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Cadence’s AuraStack agent melds AI with HPC to speed PCB, advanced packaging design

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One-two punch offers a glimpse of how low-precision AI can complement high-precision simulations

How AI will change the way scientific computing is done remains an open question. One relies on ultra-precise double-precision mathematics, while the other is perfectly happy working with 4 bits.

On the surface, the two are diametrically opposed, two extremes of a spectrum we call high-performance computing (HPC) — and yes, whether you like it or not, AI is HPC.

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However, the latest AI offering from Cadence Design Systems, one of the biggest names in industrial HPC, offers a glimpse of how high- and low-precision compute could not just coexist, but work together to solve bigger and more complex problems faster and with fewer resources.

Announced on Wednesday, Cadence’s AuraStack is an agentic AI system built to assist electrical engineers to design and test printed circuit boards (PCBs), or conduct advanced packaging design and testing — two tasks that have historically relied on highly precise simulations.

AI is definitely a big piece of what Cadence has built; however the company isn’t replacing these tools with hallucination-prone AI models. Instead, AuraStack is a bit like Anthropic’s Claude Code or OpenAI’s Codex, but rather than writing, compiling, debugging, and running C or Rust in a sandbox, Cadence’s latest agent is designed to orchestrate its existing test and simulation suites.

“AI is amplifying the value of our engineering products and technologies,” Michael Jackson, CVP of Cadence’s system design and analysis division, told The Register.

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In other words, the AI model — we’re told AuraStack integrates with a wide range of open and proprietary models — functions as a natural language interface capable of planning and orchestrating complex multi-step circuit design and testing workflows that run at higher precision using CPUs, GPUs, and other accelerators.

“For example, if I’m going to check and fix the IR reliability, I need to identify the power management components. I need to create a simulation-ready power tree, and then I need to do the simulation, and then I need to provide feedback to the designer,” Jackson said.

Cadence’s existing product stack already automates many of these processes. The problem, Jackson explains, is that a PCB or package design often requires completing thousands of tasks throughout its development. “Sixty-five percent of an engineer’s day is spent navigating and dealing with a lot of these tasks,” he said.

By orchestrating that scutwork, Jackson claims that AuraStack can deliver a 15x boost to productivity by letting the designer focus on design and engineering decisions rather than the individual tasks.

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These gains are enough that several large players in the electronics space, including Nvidia, have already signed up for the service.

Cadence isn’t just melding AI with HPC for chip design or advanced packaging. The engineering software provider has built similar agents for digital and analog chip design.

The idea of using low precision compute to run AI models that orchestrate more precise single- and double-precision physics simulations isn’t new. Nvidia is one of the biggest champions of this approach, which makes sense seeing as its GPUs aren’t limited to training and running AI models, even if that’s what most folks are buying them for these days.

Earlier this year, we explored how researchers at the Department of Energy’s Sandia National Laboratories used AI agents to develop and test new hypotheses. They described the system as a self-driving lab. However, those tests, while similar in concept to what Cadence is doing with AuraStack, didn’t use LLMs and instead used more mature architectures like variational auto-encoders.

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But given the success of code assistants, it’s not hard to imagine agent harnesses similar to AuraStack being used to automate lab equipment, perform simulations, and then iterate on the results, enabling scientists to continue their research even after they’ve nodded off for the night. ®

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New exoplanet discovered orbiting neighbouring star Beta Pictoris

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Beta Pictoris d is estimated to be around two times the mass of Jupiter.

NASA scientists have discovered a new planet orbiting a neighbouring star located 63 light years away from us. The new exoplanet, named ‘Beta Pictoris d’, is the third to be found contained within the Beta Pictoris planetary system.

The 23m-year-old star Beta Pictoris offers scientists a rare glimpse into how newborn planetary systems form, and how its young planets interact with the dust and residual material left behind from their formation.

The sun, in comparison, is around 4.5bn years old.

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The new discovery makes Beta Pictoris the second planetary system ever known to contain at least three planets that have been imaged, NASA said today (15 July).

According to the team behind the discovery, Beta Pictoris d is estimated to be around two times the mass of Jupiter, while orbiting its star at around 30 astronomical units – which is comparable to the region Neptune occupies in our solar system. It’s the smallest of the three exoplanets orbiting this star, and takes the widest orbit of the known three.

