News
- OpenAI published the first Jalapeño benchmarks at Hot Chips, claiming 1.5 to 1.9x more throughput per kilowatt and up to 3.6x lower latency than Nvidia's GB200 and GB300 rack systems
- The chip's purported gains are at a reported 700W power draw and center around efficiency, with Nvidia's GB300 still leading on absolute throughput per package by 20-25 percent.
- The numbers are currently self-reported, and volume production of the chip is not expected to ramp up until 2027
OpenAI took the stage at Hot Chips on August 25 with the first published performance figures for Jalapeño, the inference accelerator it co-developed with Broadcom, and the numbers are designed to be read the way it flatters the former: efficiency.
The company reported 1.5 to 1.9 times more throughput per kilowatt and 1.7 to 3.6 times lower end-to-end latency across three open models than the Nvidia rack systems it tested against.
OpenAI's Jalapeño is currently rated at 700W, versus comparable Nvidia silicon that was rated for 1200W and 1400W, a key differentiator in a benchmark that already has limited information available to researchers looking to pick a clear winner.
AI efficiency takes center stage?OpenAI's Jalapeño is an ASIC, or an Application-specific integrated circuit, which essentially means that it focuses primarily on and is great for very specific AI workloads; in this case, OpenAI's inference needs, which allow it to run multiple models with significant efficiency gains in tow.
Richard Ho, who runs OpenAI's hardware program, told reporters on a press call that the results show "a very, very significant performance advance over state-of-the-art."
OpenAI ran SemiAnalysis's public InferenceX suite on GPT-OSS 120B, DeepSeek R1 670B, and Moonshot AI's trillion-parameter Kimi K2.5, at a nominal 8,000-token input and 1,000-token output. It scored a 1.9x efficiency win vs. GB200 on its own GPT-OSS model, and 1.7x and 1.5x on DeepSeek and Moonshot's offerings against a GB300 system. Interestingly, the figures for GPT-OSS 120B running on a GB300 compared to OpenAI's Jalapeño are not published.
It is important to point out here that there is a certain degree of cherry-picking to flatter OpenAI's own results: by choosing to compare ratios on a per-kilowatt basis versus a per-chip basis, while efficiency remains consistent, it does paint Jalapeño as potentially a much more potent competitor to Nvidia's last-generation offerings than it actually is.
Nvidia's GB300 might not have an efficiency win versus Jalapeño, but it remains a much more powerful chip in all tests, at a time when Nvidia is already rolling out Vera Rubin. Curiously, OpenAI has not published any information about how its chip stacks up against an HBM4-touting Vera Rubin, which Nvidia has presented as an efficiency juggernaut.
It is important to point out that Jalapeño's results also use single-token prediction throughout, with no speculative decoding and no prefill-decode disaggregation. Nvidia's production deployments commonly use multi-token prediction, and when OpenAI pits Jalapeño against a GB300 configured that way, the peak efficiency lead drops to roughly 1.5x.
OpenAI says it built the chip to keep model state local, writing that it "designed Jalapeño to minimize data movement and communication delays." Cores and HBM are divided into slices, each core slice holding a low-latency view of its own memory, with synchronization pushed onto a dedicated collective network. Each package pairs a compute die with six HBM4 stacks for 216 GiB at 15.4 TB/s, which is less capacity than the GB300's 288GB of HBM3E but considerably more bandwidth, and roughly 50 percent more memory per watt of rated power.
Every number published currently comes from A0 silicon, also known as the initial, first-run version of the chip. A more efficient B0 stepping is already in the fab with roughly 25 percent better performance per watt, and production is scheduled to ramp gradually across 2027.
Although it may not hold a candle to Nvidia's Vera Rubin, it might not have to; Alexander Harrowell of Omdia told CNBC that "this is the biggest competitive threat to NVIDIA," noting that roughly half of AI infrastructure capital spending comes from firms that already run custom chip programs or could. Yole Group's Adrien Sanchez framed it as pressure on Nvidia's inference margins specifically, the fastest-growing part of the business.
