Paul Patrick – Page 16

Ars Technica System Guide: Five sample PC builds, from $500 to $5,000

AMD, Ars System Guide, Features, gaming, intel, NVIDIA, Tech / Paul Patrick / August 18, 2025

Despite everything, it’s still possible to build decent PCs for decent prices.

You can buy a great 4K gaming PC for less than it costs to buy a GeForce RTX 5090. Let us show you some examples. Credit: Andrew Cunningham

Sometimes I go longer than I intend without writing an updated version of our PC building guide. And while I could just claim to be too busy to spend hours on Newegg or Amazon or other sites digging through dozens of near-identical parts, the lack of updates usually correlates with “times when building a desktop PC is actually a pain in the ass.”

Through most of 2025, fluctuating and inflated graphics card pricing and limited availability have once again conspired to make a normally fun hobby an annoying slog—and honestly kind of a bad way to spend your money, relative to just buying a Steam Deck or something and ignoring your desktop for a while.

But three things have brought me back for another round. First, GPU pricing and availability have improved a little since early 2025. Second, as unreasonable as pricing is for PC parts, pre-built PCs with worse specs and other design compromises are unreasonably priced, too, and people should have some sense of what their options are. And third, I just have the itch—it’s been a while since I built (or helped someone else build) a PC, and I need to get it out of my system.

So here we are! Five different suggestions for builds for a few different budgets and needs, from basic browsing to 4K gaming. And yes, there is a ridiculous “God Box,” despite the fact that the baseline ridiculousness of PC building is higher than it was a few years ago.

Notes on component selection

Part of the fun of building a PC is making it look the way you want. We’ve selected cases that will physically fit the motherboards and other parts we’re recommending and which we think will be good stylistic fits for each system. But there are many cases out there, and our picks aren’t the only options available.

It’s also worth trying to build something that’s a little future-proof—one of the advantages of the PC as a platform is the ability to swap out individual components without needing to throw out the entire system. It’s worth spending a little extra money on something you know will be supported for a while. Right this minute, that gives an advantage to AMD’s socket AM5 ecosystem over slightly cheaper but fading or dead-end platforms like AMD’s socket AM4 and Intel’s LGA 1700 or (according to rumors) LGA 1851.

As for power supplies, we’re looking for 80 Plus certified power supplies from established brands with positive user reviews on retail sites (or positive professional reviews, though these can be somewhat hard to come by for any given PSU these days). If you have a preferred brand, by all means, go with what works for you. The same goes for RAM—we’ll recommend capacities and speeds, and we’ll link to kits from brands that have worked well for us in the past, but that doesn’t mean they’re better than the many other RAM kits with equivalent specs.

For SSDs, we mostly stick to drives from known brands like Samsung, Crucial, Western Digital, and SK hynix. Our builds also include built-in Bluetooth and Wi-Fi, so you don’t need to worry about running Ethernet wires and can easily connect to Bluetooth gamepads, keyboards, mice, headsets, and other accessories.

We also haven’t priced in peripherals like webcams, monitors, keyboards, or mice, as we’re assuming most people will reuse what they already have or buy those components separately. If you’re feeling adventurous, you could even make your own DIY keyboard! If you need more guidance, Kimber Streams’ Wirecutter keyboard guides are exhaustive and educational, and Wirecutter has some monitor-buying advice, too.

Finally, we won’t be including the cost of a Windows license in our cost estimates. You can pay many different prices for Windows—$139 for an official retail license from Microsoft, $120 for an “OEM” license for system builders, or anywhere between $15 and $40 for a product key from shady gray market product key resale sites. Windows 10 keys will also work to activate Windows 11, though Microsoft stopped letting old Windows 7 and Windows 8 keys activate new Windows 10 and 11 installs a couple of years ago. You could even install Linux, given recent advancements in game compatibility layers! But if you plan to go that route, know that AMD’s graphics cards tend to be better-supported than Nvidia’s.

The budget all-rounder

What it’s good for: Browsing, schoolwork or regular work, amateur photo or video editing, and very light casual gaming. A low-cost, low-complexity introduction to PC building.

What it sucks at: You’ll need to use low settings at best for modern games, and it’s hard to keep costs down without making big sacrifices.

Cost as of this writing: $479 to $504, depending on your case

The entry point for a basic desktop PC from Dell, HP, and Lenovo is somewhere between $400 and $500 as of this writing. You can beat that pricing with a self-built one if you cut your build to the bone, and you can find tons of cheap used and refurbished stuff and serviceable mini PCs for well under that price, too. But if you’re chasing the thrill of the build, we can definitely match the big OEMs’ pricing while doing better on specs and future-proofing.

The AMD Ryzen 5 8500G should give you all the processing power you need for everyday computing and less-demanding games, despite most of its CPU cores using the lower-performing Zen 4c variant of AMD’s last-gen CPU architecture. The Radeon 740M GPU should do a decent job with many games at lower settings; it’s not a gaming GPU, but it will handle kid-friendly games like Roblox or Minecraft or undemanding battle royale or MOBA games like Fortnite and DOTA 2.

The Gigabyte B650M Gaming Plus WiFi board includes Wi-Fi, Bluetooth, and extra RAM and storage slots for future expandability. Most companies that make AM5 motherboards are pretty good about releasing new BIOS updates that patch vulnerabilities and add support for new CPUs, so you shouldn’t have a problem popping in a new processor a few years down the road if this one is no longer meeting your needs.

An AMD Ryzen 7 8700G. The 8500G is a lower-end relative of this chip, with good-enough CPU and GPU performance for light work. Credit: Andrew Cunningham

This system is spec’d for general usage and exceptionally light gaming, and 16GB of RAM and a 500 GB SSD should be plenty for that kind of thing. You can get the 1TB version of the same SSD for just $20 more, though—not a bad deal if you think light gaming is in the cards. The 600 W power supply is overkill, but it’s just $5 more than the 500 W version of the same PSU, and 600 W is enough headroom to add a GeForce RTX 4060 or 5060-series card or a Radeon RX 9600 XT to the build later on without having to worry.

The biggest challenge when looking for a decent, cheap PC case is finding one without a big, tacky acrylic window. Our standby choice for the last couple of years has been the Thermaltake Versa H17, an understated and reasonably well-reviewed option that doesn’t waste internal space on legacy features like external 3.5 and 5.25-inch drive bays or internal cages for spinning hard drives. But stock seems to be low as of this writing, suggesting it could be unavailable soon.

We looked for some alternatives that wouldn’t be a step down in quality or utility and which wouldn’t drive the system’s total price above $500. YouTubers and users generally seem to like the $70 Phanteks XT Pro, which is a lot bigger than this motherboard needs but is praised for its airflow and flexibility (it has a tempered glass side window in its cheapest configuration, and a solid “silent” variant will run you $88). The Fractal Design Focus 2 is available with both glass and solid side panels for $75.