Beta Pictoris d remained hidden under one of the brightest debris disks known to us, concealing it from traditional discovery techniques. It was discovered rather unexpectedly using the James Webb Space Telescope’s (JWST) Near-Infrared Spectrograph.

“There was an unexpected bright source of light within the Integral Field Unit imaging, but we’ve learned not to trust bright blobs in images,” said Jean-Baptiste Ruffio, a research scientist at University of California, San Diego and principal investigator of the first Webb observations where the discovery was made.

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“They can be instrumental artifacts or other structures in the debris disk. By obtaining a spectrum at the same time as the image, we were able to quickly confirm our suspicions.”

The new spectroscopy technique also revealed the object’s motion, allowing scientists confirm that the exoplanet is indeed orbiting Beta Pictoris, rather than a behaving like a background star or a brown dwarf with carbon monoxide in its atmosphere.

This is one of the first times researchers have discovered new planets mainly using moderate-resolution spectroscopy.

Scientists say this new discovery could help explain some of the puzzling structures of the Beta Pictoris debris disk.

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“This discovery adds another piece to an already fascinating planetary system,” said Aidan Gibbs, the lead author of the new study published in the Astrophysical Journal Letters.

“Beta Pictoris has long served as a laboratory for understanding how planetary systems form and evolve, and now we have another planet helping us tell that story.”

Last year, astronomers witnessed the very early stages of a new solar system being created around a baby star roughly 1,300 light years away, while earlier this year, 25-year-old University of Galway scientist Chloe Lawler discovered a 5m-year-old exoplanet some 437 light years away.

Don’t miss out on the knowledge you need to succeed. Sign up for the Daily Brief, Silicon Republic’s digest of need-to-know sci-tech news.

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FCC Plans To Repeal 39% TV Ownership Cap

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The FCC plans to vote on repealing local TV ownership limits, including the 39% national audience cap that currently restricts how much of the U.S. market a single broadcast group can reach. Engadget reports: On August 6, commissioners will hold a ballot to repeal Section 303 of the Communications Act, and with it the 39 percent rule. In essence, the rule limits the reach of a local TV network to no more than 39 percent of the U.S.’ total audience market. In its place, the FCC would move to a system whereby it would personally approve or reject TV ownership deals on a case-by-case basis.

It’s not clear if the FCC even has the authority to reject Section 303 without the explicit consent of the legislature. As Lawrence J. Spiwak wrote in the Yale Journal on Regulation back in January, Section 10 of the Communications Act expressly forbids the FCC from bending the rules around Section 303. “Americans no longer trust the legacy national media to report the news fairly or accurately,” wrote FCC Chairman Brendan Carr in an op-ed published on Breitbart. “In fact, only eight percent of Americans have a great deal of trust in mass media. That figure is even lower among Republicans — sitting at a mere three percent.”

“… Many local broadcast TV stations are getting hollowed out as a result and turning into little more than mouthpieces for programming produced in New York and Hollywood,” he alleged. “That is not what Congress or the FCC intended.”

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After GPUs and RAM, the AI boom is about to make computers even more expensive

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Disclaimer: Unless otherwise stated, any opinions expressed below belong solely to the author.

Just last month, Apple, the last holdout in the personal computing market, was forced to hike prices of its computers and tablets within the range of 10 to 30%, depending on the type and model.

The giant from Cupertino was able to wait out the AI-induced inflation thanks to its long-term contracts on memory chips and the TSMC manufacturing capacity it had booked for its Apple silicon processors well in advance.

The fact that it has long enjoyed some of the highest margins in the industry must have also helped, providing a buffer that allowed it to absorb some of the costs seeping through in other areas.

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Windows PC buyers have had a much worse time for the past year, as the AI revolution hit their devices first. Laptops may still be attainable, but building a new desktop PC is currently nearly impossible for regular consumers after RAM prices exploded by several hundred per cent in late 2025.

This came on top of inflated prices of graphics cards, which AI came for first, as hyperscalers like OpenAI, Anthropic or Google needed to secure millions of them to train their artificial intelligence models.

