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Micron breaks ground on 9 billion western Japan plant expansion

The Japan Times

Micron Technology on Saturday broke ground on the expansion of its factory in western Japan, a ¥1.5 trillion ($9.3 billion) undertaking to produce advanced memory chips. The Boise, Idaho-based company is building the facility in Hiroshima to make chips such as high-bandwidth memory crucial for AI processors like Nvidia's, with shipments to start around the summer of 2028. Japan's Ministry of Economy, Trade and Industry has allocated up to ¥500 billion to help cover the cost. The move is part of a global rampup by the U.S. company to meet demand for AI. Micron is building two leading-edge fabs in Boise and in January held a groundbreaking ceremony for a $100 billion production site outside Syracuse, New York, part of a pledge to increase DRAM production on American soil. "Micron's very first HBM production wafer -- for the memory technology at the heart of AI -- was made right here in Hiroshima," Micron CEO Sanjay Mehrotra said during a ceremony attended by central and local government officials.


What could new rights for unmarried couples mean for your money?

BBC News

What could new rights for unmarried couples mean for your money? When Amelia's fiance died suddenly in his 20s, just months before their wedding, she never imagined the legal and financial turmoil that would follow. I lost him, she says, and then I lost everything we'd ever built together. The couple had been together more than seven years and shared a business. But they were not married and Simon did not have a will, so his mother and father inherited all of his assets - apart from the couple's house - and Amelia was unable to stop them.


America's Time Capsule will be buried for 250 years. Here's how to watch.

Popular Science

Science America's Time Capsule will be buried for 250 years. The high-tech historical repository will be buried in Philadelphia on July Fourth. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Breakthroughs, discoveries, and DIY tips sent six days a week. By signing up, you confirm you are 16+, will receive newsletters and promotional content and agree to our Terms of Use and acknowledge the data practices in our Privacy Policy .


A Twist in This Year's Strangest Literary AI Scandal

The Atlantic - Technology

Jamir Nazir, the controversial winner of the Commonwealth award, tells his side of the story. Jamir Nazir has become the face of the AI-writing crisis. In May, the largely unknown 62-year-old Trinidadian writer was named a regional winner of the prestigious Commonwealth Prize for his short story " The Serpent in the Grove " But after it was published in the literary magazine, signs began to emerge that the story--about a cocoa farmer who cheated on his wife, and then tried to kill her--may have been AI-generated. Inscrutable lines plucked from Nazir's dense prose were mocked and memed. A young woman in the story "had the kind of walking that made benches become men."


Kioxia ships samples of new flash memory for AI data centers

The Japan Times

Hiroo Ota (center left), CEO of Kioxia Holdings, and others unveil Kioxia's new 3D flash memory chip at its Kitakami plant in Kitakami, Iwate Prefecture, on Friday. Kioxia Holdings has started shipping samples of its next-generation flash memory chips to artificial-intelligence data center operators, seeking to gain ground in the lucrative business against rivals. The Tokyo-based chipmaker's latest high-density 3D flash memory chips aim to better meet AI data center needs with better efficiency and transmission speeds. The 332-layer 10th-generation chips pack more data into silicon and can store 59% more data compared with its previous flagship 8th-generation chip, the company said Friday. Production will take place at the company's second manufacturing facility at its Kitakami plant in Iwate Prefecture, which began operating in September last year.


Australia news live: shadow arts minister Angie Bell, a former musician, says AI giants must pay for content

