It’s no secret that the growth of generative AI has demanded ever increasing amounts of water and electricity, but a new study from The Washington Post and researchers from University of California, Riverside shows just how many resources OpenAI’s chatbot needs in order to perform even its most basic functions.
In terms of water usage, the amount needed for ChatGPT to write a 100-word email depends on the state and the user’s proximity to OpenAI’s nearest data center. The less prevalent water is in a given region, and the less expensive electricity is, the more likely the data center is to rely on electrically powered air conditioning units instead. In Texas, for example, the chatbot only consumes an estimated 235 milliliters needed to generate one 100-word email. That same email drafted in Washington, on the other hand, would require 1,408 milliliters (nearly a liter and a half) per email.
Data centers have grown larger and more densely packed with the rise of generative AI technology, to the point that air-based cooling systems struggle to keep up. This is why many AI data centers have switched over to liquid-cooling schemes that pump huge amounts of water past the server stacks, to draw off thermal energy, and then out to a cooling tower where the collected heat dissipates.
ChatGPT’s electrical requirements are nothing to sneeze at either. According to The Washington Post, using ChatGPT to write that 100-word email draws enough current to operate more than a dozen LED lightbulbs for an hour. If even one-tenth of Americans used ChatGPT to write that email once a week for a year, the process would use the same amount of power that every single Washington, D.C., household does in 20 days. D.C. is home to roughly 670,000 people.
This is not an issue that will be resolved any time soon, and will likely get much worse before it gets better. Meta, for example, needed 22 million liters of water to train its latest Llama 3.1 models. Google’s data centers in The Dalles, Oregon, were found to consume nearly a quarter of all the water available in the town, according to court records, while xAI’s new Memphis supercluster is already demanding 150MW of electricity — enough to power as many as 30,000 homes — from the the local utility, Memphis Light, Gas and Water.
Acer’s Predator Atlas 8 finally has a US release date and price, several months after the company first showed off the handheld in May. The highlight is the Intel Arc G3 Extreme chip inside, which has been adopted by only a couple of other consoles besides the Atlas 8. This version will go on sale exclusively at Best Buy on November 1 for $1,299.99.
Acer originally said the Atlas 8 would arrive in North America in October, but left pricing open at the time. The launch came amid the ongoing DRAM crunch, which has made memory more expensive across the PC industry and complicated pricing for hardware makers.
Google DeepMind's AI world model Genie 4 can now build interactive worlds that you can explore and reshape as they run. It also generates ambient sounds, music, and dialogue that respond to your actions.
The new world model builds on Genie 3 with improved realism, more natural human movement, and better simulations of real-world physics. It could eventually help with everything from game development to training robots.
Apple has an incredible talent for making me admire its products while simultaneously questioning what on earth it's thinking with the pricing. This isn't even something as bizarre as a monitor stand, but the audacity for starting a new laptop lineup from $2,000 doesn't surprise me.
The newly announced 14-inch MacBook Pro with M6 is just the latest to showcase this. The funny thing is, I already know that it's going to be a reliable workstation. You get a powerful new 2nm M6 processor, a gorgeous Liquid Retina XDR display, and up to 24 hours of battery life. We were impressed by the M5 MacBook Air, so the high-end M6 powered MacBook Pro definitely won't let us down.