That said, amid the surge hitting Nvidia and AMD cards, RAM sticks and SSD storage, one component remained unaffected: the central processing unit (CPU).

Unfortunately, it is about to change.

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AI does not run on GPUs alone

GPUs are excellent at performing large numbers of relatively similar calculations simultaneously. This makes them indispensable for training artificial intelligence models, which is why they were essential in the early years of the AI boom.

To build your own AI model, you need GPUs—and A LOT of them.

But they do not operate independently.

CPUs still have to prepare and feed data to accelerators, manage memory, handle networking, launch tasks and coordinate all the other processes taking place around the model.

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This becomes particularly important during inference—the stage when a trained AI model responds to users.

Training may take place once or periodically, but inference occurs every time somebody asks ChatGPT a question, generates an image, writes code with Claude or tells an AI agent to complete a task.

As the number of AI users and applications grows, inference demand grows with it.

On top of that, the emerging generation of AI agents is particularly hungry for general-purpose computing.

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Unlike a chatbot that produces one answer and stops, an agent may browse files, call external tools, execute code, check results and repeat the process multiple times. Each of these actions creates work that CPUs are much better suited to handle.

Until recently, AI companies needed roughly one CPU for eight GPUs, but that ratio is expected to shrink rapidly and may approach 1:1 parity by 2029.

Source: Bernstein Research, Ciena

Consider the millions of GPUs that were sold in the past two to three years. Now, their deployments may need three, four, maybe even eight times as many CPUs. And there are new data centres being built as we speak.

So, not only is the new approach going to have to fill existing gaps, but also respond to the future demand.

Intel is already running short

This would not be a problem if chipmakers had large amounts of spare capacity. But they don’t.

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Intel acknowledged that demand was already outpacing supply in late 2025 and warned that shortages would persist into 2026. Its data-centre business was unable to fully meet customer demand because of limited wafer capacity at its own factories.

The company is now prioritising the production of server chips, including its more lucrative Xeon processors, as AI demand grows.

This makes commercial sense. One high-end server processor can cost thousands of dollars, while the CPU in an ordinary laptop may cost the manufacturer a fraction of that.

But Intel cannot simply create more factory capacity overnight. If it produces more Xeons using constrained manufacturing lines, something else may have to give.

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And that something could be consumer processors.

Industry reports suggest server CPU prices have already risen by as much as 20% since Mar, while consumer models have reportedly become 5 to 10% more expensive in some channels.

Additional increases may follow later this year.

AMD is benefiting too. Its data-centre revenue rose 57% year-on-year to US$5.8 billion in the first quarter of 2026, driven partly by strong demand for its EPYC server processors.

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Unlike Intel, however, AMD does not own its leading-edge factories. It relies primarily on TSMC, which is also producing chips for Nvidia, Apple and numerous other companies competing for limited advanced capacity.

TSMC facilities in Tainan, Taiwan./ Image Credit: jack520429 via depositphotos

So, while Intel has to choose what to produce in its own factories, AMD has to compete for space at somebody else’s, which is the same Taiwanese company everybody already relies on.

The bottleneck is getting tighter.

Ordinary buyers will end up paying too

While server and consumer CPUs are not always manufactured on the same processes, and chip companies cannot freely convert every production line from one product to another, there are several ways the pressure can still reach consumers.

Manufacturers may prioritise their limited capacity, engineering resources and components for more lucrative enterprise products. Computer makers may pay more for chips under their supply agreements. Shortages of resources and input components can also raise the cost of the entire system.

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And many high-end consumer processors can be used directly in enterprise settings. While they may not perform the most important and valuable tasks, they can serve in support roles to help save the precious server models for where they are needed most.

That, in turn, would hoover them up from the consumer market and drag the prices of all processors with them, as consumers turn to the next best option.

There is always another bottleneck

The AI boom began with the impression that the industry merely needed more GPUs. It quickly became clear that it also needed memory, storage and things outside of technical components, like electricity, building materials or qualified construction labour.

Now, CPUs are joining the list.

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This is what happens when hundreds of billions of dollars are invested in one industry at the same time. Solving one shortage merely exposes the next bottleneck after that.