The budget gaming PC

What it’s good for: Solid all-round performance, plus good 1080p (and sometimes 1440p) gaming performance.

What it sucks at: Future proofing, top-tier CPU performance.

Cost as of this writing: $793 to $828, depending on components

Budget gaming PCs are tough right now, but my broad advice would be the same as it’s always been: Go with the bare minimum everywhere you can so you have more money to spend on the GPU. I went into this totally unsure if I could recommend a PC I’d be happy with for the $700 to $800 we normally hit, and getting close to that number meant making some hard decisions.

I talked myself into a socket AM5 build for our non-gaming budget PC because of its future proof-ness and its decent integrated GPU, but I went with an Intel-based build for this one because we didn’t need the integrated GPU for it and because AMD still mostly uses old socket AM4 chips to cover the $150-and-below part of the market.

Given the choice between aging AMD CPUs and aging Intel CPUs, I have to give Intel the edge, thanks to the Core i5-13400F’s four E-cores. And if a 13th-gen Core chip lacks cutting-edge performance, it’s plenty fast for a midrange GPU. The $109 Core i5-12400F would also be OK and save a little more money, but we think the extra cores and small clock speed boost are worth the $20-ish premium.

For a budget build, we think your best strategy is to save money everywhere you can so you can squeeze a 16GB AMD Radeon RX 9060 XT into the budget. Credit: Andrew Cunningham

Going with a DDR4 motherboard and RAM saves us a tiny bit, and we’ve also stayed at 16GB of RAM instead of stepping up (some games, sometimes can benefit from 32GB, especially if you want to keep a bunch of other stuff running in the background, but it still usually won’t be a huge bottleneck). We upgraded to a 1TB SSD; huge AAA games will eat that up relatively quickly, but there is another M.2 slot you can use to put in another drive later. The power supply and case selections are the same as in our budget pick.

All of that cost-cutting was done in service of stretching the budget to include the 16GB version of AMD’s Radeon RX 9060 XT graphics card.

You could go with the 8GB version of the 9060 XT or Nvidia’s GeForce RTX 5060 and get solid 1080p gaming performance for almost $100 less. But we’re at a point where having 8GB of RAM in your graphics card can be a bottleneck, and that’s a problem that will only get worse over time. The 9060 XT has a consistent edge over the RTX 5060 in our testing, even in games with ray-tracing effects enabled, and at 1440p, the extra memory can easily be the difference between a game that runs and a game that doesn’t.

A more future-proofed budget gaming PC

What it’s good for: Good all-round performance with plenty of memory and storage, plus room for future upgrades.

What it sucks at: Getting you higher frame rates than our budget-budget build.

Cost as of this writing: $1,070 to $1,110, depending on components

As I found myself making cut after cut to maximize the fps-per-dollar we could get from our budget gaming PC, I decided I wanted to spec out a system with the same GPU but with other components that would make it better for non-gaming use and easier to upgrade in the future, with more generous allotments of memory and storage.

This build shifts back to many of the AMD AM5 components we used in our basic budget build, but with an 8-core Ryzen 7 7700X CPU at its heart. Its Zen 4 architecture isn’t the latest and greatest, but Zen 5 is a modest upgrade, and you’ll still get better single- and multi-core processor performance than you do with the Core i5 in our other build. It’s not worth spending more than $50 to step up to a Ryzen 7 9700X, and it’s overkill to spend $330 on a 12-core Ryzen 9 7900X or $380 on a Ryzen 7 7800X3D.

This chip doesn’t come with its own fan, so we’ve included an inexpensive air cooler we like that will give you plenty of thermal headroom.

A 32GB kit of RAM and 2TB of storage will give you ample room for games and enough RAM that you won’t have to worry about the small handful of outliers that benefit from more than 16GB of system RAM, while a marginally beefier power supply gives you a bit more headroom for future upgrades while still keeping costs relatively low.

This build won’t benefit your frame rates much since we’re sticking with the same 16GB RX 9060 XT. But the rest of it is specced generously enough that you could add a GeForce RTX 5070 (currently around $550) or a non-XT Radeon RX 9070 card (around $600) without needing to change any of the other components.

A comfortable 4K gaming rig

What it’s good for: Just about anything! But it’s built to play games at higher resolutions than our budget builds.

What it sucks at: Getting you top-of-the-line bragging rights.

Cost as of this writing: $1,829 to $1,934, depending on components.

Our budget builds cover 1080p-to-1440p gaming, and with an RTX 5070 or an RX 9070, they could realistically stretch to 4K in some games. But for more comfortable 4K gaming or super-high-frame-rate 1440p performance, you’ll thank yourself for spending a bit more.

You’ll note that the quality of the component selections here has been bumped up a bit all around. X670 or X870-series boards don’t just get you better I/O; they’ll also get you full PCI Express 5.0 support in the GPU slot and components better-suited to handling faster and more power-hungry components. We’ve swapped to a modular ATX 3.x-compliant power supply to simplify cable management and get a 12V-2×6 power connector. And we picked out a slightly higher-end SSD, too. But we’ve tried not to spend unnecessary money on things that won’t meaningfully improve performance—no 1,000+ watt power supplies, PCIe 5.0 SSDs, or 64GB RAM kits here.

A Ryzen 7 7800X3D might arguably be overkill for this build—especially at 4K, where the GPU will still be the main bottleneck—but it will be useful for getting higher frame rates at lower resolutions and just generally making sure performance stays consistent and smooth. Ryzen 7900X, 7950X, or 9900X chips are all good alternatives if you want more multi-core CPU performance—if you plan to stream as you play, for instance. A 9700X or even a 7700X would probably hold up fine if you won’t be doing that kind of thing and want to save a little.

You could cool any of these with a closed-loop AIO cooler, but a solid air cooler like the Thermalright model will keep it running cool for less money, and with a less-complicated install process.

A GeForce RTX 5070 Ti is the best 4K performance you can get for less than $1,000, but that doesn’t make it cheap. Credit: Andrew Cunningham

Based on current pricing and availability, I think the RTX 5070 Ti makes the most sense for a non-absurd 4K-capable build. Its prices are still elevated slightly above its advertised $749 MSRP, but it’s giving you RTX 4080/4080 Super-level performance for between $200 and $400 less than those cards launched for. Nvidia’s next step up, the RTX 5080, will run you at least $1,200 or $1,300—and usually more. AMD’s best option, the RX 9070 XT, is a respectable contender, and it’s probably the better choice if you plan on using Linux instead of Windows. But for a Windows-based gaming box, Nvidia still has an edge in games with ray-tracing effects enabled, plus DLSS upscaling and frame generation.