The timing of this announcement is both awkward and potentially suspect at a time when Nvidia just agreed to backstop $105 billion in financing for OpenAI's upcoming Ohio facility, even as Richard Ho told Bloomberg that the company continues to need a lot of Nvidia's chips, with the latter being "a really good partner." This is hardly surprising, given Jalapeño's limitations as an ASIC useful mainly for inference, while Nvidia's chips are key to training new AI models.
From Nvidia's perspective, this can be seen as a blow to its plans for a high-margin inference industry where one of the two major buyers of inference hardware is not only looking for a homegrown alternative, but is already well on its way to getting the job done.
- HUR identified 140 components linked to the upgraded Iskander missile system
- American manufacturers supplied 63 of the missile's identified electronic components
- Only one-quarter of all components came from Russian domestic manufacturers
Ukraine’s Defense Intelligence (HUR) has released details about foreign-made parts it says were found inside Russia’s upgraded Iskander-1000 ballistic missile.
The disclosure said American companies, including Xilinx, part of AMD, Atmel, part of Micron Technology, DM&P Electronics, Winbond Electronics, and Analog Devices, supplied critical parts for the missile's guidance and processing systems.
The agency also identified 140 components linked to the missile and said only a limited share came from Russian manufacturers.
Foreign chips remain inside Russia’s upgraded missile systemThe disclosure points to continued foreign technology use in a weapon system developed by Moscow despite efforts to reduce outside dependence.
According to Ukrainian intelligence, 35 companies are connected to the production network supporting Russia’s Iskander-M missile family.
The agency said the updated 9M723-2 variant, also called Iskander-1000, has appeared during recent attacks and forms part of the Bora-M missile system.
The newer missile version reportedly uses a larger engine and modified launcher design, allowing it to reach distances of up to 550km.
This compares with the 390km range attributed by Ukrainian intelligence to the earlier 9M723-1 missile model.
HUR stated that Russia continues to use imported electronic parts in key missile areas despite attempts to replace foreign technology with domestic alternatives.
The agency said only about one-quarter of the identified components were produced by Russian firms.
The intelligence report lists 63 components linked to manufacturers from the United States, while Switzerland and Belarus each account for eight components.
Germany and Taiwan were each linked to four parts, while China supplied three components according to the information released by HUR.
“The most critical components—microprocessors, FPGAs, memory, digital-to-analog and analog-to-digital converters—come from American and Taiwanese manufacturers…” said Ukraine’s Defense Intelligence.
The missile’s guidance system was described as one of the areas with significant foreign dependence.
HUR claims only five of 43 parts inside a flight information processing unit connected to the missile’s laser gyroscope were Russian-made.
Sanctions face challenges as supply chains remain complexThe identified components include field programmable gate arrays, memory chips, microprocessors and conversion devices used for handling digital and analogue signals.
Such parts are common in many electronic systems, making their movement across global markets difficult to monitor completely.
Ukraine’s intelligence service has called for stronger restrictions against companies, organizations and facilities it believes are linked to Russia’s missile production network.
The agency said international cooperation would be necessary to limit access to important technologies.
However, controlling the movement of advanced electronic components remains difficult because many parts have civilian uses and can pass through several countries before reaching final users.
The presence of international suppliers does not alone establish whether companies directly supply military programs.
The report comes as Ukraine continues efforts to disrupt Russia’s missile operations through sanctions pressure and attacks against launch equipment.
Ukrainian officials have also reported strikes against Russian missile launch platforms before they could be used.
“To counter the aggressor’s plans, it is important to consolidate efforts aimed at restricting Russia’s program for the development, production, and modernization of ballistic weapons,” HUR said.