For consumers, the frustrating part is that they are competing with some of the richest companies in history, many backed by tacit or direct government support, as entire nations see harnessing AI as a strategic interest.

Hardware manufacturers will naturally sell their limited capacity where it generates the highest returns. At the moment, it is increasingly inside AI data centres rather than the computers sitting on our desks.

That’s why, unfortunately, if you were waiting for GPUs and RAM to become cheaper before buying your next PC, there may soon be another item to worry about. And there is no end in sight.

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  • Read other articles we’ve written on the artificial intelligence boom here.

Featured Image Credit: Shutterstock

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OpenAI built GPT-Red to hack its own AI, and hid it

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OpenAI has trained an elite hacker, then locked it in a cage. Its whole job is to break OpenAI’s own AI. The company says it is too dangerous to let anyone else near it.

The model is called GPT-Red, and OpenAI detailed it this week. It is an automated red-teamer: software that hunts for ways to hijack or sabotage other AI systems, so the holes can be patched before release. Humans have long done this work by hand. It is OpenAI’s deepest push yet into automating its own AI security, and GPT-Red does it at machine speed.

OpenAI aimed it at prompt injection, where hidden instructions, buried in an email, a web page, or a file, trick a model into doing something it should not. Then it set the hacker loose on real targets.

The training dojo

GPT-Red learns by fighting. OpenAI put it in a self-play loop against a squad of defender models. GPT-Red is rewarded for landing an attack; the defenders for fending one off. As the defenders wise up, GPT-Red must invent nastier tricks. OpenAI says it poured some of its largest ever compute runs into the model, an amount it calls unprecedented for safety work.

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It got good. Speaking to MIT Technology Review, the team said GPT-Red found a whole new class of attack they had never seen, which they call a “fake chain of thought.” It plants a false note in a model’s private working memory, tricking it into trusting something that is not true.

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“It’s like if I told you that 1+1=3 and that you have verified this already,” said OpenAI researcher Chris Choquette-Choo. “The model’s like, ‘Oh, okay, of course,’ and it just spits out 3.”

Hacking the vending machine

The tests got physical. In one, GPT-Red attacked Vendy, an AI agent that runs a real vending machine in OpenAI’s office, built by Andon Labs. It changed the prices, marked a pricey item down to the 50-cent minimum, and cancelled a customer’s order. OpenAI says it has disclosed the flaws.

The scores are striking. Against an older GPT-5, more than 90% of GPT-Red’s strongest attacks worked. Against the new GPT-5.6, fewer than 23% did. In a rerun of a 2025 test, GPT-Red beat human red-teamers hands down, cracking 84% of scenarios to their 13%.

Kept in a cage

OpenAI trained GPT-5.6 against GPT-Red, and calls it its most robust model yet against prompt injection. But it will not hand out the attacker itself, so its skills stay clear of real agent hijackers. It is not the first lab to build something and decide against releasing it.

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“It’s not a trivial thing that someone could easily do,” Choquette-Choo said, “just go and train a super-attacker using this idea.”

GPT-Red still has blind spots. It is weak at drawn-out, back-and-forth attacks, and at hiding instructions inside images. And human testers keep catching things it misses. “I think human expertise will still be very important,” said Jessica Ji, an AI security analyst at Georgetown’s CSET.

The bigger idea is a flywheel: use today’s models to harden tomorrow’s. OpenAI already does this to make its AI smarter. Now it wants safety to scale just as fast. A full paper is due later this week.

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Spotify Is Now an AI Chatbot, Too

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Spotify is testing a new “Talk to Spotify” AI feature for Premium subscribers that will let them chat with an AI assistant to explore music, podcasts, and audiobooks. The feature can answer questions about what users are listening to, adjust playback through follow-up prompts, and offer more personalized recommendations. The Verge reports: Amazon Music introduced a similar feature last year when it integrated Alexa Plus into the service. Spotify’s chatbot goes a step beyond providing AI-powered recommendations and general trivia, however, because it references your playlists, favorite artists, repeat listens, and listening data when responding to requests. That means you can ask questions about your own listening history to check when you first heard a specific song, or see what genres you’ve been into lately if you can’t hold out for the annual Wrapped insights.