The Guardian

Follow the day's latest updates Court approves $23.5m fine and costs order against ASX Shadow arts minister says AI companies need to do what everyone else does: 'ask permission and pay for it' Albanese defends gambling reforms, says he's'not against someone having a punt' Pocock says it's'tragic' gambling reforms don't go nearly far enough Shadow arts minister says AI companies need to do what everyone else does: 'ask permission and pay for it' If AI companies want to use Australian creative work, they should do what everyone else does: ask permission and pay for it. Australian creativity is one of our greatest national assets - not a free resource for multinational tech companies. The Coalition will always back the right of artists to control their work and be fairly compensated when others profit from it. This is about consent, fairness and respect for Australian creativity. Court approves $23.5m fine and costs order against ASX Shadow arts minister says AI companies need to do what everyone else does: 'ask permission and pay for it' Albanese defends gambling reforms, says he's'not against someone having a punt' Pocock says it's'tragic' gambling reforms don't go nearly far enough Court approves $23.5m fine and costs order against ASX A federal court judge has ordered the ASX operator to pay $23.5m in penalties and costs after the company admitted to making a misleading statement about a troubled upgrade for technology required to run the stock exchange.


OpenAI proposes handing U.S. government a 5% stake, report says

The Japan Times

OpenAI proposes handing U.S. government a 5% stake, report says OpenAI has discussed giving the U.S. government a 5% stake as artificial intelligence firms face scrutiny in Washington. OpenAI has discussed giving the U.S. government a 5% stake, the Financial Times reported on Thursday, as artificial intelligence firms face scrutiny in Washington over the likely misuse of advanced models and whether Americans would benefit from the industry's massive valuations. The ChatGPT creator has proposed that other U.S. AI firms also give Washington similar stakes, although it is unclear whether they would agree, the report said, citing two people familiar with the talks. The move follows growing public backlash in the U.S. over AI's potential to cause economic upheaval, including layoffs, and could help OpenAI sweeten ties with an administration that is increasingly taking an active role in regulating the technology. In a time of both misinformation and too much information, quality journalism is more crucial than ever.


'Milestone': Scientists claim to build synthetic cell, raising concerns in step toward artificial life

FOX News

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Learning Effective Soliton Dynamics from Scattering Data

arXiv.org Machine Learning

In such settings, the inverse scattering transform (IST) of Ablowitz, Kaup, Newell, and Segur [2] has enjoyed a rich and successful history, and is now the standard theoretical framework for deriving reduced-order evolution equations for soliton dynamics. Although these derivations are traditionally of an analytical - rather than data-driven - nature, recent work has employed the IST formalism as a tool for experimental data analysis, using the technique to analyze soliton content from empirical measurements [8, 15, 24]. Moreover, recent approaches using alternative parameterization techniques have demonstrated that the learning of reduced-order, interpretable equations of motion for solitons is tenable in a data-driven setting [6, 26, 27]. Despite the success of this recent work, however, little effort has been devoted to developing a data-driven modeling approach based on the IST itself, most likely due to the fact that the framework is fundamentally problem-specific. In this paper, we address the question of whether effective soliton dynamics can be inferred directly from observed scattering data (as opposed to being derived or approximated analytically).


Conditional Inference Trees and Forests for Feature Selection

arXiv.org Machine Learning

Conditional inference trees (CIT) and conditional inference forests (CIF) reduce split-selection bias by testing features before choosing split thresholds, but repeated permutation tests and threshold searches can make these methods computationally expensive. We study CIT and CIF as top-$k$ feature-ranking methods for downstream prediction using real-data benchmarks, runtime ablations, and synthetic feature-recovery experiments. At a fixed node, if the features and permutation budget do not depend on the node responses, Bonferroni-corrected $+1$ Monte Carlo permutation $p$-values control nodewise rejection under the complete permutation null. CIF ranks 4th among 17 classification methods on 22 datasets and 3rd among 18 regression methods on 8 datasets. With Bonferroni correction held fixed, the CIF runtime ablations indicate that adaptive stopping and the number of thresholds searched have the largest measured effect on runtime: turning off adaptive stopping and using exact threshold search increase fitting time by 4.0--8.4$\times$ and 1.9--10.8$\times$, respectively, while downstream score changes are at most 0.011. Sparse high-$p$ simulations indicate that forest feature sampling can leave informative features out of many split decisions. Overall, the results support CIF as a top-$k$ feature-ranking method in the evaluated downstream prediction benchmarks.