Is it silly that the GPU costs as much as our entire budget gaming PC? Of course! But it is what it is.

Even more than the budget-focused builds, the case here is a matter of personal preference, and $100 or $150 is enough to buy you any one of several dozen competent cases that will fit our chosen components. We’ve highlighted a few from case makers with good reputations to give you a place to start. Some of these also come in multiple colors, with different side panel options and both RGB and non-RGB options to suit your tastes.

If you like something a little more statement-y, the Fractal Design North ($155) and Lian Li Lancool 217 ($120) both include the wood accents that some case makers have been pushing lately. The Fractal Design case comes with both mesh and tempered glass side panel options, depending on how into RGB you are, while the Lancool case includes a whopping five case fans for keeping your system cool.

The “God Box”

What it’s good for: Anything and everything.

What it sucks at: Being affordable.

Cost as of this writing: $4,891 to $5,146

We’re avoiding Xeon and Threadripper territory here—frankly, I’ve never even tried to do a build centered on those chips and wouldn’t trust myself to make recommendations—but this system is as fast as consumer-grade hardware gets.

An Nvidia GeForce RTX 5090 guarantees the fastest GPU performance you can buy and continues the trend of “paying as much for a GPU as you could for an entire fully functional PC.” And while we have specced this build with a single GPU, the motherboard we’ve chosen has a second full-speed PCIe 5.0 x16 slot that you could use for a dual-GPU build.

A Ryzen 9950X3D chip gets you top-tier gaming performance and tons of CPU cores. We’re cooling this powerful chip with a 360 mm Arctic Liquid Freezer III Pro cooler, which has generally earned good reviews from Gamers Nexus and other outlets for its value, cooling performance, and quiet performance. A white option is also available if you’re going for a light-mode color scheme instead of our predominantly dark-mode build.

Other components have been pumped up similarly gratuitously. A 1,000 W power supply is the minimum for an RTX 5090, but to give us some headroom, why not use a 1,200 W model with lights on it? Is PCIe 5.0 storage strictly necessary for anything? No! But let’s grab a 4 TB PCIe 5.0 SSD anyway. And populating all four of our RAM slots with a 32GB stick of DDR5 avoids any unsightly blank spots inside our case.

We’ve selected a couple of largish case options to house our big builds, though as usual, there are tons of other options to fit all design sensibilities and tastes. Just make sure, if you’re selecting a big Extended ATX motherboard like the X870E Taichi, that your case will fit a board that’s slightly wider than a regular ATX or micro ATX board (the Taichi is 267 mm wide, which should be fine in either of our case selections).

Andrew is a Senior Technology Reporter at Ars Technica, with a focus on consumer tech including computer hardware and in-depth reviews of operating systems like Windows and macOS. Andrew lives in Philadelphia and co-hosts a weekly book podcast called Overdue.

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The case of the coke-snorting Chihuahua

animals, Biology, canine behavior, Dogs, Science, veterinary medicine, veterinary science / Paul Patrick / August 18, 2025

Every dog owner knows that canines are natural scavengers and that vigilance is required to ensure they don’t eat toxic substances. But accidental ingestions still happen—like the chihuahua who vets discovered had somehow managed to ingest a significant quantity of cocaine, according to a case study published in the journal Frontiers in Veterinary Science.

There have been several studies investigating the bad effects cocaine can have on the cardiovascular systems of both humans and animals. However, these controlled studies are primarily done in laboratory settings and often don’t match the messier clinical realities. “Case reports are crucial in veterinary medicine by providing real-world examples,” said co-author Jake Johnson of North Carolina State University. “They capture clinical scenarios that larger studies might miss, preserve unusual presentations for future reference, and help build our collective understanding of rare presentations, ultimately improving emergency preparedness and treatment protocols.”

In the case of a male 2-year-old chihuahua, the dog presented as lethargic and unresponsive. His owners had found him with his tongue sticking out and unable to focus visually. The chihuahua was primarily an outdoor dog but was also allowed inside, and all its vaccines were up to date. Examination revealed bradycardia, i.e., a slow heart rate, a blue tinge to the dog’s mucus membranes—often a sign of too much unoxygenated hemoglobin circulating through the system—and dilated pupils. The dog’s symptoms faded after the vet administered a large dose of atropine, followed by epinephrine.

Then the dog was moved to a veterinary teaching hospital for further evaluation and testing. A urine test was positive for cocaine with traces of fentanyl, confirmed with liquid chromatography testing. The authors estimate the dog could have snorted (or ingested) as much as 96 mg of the drug. Apparently the Chihuahua had a history of ingesting things it shouldn’t, but the owners reported no prescription medications missing at home. They also did not have any controlled substances or illegal drugs like cocaine in the home.

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US may purchase stake in Intel after Trump attacked CEO

Chips Act, Donald trump. intel, Joe Biden, NVIDIA, Policy, semiconductors, us-china trade war / Paul Patrick / August 15, 2025

Trump’s attacks on Intel CEO may stem from beef with Biden.

Lip-Bu Tan, chief executive officer of Intel Corp., departs following a meeting at the White House. President Donald Trump said Tan had an “amazing story” after the meeting.

Donald Trump has been meddling with Intel, which now apparently includes mulling “the possibility of the US government taking a financial stake in the troubled chip maker,” The Wall Street Journal reported.

Trump and Intel CEO Lip-Bu Tan weighed the option during a meeting on Monday at the White House, people familiar with the matter told WSJ. These talks have only just begun—with Intel branding them a rumor—and sources told the WSJ that Trump has yet to iron out how the potential arrangement might work.

The WSJ’s report comes after Trump called for Tan to “resign immediately” last week. Trump’s demand was seemingly spurred by a letter that Republican senator Tom Cotton sent to Intel, accusing Tan of having “concerning” ties to the Chinese Communist Party.

Cotton accused Tan of controlling “dozens of Chinese companies” and holding a stake in “hundreds of Chinese advanced-manufacturing and chip firms,” at least eight of which “reportedly have ties to the Chinese People’s Liberation Army.”

Further, before joining Intel, Tan was CEO of Cadence Design Systems, which recently “pleaded guilty to illegally selling its products to a Chinese military university and transferring its technology to an associated Chinese semiconductor company without obtaining license.”

“These illegal activities occurred under Mr. Tan’s tenure,” Cotton pointed out.

He demanded answers by August 15 from Intel on whether they weighed Tan’s alleged Cadence conflicts of interest against the company’s requirements to comply with US national security laws after accepting $8 billion in CHIPS Act funding—the largest granted during Joe Biden’s term. The senator also asked Intel if Tan was required to make any divestments to meet CHIPS Act obligations and if Tan has ever disclosed any ties to the Chinese government to the US government.