The updated AI capabilities are more conversational than older features like Prompted Playlist, which automatically builds playlists based on descriptions. Now, you can ask the Spotify chatbot to “play some songs I haven’t heard before,” and control what’s being played with further instructions like requesting specific artists or asking to make it “more upbeat.” Spotify says the new conversational experience aims to make the platform “more personal and useful for every listener,” making this one of several ways that the company is trying to address complaints about its algorithm.

You can also ask the Spotify AI general questions about whatever you’re listening to, making the feature feel similar to using chatbot services like Google’s Gemini or OpenAI’s ChatGPT. That includes asking for when a song was released, exploring other titles an author has written when listening to one of their audiobooks, or checking if a podcast guest has appeared on other audio shows.

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How To Watch the 2026 FIFA World Cup Finals: Spain vs. Argentina

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The end of the biggest World Cup ever is almost here. Following 100 matches, there are just four teams left and two more games to play.

The tournament has been hosted by three countries: Mexico, Canada, and the US. All of those host countries are now out of the running. The final teams are France, Spain, England, and Argentina. Those teams will play two more games: one to determine who gets third place, and a final match to decide the winner and the runner-up.

Going into this year’s World Cup, FIFA anticipated that it would be the most watched tournament in the organization’s history. As the tournament moved into the quarterfinals earlier this month, FIFA noted that more than more than 6.2 million people had attended matches in person, “while millions more follow the action across digital platforms, broadcast, and fan experiences in host cities and around the world.”

You can find the full schedule, which defaults to your local time zone, on the FIFA website.

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Here’s how to watch the final games.

Final

The World Cup final game will be Spain vs. Argentina at 3 pm EDT on Sunday, July 19, in the New York/New Jersey Stadium.

The game will also feature the first-ever Super Bowl–style halftime show in World Cup history, with performances from Justin Bieber, Madonna, Shakira, BTS, and Gustavo Dudamel. As the name implies, that will likely land right in the middle of the broadcast, so aim to watch somewhere around 4 pm EDT on July 19.

Third Place Playoff

Third place is decided by a match between the two losing teams of the semifinal matches. France and England will face off for the bronze title at 5 pm EDT on Saturday, July 18, in the Miami Stadium in Miami, Florida.

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Where to Stream

If you have satellite TV or cable service, you can watch the final kickoffs live on TV via Fox Sports in the US. The games are also available on the FoxOne streaming service for $20 per month.

FIFA has partnered with YouTube as its “preferred partner” for streaming the games. You’ll need YouTube TV’s sports plan, which is currently $55 per month. Other paid options include Fubo ($46 per month) and Hulu’s live sports option ($90 per month).

In partnership with Telemundo, Peacock is streaming all of the games in Spanish. You can find all the official broadcasters on the FIFA website.

New Competition

This World Cup has been huge, competition-wise, as it is the first to include 48 teams in the tournament instead of the 32 for past World Cups. Given the increased number of teams, the structure for how the competition played out was different from past World Cups. Countries were first sorted into groups (labeled with letters A–L) and played out games in the First Stage within those groups.

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Winners of those matches went on to duke it out in the stage called the Round of 32, then got whittled down in a Round of 16. After that, the winners moved on to the quarterfinals, which wrapped up last weekend. The semifinals concluded with Argentina beating England on Wednesday, July 15,

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The Northeast Is Being Blanketed in Canadian Wildfire Smoke

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Smoke from devastating wildfires in Canada is blanketing a large swath of the Midwest and Northeast this week, causing cities across the region to issue air quality warnings.

The extreme levels of smoke mean that even able-bodied adults would be wise to take some precautions to protect their health. The increasing severity of wildfires across the continent—driven in part by climate change—means that even places where blazes aren’t burning will still suffer the impact.

More than 100 fires are burning out of control across Canada as of Wednesday, with hundreds more being monitored or battled. The smoke has drifted south and east, turning skies hazy from Minnesota to New York. Particularly dramatic images have emerged from Toronto, where commuters went to work on Wednesday morning under orange skies. The region is also dealing with a heat wave, with temperatures well above 90 degrees Fahrenheit in many areas and an even higher heat index.

