They work 24/7 at high speeds and get searingly hot - but data centre computer chips get plenty of pampering. Some of them basically live at the spa. We'll have fluid that comes up and [then] shower down, or trickle down, onto a component, says Jonathan Ballon, chief executive at liquid cooling firm Iceotope. Some things will get sprayed. In other cases, the industrious gizmos recline in circulating baths of fluid, which ferries away the heat they generate, enabling them to function at very high speeds, known as overclocking.

Video game performers with SAG-AFTRA will strike beginning Friday as AI "loopholes" have caused concerns. Beginning at 12:01 Friday morning, video game voice actors and motion capture performers under the Screen Actors Guild-American Federation of Television and Radio Artists will strike over artificial intelligence protections. This is the second strike for SAG-AFTRA performers in video games. While the union has conceded that wages and job safety have made gains in video game contracts, AI in interactive media continues to be a source of insecurity. TENS OF THOUSANDS OF GAMERS DESCEND ON LAS VEGAS FOR THE EVO TOURNAMENT SAG-AFTRA Chief Contracts Officer Ray Rodriguez shared at the presser on Thursday that some performers' work may be treated as "data" under current AI guidance.

Actors in the video game industry are going on strike. On Thursday, the union representing voice and motion-capture performers announced they would be walking off the job after talks with major video game companies broke down over concerns over AI protections. The work stoppage is set to begin Friday. "We're not going to consent to a contract that allows companies to abuse AI to the detriment of our members," Fran Drescher, the president of the Screen Actors Guild-American Federation of Television and Radio Artists (SAG-AFTRA), which represents the performers, said in a prepared statement. When these companies get serious about offering an agreement our members can live--and work--with, we will be here, ready to negotiate." Several members of SAG-AFTRA are currently at Comic-Con International in San Diego for panels and other appearances. They will still be able to honor their obligations this weekend "given the close proximity" of the strike announcement to the event, which runs through Sunday. "Solidarity," Dragon Age: The Veilguard voice actor Erika Ishii posted on X. "We'll be fulfilling contracts at SDCC but afterwards we hold the line." Last year's Hollywood strikes greatly reduced the number of performers able to participate in Comic-Con events. Tensions over AI between SAG members and major video game companies have been high for months. Negotiations between the two sides began in earnest in October 2022. Members voted to authorize a strike in September of 2023. "Eighteen months of negotiations have shown us that our employers are not interested in fair, reasonable AI protections, but rather flagrant exploitation," Sarah Elmaleh, SAG's negotiating chair for the Interactive Media Agreement (IMA) that covers video game workers, said in a statement. "We refuse this paradigm--we will not leave any of our members behind, nor will we wait for sufficient protection any longer." In the video game industry, actors regularly lend their voice, likeness, and even movements to projects. Voice acting and motion-capture are a crucial part of game development, even as AI begins to change the way developers create their games. Despite success on other points, video game companies and SAG have been unable to find common ground on AI. "We are disappointed the union has chosen to walk away when we are so close to a deal, and we remain prepared to resume negotiations," Audrey Cooling, a spokesperson for the video game companies involved in the negotiations said in a statement to WIRED. That group includes companies such as Activision, Disney, Electronic Arts, Insomniac Games, Take-Two, and Warner Bros., among others. "We have already found common ground on 24 out of 25 proposals, including historic wage increases and additional safety provisions," Cooling said. "Our offer is directly responsive to SAG-AFTRA's concerns and extends meaningful AI protections that include requiring consent and fair compensation to all performers working under the IMA.

This year, Samsung is planning to open a semiconductor chip manufacturing plant in Taylor, TX, that will cost the company an estimated 17 billion. Intel is building a 20-billion facility in Columbus, OH, and industry leaders GlobalFoundries, TSMC, and Texas Instruments are building their own so-called chip fabs in the U.S. as well. This construction boom has been spurred in part by increasing demand for the smartphones, personal electronic devices, and Artificial Intelligence (AI) services that depend on chips, and the 50 billion in funding that the 2022 CHIPS and Science Act allocated to American semiconductor manufacturing has proven to be a strong incentive. Yet the boom is global, with new plants being developed all over the world. As companies plan these new chip fabs, one of the first questions they need to answer is where they are going to get their water.