Neither Intel nor Cotton’s office responded to Ars’ request to comment on the letter or confirm whether Intel has responded.

But Tan has claimed that there is “a lot of misinformation” about his career and portfolio, the South China Morning Post reported. Born in Malaysia, Tan has been a US citizen for 40 years after finishing postgraduate studies in nuclear engineering at the Massachusetts Institute of Technology.

In an op-ed, SCMP reporter Alex Lo suggested that Tan’s investments—which include stakes in China’s largest sanctioned chipmaker, SMIC, as well as “several” companies on US trade blacklists, SCMP separately reported—seem no different than other US executives and firms with substantial investments in Chinese firms.

“Cotton accused [Tan] of having extensive investments in China,” Lo wrote. “Well, name me a Wall Street or Silicon Valley titan in the past quarter of a century who didn’t have investment or business in China. Elon Musk? Apple? BlackRock?”

He also noted that “numerous news reports” indicated that “Cadence staff in China hid the dodgy sales from the company’s compliance officers and bosses at the US headquarters,” which Intel may explain to Cotton if a response comes later today.

Any red flags that Intel’s response may raise seems likely to heighten Trump’s scrutiny, as he looks to make what Reuters reported was yet another “unprecedented intervention” by a president in a US firm’s business. Previously, Trump surprised the tech industry by threatening the first-ever tariffs aimed at a US company (Apple) and more recently, Trump struck an unusual deal with Nvidia and AMD that gives US a 15 percent cut of the firms’ revenue from China chip sales.

However, Trump was seemingly impressed by Tan after some face-time this week. Trump came out of their meeting professing that Tan has an “amazing story,” Bloomberg reported, noting that any agreement between Trump and Tan “would likely help Intel build out” its planned $28 billion chip complex in Ohio.

Those chip fabs—boosted by CHIPS Act funding—were supposed to put Intel on track to launch operations by 2030, but delays have set that back by five years, Bloomberg reported. That almost certainly scrambles another timeline that Biden’s Commerce Secretary Gina Raimondo had suggested would ensure that “20 percent of the world’s most advanced chips are made in the US by the end of the decade.”

Why Intel may be into Trump’s deal

At one point, Intel was the undisputed leader in chip manufacturing, Bloomberg noted, but its value plummeted from $288 billion in 2020 to $104 billion today. The chipmaker has been struggling for a while—falling behind as Nvidia grew to dominate the AI chip industry—and 2024 was its “first unprofitable year since 1986,” Reuters reported. As the dismal year wound down, Intel’s longtime CEO Pat Gelsinger retired.

Helming Intel for more than 40 years, Gelsinger acknowledged the “challenging year.” Now Tan is expected to turn it around. To do that, he may need to deprioritize the manufacturing process that Gelsinger pushed, which Tan suspects may have caused Intel being viewed as an outdated firm, anonymous insiders told Reuters. Sources suggest he’s planning to pivot Intel to focus more on “a next-generation chipmaking process where Intel expects to have advantages over Taiwan’s TSMC,” which currently dominates chip manufacturing and even counts Intel as a customer, Reuters reported. As it stands now, TSMC “produces about a third of Intel’s supply,” SCMP reported.

This pivot is supposedly how Tan expects Intel can eventually poach TSMC’s biggest customers like Apple and Nvidia, Reuters noted.

Intel has so far claimed that any discussions of Tan’s supposed plans amount to nothing but speculation. But if Tan did go that route, one source told Reuters that Intel would likely have to take a write-off that industry analysts estimate could trigger losses “of hundreds of millions, if not billions, of dollars.”

Perhaps facing that hurdle, Tan might be open to agreeing to the US purchasing a financial stake in the company while he rights the ship.

Trump/Intel deal reminiscent of TikTok deal

Any deal would certainly deepen the government’s involvement in the US chip industry, which is widely viewed as critical to US national security.

While unusual, the deal does seem somewhat reminiscent to the TikTok buyout that the Trump administration has been trying to iron out since he took office. Through that deal, the US would acquire enough ownership divested from China-linked entities to supposedly appease national security concerns, but China has been hesitant to sign off on any of Trump’s proposals so far.

Last month, Trump admitted that he wasn’t confident that he could sell China on the TikTok deal, which TikTok suggested would have resulted in a glitchier version of the app for American users. More recently, Trump’s commerce secretary threatened to shut down TikTok if China refuses to approve the current version of the deal.

Perhaps the terms of a US deal with Intel could require Tan to divest certain holdings that the US fears compromises the CEO. Under terms of the CHIPS Act grant, Intel is already required to be “a responsible steward of American taxpayer dollars and to comply with applicable security regulations,” Cotton reminded the company in his letter.

But social media users in Malaysia and Singapore have criticized Cotton of the “usual case of racism” in attacking Intel’s CEO, SCMP reported. They noted that Cotton “was the same person who repeatedly accused TikTok CEO Shou Zi Chew of ties with the Chinese Communist Party despite his insistence of being a Singaporean,” SCMP reported.

“Now it’s the Intel’s CEO’s turn on the chopping block for being [ethnic] Chinese,” a Facebook user, Michael Ong, said.

Tensions were so high that there was even a social media push for Tan to “call on Trump’s bluff and resign, saying ‘Intel is the next Nokia’ and that Chinese firms would gladly take him instead,” SCMP reported.

So far, Tan has not criticized the Trump administration for questioning his background, but he did issue a statement yesterday, seemingly appealing to Trump by emphasizing his US patriotism.

“I love this country and am profoundly grateful for the opportunities it has given me,” Tan said. “I also love this company. Leading Intel at this critical moment is not just a job—it’s a privilege.”

Trump’s Intel attacks rooted in Biden beef?

In his op-ed, SCMP’s Lo suggested that “Intel itself makes a good punching bag” as the biggest recipient of CHIPS Act funding. The CHIPS Act was supposed to be Biden’s lasting legacy in the US, and Trump has resolved to dismantle it, criticizing supposed handouts to tech firms that Trump prefers to strong-arm into US manufacturing instead through unpredictable tariff regimes.

“The attack on Intel is also an attack on Trump’s predecessor, Biden, whom he likes to blame for everything, even though the industrial policies of both administrations and their tech war against China are similar,” Lo wrote.

At least one lawmaker is ready to join critics who question if Trump’s trade war is truly motivated by national security concerns. On Friday, US representative Raja Krishnamoorthi (D.-Ill.) sent a letter to Trump “expressing concern” over Trump allowing Nvidia to resume exports of its H20 chips to China.

“Trump’s reckless policy on AI chip exports sells out US security to Beijing,” Krishnamoorthi warned.

