An anonymous reader quotes a report from Ars Technica: The US crackdown on chip exports to China has continued with the arrests of four people accused of a conspiracy to illegally export Nvidia chips. Two US citizens and two nationals of the People's Republic of China (PRC), all of whom live in the US, were charged in an indictment (PDF) unsealed on Wednesday in US District Court for the Middle District of Florida. The indictment alleges a scheme to send Nvidia "GPUs to China by falsifying paperwork, creating fake contracts, and misleading US authorities," John Eisenberg, assistant attorney general for the Justice Department's National Security Division, said in a press release yesterday.

The four arrestees are Hon Ning Ho (aka Mathew Ho), a US citizen who was born in Hong Kong and lives in Tampa, Florida; Brian Curtis Raymond, a US citizen who lives in Huntsville, Alabama; Cham Li (aka Tony Li), a PRC national who lives in San Leandro, California; and Jing Chen (aka Harry Chen), a PRC national who lives in Tampa on an F-1 non-immigrant student visa. The suspects face a raft of charges for conspiracy to violate the Export Control Reform Act of 2018, smuggling, and money laundering. They could serve many decades in prison if convicted and given the maximum sentences and forfeit their financial gains. The indictment says that Chinese companies paid the conspirators nearly $3.9 million. One of the suspects was briefly the CTO of Corvex, a Virginia-based AI cloud computing company that is planning to go public. Corvex told CNBC yesterday that it "had no part in the activities cited in the Department of Justice's indictment," and that "the person in question is not an employee of Corvex. Previously a consultant to the company, he was transitioning into an employee role but that offer has been rescinded."

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Google's AI infrastructure chief told employees the company must double its AI serving capacity every six months in order to meet demand. In a presentation earlier this month, Amin Vahdat, a vice president at Google Cloud, gave a presentation titled "AI Infrastructure." It included a slide on "AI compute demand" that said: "Now we must double every 6 months.... the next 1000x in 4-5 years." CNBC reports: The presentation was delivered a week after Alphabet reported better-than-expected third-quarter results and raised its capital expenditures forecast for the second time this year, to a range of $91 billion to $93 billion, followed by a "significant increase" in 2026. Hyperscaler peers Microsoft, Amazon and Meta also boosted their capex guidance, and the four companies now expect to collectively spend more than $380 billion this year.

Google's "job is of course to build this infrastructure but it's not to outspend the competition, necessarily," Vahdat said. "We're going to spend a lot," he said, adding that the real goal is to provide infrastructure that is far "more reliable, more performant and more scalable than what's available anywhere else." In addition to infrastructure build-outs, Vahdat said Google bolsters capacity with more efficient models and through its custom silicon. Last week, Google announced the public launch of its seventh generation Tensor Processing Unit called Ironwood, which the company says is nearly 30 times more power efficient than its first Cloud TPU from 2018.

Vahdat said the company has a big advantage with DeepMind, which has research on what AI models can look like in future years. Google needs to "be able to deliver 1,000 times more capability, compute, storage networking for essentially the same cost and increasingly, the same power, the same energy level," Vahdat said. "It won't be easy but through collaboration and co-design, we're going to get there."

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Stueyman has added a photo to the pool:

Diana Mini and some Fuji c400

Stueyman has added a photo to the pool:

St George’s Cathedral, Perth Wa

Stueyman has added a photo to the pool:

House being built on a bush block.

Photon Obsolescence has added a photo to the pool:

Tourism 101:
Bay of Fires- Binalong Bay,
Tasmania, Australia

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