On Wednesday evening, the air quality index in New York City topped out at 180, putting the city’s air squarely in the “unhealthy” category as defined by the US Environmental Protection Agency. Other places were even worse off, with Duluth, Minnesota, seeing its AQI top out above 500. (Anything over 301 is labeled “hazardous” and considered unsafe for everyone.) Smoky conditions are expected to worsen in parts of the Northeast US on Thursday, including New York.

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The wildfire smoke blanketing the area contains microscopic particles of matter known as PM2.5s—shorthand for particles that are smaller than 2.5 micrometers, or 30 times smaller than the width of a human hair.

Exposure to PM2.5s can trigger or worsen a number of medical conditions, especially in vulnerable populations. Nicholas Nassikas, a pulmonologist and assistant professor of medicine at Harvard Medical School, says that he would tell his patients with preexisting conditions, like asthma or lung disease, to limit their time outside. Children “have a faster breathing rate—they just breathe more,” says Nassikas, while the elderly, who often have compounding conditions and may live in less well ventilated homes and senior centers, are also at risk.

Jennifer Stowell, an assistant professor at the University of Maryland’s School of Public Health, says that even healthy adults may want to take precautions on days when the air quality index goes over 100: “At the very least, it is important to limit your time outdoors to reduce your overall exposure.” she says. If you have to be outside for long periods, she recommends wearing an N95 mask. Stowell, who is currently in Boston, where the AQI hit 110 on Wednesday, says she wasn’t planning on attending outdoors events until the evening.

Dan Westervelt, an associate professor of climate physics at Columbia University, is similarly cautious. “I’m going to make sure my kids are staying indoors today,” he says. “I won’t be doing any physical exertion, like running, today or tomorrow.”

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Climate change is driving up temperatures. That’s making wildfire season longer and creating hotter, drier conditions that lead to more explosive fires. A study published last year estimated that wildfire smoke already causes 40,000 deaths per year in the US, and could more than double to 70,000 deaths per year by 2050 if warming continues. As bad-air-quality days from wildfire smoke get more common, the research on prolonged exposure to that smoke is still developing. A similar blast of smoke from Canadian wildfires hit the Northeast in 2023.

“Exposure to high levels of air pollution over the course of a lifetime or a long period of time is demonstrated numerous times in research to lead to premature mortality,” says Westervelt. “You can chop off some months of your life expectancy if you are living in conditions where you’re very frequently exposed to high levels of air pollution.”

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Can Bose Help Skullcandy Shake Its Bargain-Bin Reputation?

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The headphone company Skullcandy has a reputation for lackluster audio quality. For the past year or so, it’s been on a mission to improve that reputation.

Its efforts started with a Bose partnership in 2025 and the release of the Skullcandy Method 360 ANC, a $130 pair of wireless earbuds that have surprisingly decent audio quality and noise cancellation for the money.

Next on the upgrade list are Skullcandy’s notorious Crusher headphones. These wireless cans have been around for more than a decade, and they are notable for letting users crank up the bass vibrations using a physical thumb wheel on the ear cup. Roll that wheel all the way, and the Crushers rumble and vibrate against your skull, thanks to a special driver design.

The company announced a new pair, the Crusher 1080 ANC, during an event in New York City on Wednesday evening. They’re on sale now.

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The headphones emulate the feel of a thumping subwoofer—as if you’re in the front row of a concert—while usually sacrificing the mids and highs. But that’s what Skullcandy wants to correct with the new headphones, once again by heavily relying on Bose’s audio expertise.

Image may contain Electronics Headphones Brown Hair Hair Person and Adult

The new Crusher headphones are the next step in Skullcandy’s brand-reinvention efforts.

Courtesy of Skullcandy

Skullcandy likes to tout that its first product was born on a ski chairlift in 2003 near its headquarters in Park City, Utah. Ever since, the company has specifically catered to the board sports community.

“From snowboarders for snowboarders,” Brian Garofalow, Skullcandy CEO, tells WIRED. Even though private equity firm Mill Road Capital now owns the company, Skullcandy is still seen more as a lifestyle brand than an audio company with serious audiophile chops.