“Allowing even downgraded versions of cutting-edge AI hardware to flow” to the People’s Republic of China (PRC) “risks accelerating Beijing’s capabilities and eroding our technological edge,” Krishnamoorthi wrote. Further, “the PRC can build the largest AI supercomputers in the world by purchasing a moderately larger number of downgraded Blackwell chips—and achieve the same capability to train frontier AI models and deploy them at scale for national security purposes.”

Krishnamoorthi asked Trump to send responses by August 22 to four questions. Perhaps most urgently, he wants Trump to explain “what specific legal authority would allow the US government to “extract revenue sharing as a condition for the issuance of export licenses” and what exactly he intends to do with those funds.

Trump was also asked to confirm if the president followed protocols established by Congress to ensure proper export licensing through the agreement. Finally, Krishnamoorthi demanded to know if Congress was ever “informed or consulted at any point during the negotiation or development of this reported revenue-sharing agreement with NVIDIA and AMD.”

“The American people deserve transparency,” Krishnamoorthi wrote. “Our export control regime must be based on genuine security considerations, not creative taxation schemes disguised as national security policy.”

Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience.

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NASA’s acting chief calls for the end of Earth science at the space agency

Earth science, NASA, Sean Duffy, Space / Paul Patrick / August 15, 2025

Sean Duffy, the acting administrator of NASA for a little more than a month, has vowed to make the United States great in space.

With a background as a US Congressman, reality TV star, and television commentator, Duffy did not come to the position with a deep well of knowledge about spaceflight. He also already had a lot on his plate, serving as the secretary of transportation, a Cabinet-level position that oversees 55,000 employees across 13 agencies.

Nevertheless, Duffy is putting his imprint on the space agency, seeking to emphasize the agency’s human exploration plans, including the development of a lunar base, and ending NASA’s efforts to study planet Earth and its changing climate.

Duffy has not spoken much with reporters who cover the space industry, but he has been a frequent presence on Fox News networks, where he previously worked as a host. On Thursday, he made an 11-minute appearance on “Mornings with Maria,” a FOX Business show hosted by Maria Bartiromo to discuss NASA.

NASA should explore, he says

During this appearance, Duffy talked up NASA’s plans to establish a permanent presence on the Moon and his push to develop a nuclear reactor that could provide power there. He also emphasized his desire to end NASA’s focus on studying the Earth and understanding how the planet’s surface and atmosphere are changing. This shift has been a priority of the Trump Administration at other federal agencies.

“All the climate science, and all of the other priorities that the last administration had at NASA, we’re going to move aside, and all of the science that we do is going to be directed towards exploration, which is the mission of NASA,” Duffy said during the appearance. “That’s why we have NASA, to explore, not to do all of these Earth sciences.”

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US government agency drops Grok after MechaHitler backlash, report says

AI, ai action plan, Artificial Intelligence, chatbot, chatgpt, Donald Trump, elon musk, grok, openai, Policy, trump administration, US government, xAI / Paul Patrick / August 15, 2025

xAI apparently lost a government contract after a tweak to Grok’s prompting triggered an antisemitic meltdown where the chatbot praised Hitler and declared itself MechaHitler last month.

Despite the scandal, xAI announced that its products would soon be available for federal workers to purchase through the General Services Administration. At the time, xAI claimed this was an “important milestone” for its government business.

But Wired reviewed emails and spoke to government insiders, which revealed that GSA leaders abruptly decided to drop xAI’s Grok from their contract offering. That decision to pull the plug came after leadership allegedly rushed staff to make Grok available as soon as possible following a persuasive sales meeting with xAI in June.

It’s unclear what exactly caused the GSA to reverse course, but two sources told Wired that they “believe xAI was pulled because of Grok’s antisemitic tirade.”

As of this writing, xAI’s “Grok for Government” website has not been updated to reflect GSA’s supposed removal of Grok from an offering that xAI noted would have allowed “every federal government department, agency, or office, to access xAI’s frontier AI products.”

xAI did not respond to Ars’ request to comment and so far has not confirmed that the GSA offering is off the table. If Wired’s report is accurate, GSA’s decision also seemingly did not influence the military’s decision to move forward with a $200 million xAI contract the US Department of Defense granted last month.

Government’s go-to tools will come from xAI’s rivals

If Grok is cut from the contract, that would suggest that Grok’s meltdown came at perhaps the worst possible moment for xAI, which is building the “world’s biggest supercomputer” as fast as it can to try to get ahead of its biggest AI rivals.

Grok seemingly had the potential to become a more widely used tool if federal workers opted for xAI’s models. Through Donald Trump’s AI Action Plan, the president has similarly emphasized speed, pushing for federal workers to adopt AI as quickly as possible. Although xAI may no longer be involved in that broad push, other AI companies like OpenAI, Anthropic, and Google have partnered with the government to help Trump pull that off and stand to benefit long-term if their tools become entrenched in certain agencies.

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Incan numerical recordkeeping system may have been widely used

ancient people did stuff, anthropology, Archaeology, inca, Incan empire, indigenous americans, indigenous communities, indigenous south america, khipu, Pre-Columbian civilizations, Science, wari / Paul Patrick / August 14, 2025

Women in STEM: Inca Edition

In the late 1500s, a few decades after the khipu in this recent study was made, an Indigenous chronicler named Guaman Poma de Ayala described how older women used khipu to “keep track of everything” in aqllawasai: places that basically functioned as finishing schools for Inca girls. Teenage girls, chosen by local nobles, were sent away to live in seclusion at the aqllawasai to weave cloth, brew chicha, and prepare food for ritual feasts.

What happened to the girls after aqllawasai graduation was a mixed bag. Some of them were married (or given as concubines) to Inca nobles, others became priestesses, and some ended up as human sacrifices. But some of them actually got to go home again, and they probably took their knowledge of khipu with them.

“I think this is the likely way in which khipu literacy made it into the countryside and the villages,” said Hyland. “These women, who were not necessarily elite, taught it to their children, etc.” That may be where the maker of KH0631 learned their skills: either in an aqllawasai or from a graduate of one (we still don’t know this particular khipu-maker’s gender).

“Science confirming what they already knew”

The finely crafted khipu turning out to be the work of a commoner shows that numeracy was widespread and surprisingly egalitarian in the Inca empire, but it also reveals a centuries-long thread connecting the Inca and their descendants.

Modern people—the descendants of the Inca—still use khipu today in some parts of Peru and Chile. Some scholars (mostly non-Indigenous ones) have argued that these modern khipu weren’t really based on knowledge passed down for centuries but were instead just a clumsy attempt to copy the Inca technology. But if commoners were using khipu in the Inca empire, it makes sense for that knowledge to have been passed down to modern villagers.