Our study introduces a Generative AI method that employs a cooling-guided diffusion model to optimize the layout of battery cells, a crucial step for enhancing the cooling performance and efficiency of battery thermal management systems. Traditional design processes, which rely heavily on iterative optimization and extensive guesswork, are notoriously slow and inefficient, often leading to suboptimal solutions. In contrast, our innovative method uses a parametric denoising diffusion probabilistic model (DDPM) with classifier and cooling guidance to generate optimized cell layouts with enhanced cooling paths, significantly lowering the maximum temperature of the cells. By incorporating position-based classifier guidance, we ensure the feasibility of generated layouts. Meanwhile, cooling guidance directly optimizes cooling-efficiency, making our approach uniquely effective. When compared to two advanced models, the Tabular Denoising Diffusion Probabilistic Model (TabDDPM) and the Conditional Tabular GAN (CTGAN), our cooling-guided diffusion model notably outperforms both. It is five times more effective than TabDDPM and sixty-six times better than CTGAN across key metrics such as feasibility, diversity, and cooling efficiency. This research marks a significant leap forward in the field, aiming to optimize battery cell layouts for superior cooling efficiency, thus setting the stage for the development of more effective and dependable battery thermal management systems.

I can kill foxes but I can't kill wolves. Not in real life, obviously – in real life I send emails eight hours a day – but in The Legend of Zelda: Tears of the Kingdom, where every animal is an arrow away from becoming a fortifying meal. Shoot a wolf and you'll be rewarded with a thick red slab of raw prime meat, but I can't do it, I just can't do it, even though they often attack me in packs. They look too much like dogs. I can kill a fox – even though they never attack me, and they often let out sad little yelps – but many other gamers can't.

The rapid growth of data generation fueled by artificial intelligence (AI) has transformed how data is stored, processed, managed, and transferred, while increasing the demand for computing power across cloud and edge data centers. To meet the demand generated by AI, data centers are evolving and adapting their design, power infrastructure, and cooling equipment in various unique ways. Data centers provide vast computing resources and storage, enabling artificial intelligence (AI) to process massive datasets for training and inference. By hosting specialized hardware such as GPUs and TPUs, data centers accelerate complex calculations, supporting AI applications and workloads. As Dgtl Infra delves deeper into the evolving relationship between artificial intelligence and data centers, we offer insights on power consumption, cooling requirements, and the pivotal role of data centers in supporting AI.

The graphics card, also known as Graphics Processing Unit (GPU), is responsible for calculating images in a computer, which can then be displayed on a monitor. It represents the interface between the processor's calculations and the monitor. However, the development of graphics cards is now so far advanced that, in addition to this function, they can also support and relieve the CPU during calculations. The computer's processor calculates what data a certain program wants to display on the screen and outputs it as so-called image data. This, mostly numerical, data is then converted by the GPU so that it can be displayed on a monitor or other device. Many laptops and computers contain graphics cards that are already mounted on the circuit board, i.e. the mainboard.

Achieving fast cooling of motional modes is a prerequisite for leveraging such bosonic quanta for high-speed quantum information processing. In this Letter, we address the aspect of reducing the time limit for cooling, below that constrained by the conventional sideband cooling techniques, and propose a scheme to apply deep reinforcement learning (DRL) to achieve this. In particular, we have numerically demonstrated how the scheme can be used effectively to accelerate the dynamic motional cooling of a macroscopic magnonic sphere, and how it can be uniformly extended to more complex systems, for example, a tripartite opto-magno-mechanical system, to obtain cooling of the motional mode below the time bound of coherent cooling. While conventional sideband cooling methods do not work beyond the well-known rotating wave approximation (RWA) regimes, our proposed DRL scheme can be applied uniformly to regimes operating within and beyond the RWA, and thus, this offers a new and complete toolkit for rapid control and generation of macroscopic quantum states for application in quantum technologies. Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license.

Inspur Information, a leading IT infrastructure solutions provider, launched its next-generation G7 server platform. The AMD CPU-based platform harnesses the latest 5nm AMD EPYC 9004 Series processors to offer powerful compute performance, high flexibility and high scalability that is capable of handling a wide range of computing scenarios, including virtualization, high-performance computing, big data and AI. The G7 platform provides an 86% performance improvement, and a floating-point calculation improvement of 110% compared to the previous-generation A6 server platform. It is the ultimate solution for nearly every scenario that drives exceptional time-to-results for your business-critical applications with AMD EPYC 9004 Series processors. "The G7 platform was designed with expandability and flexibility at its core" Ultimate Flexibility The G7 server platform introduces a bevy of upgrades and innovations such as PCIe 5.0, DDR5 memory and E1.S/E3.S storage.