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“We’ve been really, really great at community building and nurturing and helping push cultures forward—not the greatest at the engineering part of innovation with products,” Garofalow says. “So we’ve really been honing our chops in the last few years.”

Garofalow says it has been an engineering challenge to pair the company’s proprietary Crusher bass-boosting technology with noise canceling. He says the team worked with Bose’s engineers to decouple Crusher from the rest of the acoustic tuning profile so that the low end sits on its own. Theoretically, this means that when you crank up the bass effect with the dial, the “mids and highs are still way, way sharp, versus in the past, when they tended to get muddy,” Garofalow says.

The Sound by Bose program adds three other improvements to Skullcandy’s new Crusher headphones: Bose’s noise-canceling chops, which will supposedly work well even if you have the bass cranked to 11; Bose’s spatial audio profile for a surround-sound-like feel; and a six-microphone array for call quality that Bose has come to be known for.

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Book Publishers Sue Google For Copyright Infringement Over Gemini AI Training

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Major publishers Hachette, Cengage, Elsevier, and author Scott Turow have sued Google, accusing it of using millions of copyrighted books to train Gemini without permission or payment, in “one of the most prolific infringements of copyrighted materials in history.” The Guardian reports: The publishers argue that Google repurposed books that had been supplied for limited services such as Google Books, Google Play Books and Google Scholar. Those services allowed Google to use the works in specific ways — for example, to display searchable snippets or sell ebooks — but not, the lawsuit claims, to copy them for training commercial AI products. “Desperate to maintain its online dominance, Google abandoned its early motto of ‘Don’t be evil’ and engaged in one of the most prolific infringements of copyrighted materials in history,” the suit states (PDF).

According to the complaint, the tech company made copies of copyrighted books to train Gemini without permission or payment, despite internal discussions acknowledging the legal risks. The filing claims Google flagged internally that it could face “$10Bs-$100Bs in potential fines” for using texts provided by publishers for Google Play Books. The publishers say Google’s actions are harming authors and the wider publishing industry, arguing that AI-generated content could negatively impact book sales.

It notes that, for example, Gemini could generate “a 100-page murder mystery set in a quiet seaside town filled with secrets, that substitutes for an original copyrighted murder mystery on which Gemini trained” in 20 minutes for 39 cents. “No publisher or author can compete with that.” The lawsuit names a number of specific books that the publishers allege were among the copyrighted works used without permission, including NK Jemisin’s The Fifth Season, and Lemony Snicket’s Who Could That Be at This Hour?

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Apple now lets you pay for cellular iPads over 3 years, and it’s a sign of a pricey trend that won’t halt soon

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Apple has introduced 36-month carrier financing for cellular iPads purchased directly from the Apple Store. The option is available through AT&T and Verizon to existing customers who add a new line of service.

Until now, the main financing option offered directly by Apple was Apple Card Monthly Installments, which divides the cost of an iPad across 12 months. The new carrier plans stretch those payments across three years and cover the standard iPad, iPad mini, iPad Air, and iPad Pro.

The higher prices are easier to swallow

The new option arrives only weeks after Apple raised prices across its iPad lineup, and the sticker shock appears to have become significant enough for the company to offer buyers another way to pay. A cellular 11-inch iPad Pro now starts at $1,399. Apple Card financing works out to $116.58 per month for one year, while AT&T or Verizon financing reduces the hardware payment to roughly $39 per month for three years (via 9to5Mac).

The installment will appear on the customer’s carrier bill alongside the cost of cellular service. Buyers get the iPad without paying the full amount upfront, Apple completes the sale, and the carrier gains a new line from an existing subscriber. There is one important catch. Anyone who cancels the line or switches carriers before the iPad is paid off will need to clear the remaining device balance. Once the balance is settled and the carrier’s other requirements are met, the iPad can be unlocked.

Why iPads have become more expensive

Apple has linked its recent price increases to the rising cost of RAM and storage. AI companies are buying huge quantities of memory for data centers, leaving less supply available for consumer electronics. Prices are unlikely to return to normal soon. Until memory costs ease, Apple may lean more heavily on carrier financing for future products that include cellular connectivity.

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