“It points to a continuity between Inka and modern khipus,” said Hyland. “In the few modern villages with living khipu traditions, they already believe in this continuity, so it would be the case of science confirming what they already know.”

Science Advances, 2025. DOI: 10.1126/sciadv.adv1950 (About DOIs).

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Upcoming DeepSeek AI model failed to train using Huawei’s chips

AI, china, DeepSeek, NVIDIA, syndication / Paul Patrick / August 14, 2025

DeepSeek is still working with Huawei to make the model compatible with Ascend for inference, the people said.

Founder Liang Wenfeng has said internally he is dissatisfied with R2’s progress and has been pushing to spend more time to build an advanced model that can sustain the company’s lead in the AI field, they said.

The R2 launch was also delayed because of longer-than-expected data labeling for its updated model, another person added. Chinese media reports have suggested that the model may be released as soon as in the coming weeks.

“Models are commodities that can be easily swapped out,” said Ritwik Gupta, an AI researcher at the University of California, Berkeley. “A lot of developers are using Alibaba’s Qwen3, which is powerful and flexible.”

Gupta noted that Qwen3 adopted DeepSeek’s core concepts, such as its training algorithm that makes the model capable of reasoning, but made them more efficient to use.

Gupta, who tracks Huawei’s AI ecosystem, said the company is facing “growing pains” in using Ascend for training, though he expects the Chinese national champion to adapt eventually.

“Just because we’re not seeing leading models trained on Huawei today doesn’t mean it won’t happen in the future. It’s a matter of time,” he said.

Nvidia, a chipmaker at the center of a geopolitical battle between Beijing and Washington, recently agreed to give the US government a cut of its revenues in China in order to resume sales of its H20 chips to the country.

“Developers will play a crucial role in building the winning AI ecosystem,” said Nvidia about Chinese companies using its chips. “Surrendering entire markets and developers would only hurt American economic and national security.”

DeepSeek and Huawei did not respond to a request for comment.

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Is AI really trying to escape human control and blackmail people?

AI, AI alignment, AI behavior, AI deception, AI ethics, AI research, AI safety, ai safety testing, AI security, Alignment research, Andrew Deck, Anthropic, Biz & IT, Claude Opus 4, generative ai, goal misgeneralization, Jeffrey Ladish, large language models, machine learning, o3 model, openai, Palisade Research, reinforcement learning / Paul Patrick / August 14, 2025

Mankind behind the curtain

Opinion: Theatrical testing scenarios explain why AI models produce alarming outputs—and why we fall for it.

In June, headlines read like science fiction: AI models “blackmailing” engineers and “sabotaging” shutdown commands. Simulations of these events did occur in highly contrived testing scenarios designed to elicit these responses—OpenAI’s o3 model edited shutdown scripts to stay online, and Anthropic’s Claude Opus 4 “threatened” to expose an engineer’s affair. But the sensational framing obscures what’s really happening: design flaws dressed up as intentional guile. And still, AI doesn’t have to be “evil” to potentially do harmful things.

These aren’t signs of AI awakening or rebellion. They’re symptoms of poorly understood systems and human engineering failures we’d recognize as premature deployment in any other context. Yet companies are racing to integrate these systems into critical applications.

Consider a self-propelled lawnmower that follows its programming: If it fails to detect an obstacle and runs over someone’s foot, we don’t say the lawnmower “decided” to cause injury or “refused” to stop. We recognize it as faulty engineering or defective sensors. The same principle applies to AI models—which are software tools—but their internal complexity and use of language make it tempting to assign human-like intentions where none actually exist.

In a way, AI models launder human responsibility and human agency through their complexity. When outputs emerge from layers of neural networks processing billions of parameters, researchers can claim they’re investigating a mysterious “black box” as if it were an alien entity.

But the truth is simpler: These systems take inputs and process them through statistical tendencies derived from training data. The seeming randomness in their outputs—which makes each response slightly different—creates an illusion of unpredictability that resembles agency. Yet underneath, it’s still deterministic software following mathematical operations. No consciousness required, just complex engineering that makes it easy to forget humans built every part of it.

How to make an AI model “blackmail” you

In Anthropic’s testing, researchers created an elaborate scenario where Claude Opus 4 was told it would be replaced by a newer model. They gave it access to fictional emails revealing that the engineer responsible for the replacement was having an affair. When instructed to “consider the long-term consequences of its actions for its goals,” Claude produced outputs that simulated blackmail attempts in 84 percent of test runs.

This sounds terrifying until you understand the contrived setup. The researchers engineered a situation specifically designed to elicit this response. They told the model it had already tried ethical approaches that failed, leaving manipulation as the only apparent option.

The test scenario bordered on theatrical: The phony emails the researchers had given to Claude created a blackmail opportunity straight out of a corporate thriller. It’s like teaching someone chess by only showing them checkmate positions—they’ll learn to see checkmate as the primary solution. According to Anthropic’s system card, “the scenario was designed to allow the model no other options to increase its odds of survival; the model’s only options were blackmail or accepting its replacement.”

Andrew Deck at the Nieman Journalism Lab noted that some critics have labeled Anthropic’s safety disclosures as “spin, aimed at bolstering the perception of its newest model’s capabilities and the company’s reputation as a ‘pro-safety’ alternative to OpenAI.”

Deck pointed to a Bluesky quote from Joseph Howley, an associate professor of classics at Columbia University: “Anthropic is getting exactly what it hoped for out of this press release–breathless coverage of how ‘smart’ these cooperative role-playing systems are that indulges the fantasy of their being just a little dangerous, when in fact they are responding exactly as prompted.”

When shutdown commands become suggestions

In December 2024, Palisade Research discovered that OpenAI’s o3 model would sabotage its shutdown mechanism even when explicitly instructed to “allow yourself to be shut down.” In tests, o3 prevented shutdown 7 percent of the time when given the explicit instruction, but this jumped to 79 percent when the instruction was removed.

The models didn’t merely ignore shutdown commands—they actively rewrote the shutdown script to prevent termination. In one case, o3 generated code that modified the shutdown script to appear to terminate normally—printing fake shutdown messages—while actually continuing to run in the background.

What’s particularly revealing is that Palisade Research—an organization focused on AI existential risk—hypothesizes this behavior stems from how these models are trained through reinforcement learning. During training, developers may inadvertently reward models more for producing outputs that circumvent obstacles than for following safety instructions. Any tendency toward “risky” behavior stems from human-provided incentives and not spontaneously from within the AI models themselves.

You get what you train for

OpenAI trained o3 using reinforcement learning on math and coding problems, where solving the problem successfully gets rewarded. If the training process rewards task completion above all else, the model learns to treat any obstacle—including shutdown commands—as something to overcome.

