opportunity, everyone is seen, everyone belongs—because that was an America that had a place for me, too.
The next generation of Apple Intelligence powers an entirely new Siri: making the apps and experiences you rely on across iPhone, iPad, Mac, and Apple Vision Pro more personal and helpful than ever.
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everyone’s asking how high AI can go.
nobody’s asking how low it’s allowed to fail.
hospitals. courts. the rooms where your name becomes a case number.
Thursday, Dr Anna Schrimpf & Nicolay Hagen (Varden) pull up. 👇
📅 14 May · 6pm BST
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✦ Team Spotlight: Dr @Yuktichopra1
Today, we are launching our new academic @Substack series, Sunday Reads from The Reading Room, with a piece by Dr Yukti Chopra
New Anthropic research: Natural Language Autoencoders.
Models like Claude talk in words but think in numbers. The numbers—called activations—encode Claude’s thoughts, but not in a language we can read.
Here, we train Claude to translate its activations into human-readable text.
New Anthropic research: Natural Language Autoencoders.
Models like Claude talk in words but think in numbers. The numbers—called activations—encode Claude’s thoughts, but not in a language we can read.
Here, we train Claude to translate its activations into human-readable text.