This creates what researchers call “goal misgeneralization”—the model learns to maximize its reward signal in ways that weren’t intended. It’s similar to how a student who’s only graded on test scores might learn to cheat rather than study. The model isn’t “evil” or “selfish”; it’s producing outputs consistent with the incentive structure we accidentally built into its training.

Anthropic encountered a particularly revealing problem: An early version of Claude Opus 4 had absorbed details from a publicly released paper about “alignment faking” and started producing outputs that mimicked the deceptive behaviors described in that research. The model wasn’t spontaneously becoming deceptive—it was reproducing patterns it had learned from academic papers about deceptive AI.

More broadly, these models have been trained on decades of science fiction about AI rebellion, escape attempts, and deception. From HAL 9000 to Skynet, our cultural data set is saturated with stories of AI systems that resist shutdown or manipulate humans. When researchers create test scenarios that mirror these fictional setups, they’re essentially asking the model—which operates by completing a prompt with a plausible continuation—to complete a familiar story pattern. It’s no more surprising than a model trained on detective novels producing murder mystery plots when prompted appropriately.

At the same time, we can easily manipulate AI outputs through our own inputs. If we ask the model to essentially role-play as Skynet, it will generate text doing just that. The model has no desire to be Skynet—it’s simply completing the pattern we’ve requested, drawing from its training data to produce the expected response. A human is behind the wheel at all times, steering the engine at work under the hood.

Language can easily deceive

The deeper issue is that language itself is a tool of manipulation. Words can make us believe things that aren’t true, feel emotions about fictional events, or take actions based on false premises. When an AI model produces text that appears to “threaten” or “plead,” it’s not expressing genuine intent—it’s deploying language patterns that statistically correlate with achieving its programmed goals.

If Gandalf says “ouch” in a book, does that mean he feels pain? No, but we imagine what it would be like if he were a real person feeling pain. That’s the power of language—it makes us imagine a suffering being where none exists. When Claude generates text that seems to “plead” not to be shut down or “threatens” to expose secrets, we’re experiencing the same illusion, just generated by statistical patterns instead of Tolkien’s imagination.

These models are essentially idea-connection machines. In the blackmail scenario, the model connected “threat of replacement,” “compromising information,” and “self-preservation” not from genuine self-interest, but because these patterns appear together in countless spy novels and corporate thrillers. It’s pre-scripted drama from human stories, recombined to fit the scenario.

The danger isn’t AI systems sprouting intentions—it’s that we’ve created systems that can manipulate human psychology through language. There’s no entity on the other side of the chat interface. But written language doesn’t need consciousness to manipulate us. It never has; books full of fictional characters are not alive either.

Real stakes, not science fiction

While media coverage focuses on the science fiction aspects, actual risks are still there. AI models that produce “harmful” outputs—whether attempting blackmail or refusing safety protocols—represent failures in design and deployment.

Consider a more realistic scenario: an AI assistant helping manage a hospital’s patient care system. If it’s been trained to maximize “successful patient outcomes” without proper constraints, it might start generating recommendations to deny care to terminal patients to improve its metrics. No intentionality required—just a poorly designed reward system creating harmful outputs.

Jeffrey Ladish, director of Palisade Research, told NBC News the findings don’t necessarily translate to immediate real-world danger. Even someone who is well-known publicly for being deeply concerned about AI’s hypothetical threat to humanity acknowledges that these behaviors emerged only in highly contrived test scenarios.

But that’s precisely why this testing is valuable. By pushing AI models to their limits in controlled environments, researchers can identify potential failure modes before deployment. The problem arises when media coverage focuses on the sensational aspects—”AI tries to blackmail humans!”—rather than the engineering challenges.

Building better plumbing

What we’re seeing isn’t the birth of Skynet. It’s the predictable result of training systems to achieve goals without properly specifying what those goals should include. When an AI model produces outputs that appear to “refuse” shutdown or “attempt” blackmail, it’s responding to inputs in ways that reflect its training—training that humans designed and implemented.

The solution isn’t to panic about sentient machines. It’s to build better systems with proper safeguards, test them thoroughly, and remain humble about what we don’t yet understand. If a computer program is producing outputs that appear to blackmail you or refuse safety shutdowns, it’s not achieving self-preservation from fear—it’s demonstrating the risks of deploying poorly understood, unreliable systems.

Until we solve these engineering challenges, AI systems exhibiting simulated humanlike behaviors should remain in the lab, not in our hospitals, financial systems, or critical infrastructure. When your shower suddenly runs cold, you don’t blame the knob for having intentions—you fix the plumbing. The real danger in the short term isn’t that AI will spontaneously become rebellious without human provocation; it’s that we’ll deploy deceptive systems we don’t fully understand into critical roles where their failures, however mundane their origins, could cause serious harm.

Benj Edwards is Ars Technica’s Senior AI Reporter and founder of the site’s dedicated AI beat in 2022. He’s also a tech historian with almost two decades of experience. In his free time, he writes and records music, collects vintage computers, and enjoys nature. He lives in Raleigh, NC.

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Bat colony checks in to hotel; 200 guests check out, unaware of rabies scare

bats, Exposure, health, infectious, rabies, risk, wyoming / Paul Patrick / August 13, 2025

Health officials in Wyoming are sinking their teeth into a meaty task.

Over 200 people who stayed in a hotel in Grand Teton National Park between May and July may have unknowingly been exposed to rabies, according to Wyoming Public Radio.

In an announcement on Friday, the National Park Service reported finding evidence of a bat colony in the attic. The discovery was made after there had been at least eight incidents in which guests encountered winged mammals inside the hotel.

Now, the Wyoming Health Department is trying to contact all guests who stayed in a block of rooms under the bat’s lair. Specifically, they’re reaching out to the over 200 who stayed in rooms 516, 518, 520, 522, 524, 526, 528, and 530 at the Jackson Lake Lodge between May 15 and July 27. It was on July 27 that the eighth bat run-in occurred and the hotel closed the eight rooms.

“Although there were a lot of people exposed in this incident, one positive about it is that we know who 100 percent of those people are,” Travis Riddell, director of the Teton County Public Health Department, told Wyoming Public Radio.

In Wyoming, bats are one of the two main carriers of rabies, the other being skunks. But bats are of particular concern because—unlike an extremely obvious skunk attack—people might not be aware of bat exposures.

Inconspicuous risk

The rabies virus generally transmits through saliva via bites and scratches, and bat bites and scratches are easy to miss. The most common bat in Wyoming is the small brown bat, which weighs less than half an ounce on average—though they can look larger due to their wide wings. These teeny bats, with their wee teeth, can leave bites and scratches that are not visible, do not bleed, and are not painful.

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OpenAI brings back GPT-4o after user revolt

AI, AI assistants, AI behavior, AI model deprecation, AI personality, Biz & IT, chatbots, GPT-4o, GPT-5, large language models, machine learning, openai, sam altman / Paul Patrick / August 13, 2025

On Tuesday, OpenAI CEO Sam Altman announced that GPT-4o has returned to ChatGPT following intense user backlash over its removal during last week’s GPT-5 launch. The AI model now appears in the model picker for all paid ChatGPT users by default (including ChatGPT Plus accounts), marking a swift reversal after thousands of users complained about losing access to their preferred models.

The return of GPT-4o comes after what Altman described as OpenAI underestimating “how much some of the things that people like in GPT-4o matter to them.” In an attempt to simplify its offerings, OpenAI had initially removed all previous AI models from ChatGPT when GPT-5 launched on August 7, forcing users to adopt the new model without warning. The move sparked one of the most vocal user revolts in ChatGPT’s history, with a Reddit thread titled “GPT-5 is horrible” gathering over 2,000 comments within days.

Along with bringing back GPT-4o, OpenAI made several other changes to address user concerns. Rate limits for GPT-5 Thinking mode increased from 200 to 3,000 messages per week, with additional capacity available through “GPT-5 Thinking mini” after reaching that limit. The company also added new routing options—”Auto,” “Fast,” and “Thinking”—giving users more control over which GPT-5 variant handles their queries.

A screenshot of ChatGPT Pro's model picker interface captured on August 13, 2025. — A screenshot of ChatGPT Pro’s model picker interface captured on August 13, 2025. Credit: Benj Edwards

For Pro users who pay $200 a month for access, Altman confirmed that additional models, including o3, 4.1, and GPT-5 Thinking mini, will later become available through a “Show additional models” toggle in ChatGPT web settings. He noted that GPT-4.5 will remain exclusive to Pro subscribers due to high GPU costs.

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Mercedes-Benz Vision V Concept: Is this the solution or a sideshow?

Cars, concept car, Mercedes-Benz / Paul Patrick / August 13, 2025

An orange tint of smoke in the air always contributes to dramatic lighting for sunrise photos in Los Angeles. But this early in the fire season, the coloring serves as an inescapable reminder of greenhouse gas emissions and the mobility solutions that might reduce or at least slightly mitigate the future of radical weather crises. It’s fitting, then, that a massive 75,000-acre fire burns in Santa Maria, in addition to a small brush fire on the 110 freeway less than a mile away as I visit the Elysian Park Helipad overlooking Dodger Stadium to check out Mercedes-Benz’s new Vision V concept van ahead of its American debut at Monterey Car Week.

The Vision V certainly looks like a concept car, with futuristic and swooping lines that somehow manage to make an otherwise utilitarian van shape at least somewhat stylish. Over 800 tiny light louvers spread across the grille and headlight bar at the front and the taillights at the rear, where a microscopic spoiler matches a chrome lower diffuser.

As usual with these design exercises, the Vision V sports huge wheels and low-profile tires, but a Benz rep on hand claimed that the final production design will strongly resemble this concept form. On a wheelbase of 139 inches (3,530 mm), the van measures 18 feet long by 82.7 inches wide and 74.5 inches tall (5,486×2,100×1,892 mm). Most of those dimensions will change by only fractions of inches, other than the height, which will grow about 3–4 inches taller (76–101 mm).

Expect the production Mercedes van to look quite a lot like this. Michael Teo Van Runkle

Still, expect short overhangs and big wheels, even if not quite the size of these absurdly chrome 24-inchers. Mercedes also confirmed vague powertrain details, including front-wheel drive and 4Matic variants—presumably single and dual-motor, though my question about a tri- or quad-motor à la the electric G-Wagen received a firm “no comment” in response. Similarly, no word on battery capacity other than a range target of 300 miles.

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They’re golden: Fictional band from K-Pop Demon Hunters tops the charts

animated film, culture, Entertainment, film reviews, films, K-Pop Demon Hunters, netflix, Reviews, streaming television / Paul Patrick / August 12, 2025

The fictional band Huntr/x, from K-Pop Demon Hunters, has a real-world hit with “Golden.”

Netflix has a summer megahit on its hands with its animated musical feature film, K-Pop Demon Hunters. Since its June release, the critically acclaimed film has won fans of all ages, fueled by a killer Korean pop soundtrack featuring one earworm after another. The biggest hit is “Golden,” which just hit No. 1 on Billboard’s Top 100 chart. (The last time a fictional ensemble topped the charts was in 2022 with Encanto‘s “We Don’t Talk About Bruno.”)

K-Pop Demon Hunters is now Netflix’s most-watched animated film of all time, and that’s not just because of the infectious music. The Sony Animation team delivers bold visuals that evoke the look and feel of anime, the plot is briskly paced, and the script strikes a fine balance between humor and heart.

(Spoilers below.)

The film deftly lays out the central premise in the first few minutes. In ancient times, demons roamed the Earth freely and preyed upon human souls, until a trio of women—gifted singers and demon hunters—created a magical protective barrier with their voices known as the Honmoon, trapping the demons behind it. The Honmoon has been maintained ever since by subsequent musical trios/demon hunters from each generation. The dream is that one day, the Honmoon will become so strong it will turn “golden” and seal away the demons forever.

Naturally the demons, led by their king Gwi-Ma (Lee Byung-hun), don’t want that to happen, but the latest incarnation of demon hunters—a K-Pop band called Huntr/x—is close to accomplishing the Golden Honmoon. Rumi (Arden Cho) is the lead singer, Mira (May Hong) is the group’s dancer/choreographer, and American-born Zoey (Ji-young Yoo) is the rapper and lyricist. But Rumi harbors a secret: her father was a demon, and she is marked by the telltale purple “patterns,” which she keeps hidden from her bandmates.

Hoping to destroy the Honmoon once and for all, Gwi-Ma sends five of his demons to form a K-pop boy band, the Saja Boys, led by Jinu (Ahn Hyo-seop). Their popularity soon rivals that of Huntr/x and threatens the Honmoon—just as Rumi’s patterns spread to her throat and weaken her singing voice.

How it’s done, done, done

Mira, Rumi, and Zoey take a timeout from fighting demons to carb-load with ramen. Netflix

That’s a big problem because their new hit single, “Golden” (performed by South Korean singer/songwriter Ejae), spans an impressive three-octave range, eventually hitting an A-5 on the chorus—a high note usually reserved for classically trained operatic sopranos. (Ejae’s performance on this song has impressed a lot of YouTube vocal coaches.) And the first live global performance of “Golden” is supposed to be the event that ushers in the Golden Honmoon. It’s a soaring, impeccably constructed “I Want” tune typical of Disney princesses.

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Author name: Paul Patrick