Via United24media
Tineco is showcasing its latest smart home care technology under the theme “The Future Cleans Itself,” at IFA 2026, demonstrating how automation can simplify tasks before, during and after cleaning. For years, Tineco has developed smart home care products designed to make everyday cleaning simpler, and in 2020, the brand helped pioneer the floor washer category with the launch of the FLOOR ONE S1. Since then, Tineco has continued to push the category forward, earning recognition as the world’s No. 1 household wet & dry vacuum cleaner brand for four consecutive years.
Building on that evolution and leading Tineco’s floor care showcase at IFA 2026, is the Floor One Station S9 Scientist Pro which combines powerful cleaning performance with automated features designed to simplify operation and help keep the machine ready when you need it.
One of the key conveniences of the Tineco Floor One Station S9 Scientist Pro is the base station. While some vacuum cleaners can be a chore to use and put away, the base station helps streamline both the cleaning process and the steps that follow. It provides fast charging, keeping the Tineco Floor One Station S9 Scientist Pro powered up and ready for cleaning sessions of up to 100 minutes.
The station automatically replenishes hot water and dispenses cleaning solution, reducing the need for manual refilling during cleaning. The base station’s five-liter tank holds plenty of water for frequent cleaning, even in large homes.
After cleaning, the base station works with the floor washer to flush its roller and pipes and dry them with 230°F hot air in just five minutes. An integrated comb in the head of the Tineco Floor One Station S9 Scientist Pro helps cut out hair and detangles as you clean.
All of this cuts down on the manual upkeep needed before the next cleaning session.
The Tineco Floor One Station S9 Scientist Pro brings a full arsenal of cleaning capabilities to tackle the many messes that your floor might face. Its wide brush head and 25,000 Pa of suction can tackle dry debris with ease. Powered wheels, a swiveling neck and an edge-to-edge roller make it easy to navigate and clean along edges and baseboards. The Tineco Floor One Station S9 Scientist Pro can even lie flat to get under furniture as low as 4.33 inches.
For dried, sticky or oily messes, Hydro Burst Cleaning blasts the area with high-pressure water and cuts right through the mess. As you move the floor washer forward, it operates normally, rolling up debris, but with one click it can seamlessly drop a special scraper and move in reverse to more effectively pull up liquids and wipe away water for a streak-free finish.
The Floor One Station S9 Scientist Pro is just one part of Tineco’s broader showcase at IFA 2026. The brand is also unveiling the FLOOR ONE S11 Artist Fusion Steam, FLOOR ONE S9 Artist Boost Steam and PURE ONE STATION 7 ZeroTouch, all making their global debut at the event. Beyond these floor care launches, Tineco’s IFA presence spans floor washers, carpet cleaners, vacuum cleaners and smart kitchen products, with additional new products and technologies on display across the portfolio. Together, the lineup brings Tineco’s “The Future Cleans Itself” theme to life through technology designed to make everyday home care simpler.
*Source: Euromonitor International (Shanghai) Co., Ltd.; measured in terms of the brand’s global retail sales volume (in units) of household wet & dry vacuum cleaners in 2022, 2023, 2024, and 2025. Household wet & dry vacuum cleaners are defined as household cleaners that dispense clean water (or cleaning solution) to wash hard floors and vacuum the dirty water and debris thereafter. Based on research completed in March 2026.
- Lexar PexarBolt Ultra TBT5 Dock connects to a laptop through a single Thunderbolt 5 cable
- Bandwidth defaults to 80Gbps and boosts up to 120Gbps when needed
- Runs two 8K displays or three 4K panels simultaneously
Lexar has introduced a new docking station for Mac and Windows computers, called the PexarBolt Ultra TBT5 Dock, built around Thunderbolt 5 connectivity.
The dock combines 22 ports with a 5-inch touchscreen and a rotating metal dial to control connected displays and check system status.
The dock's Thunderbolt 5 connection is rated at up to 80 Gbps by default, with a boost mode that pushes that bandwidth to 120 Gbps in one direction.
A desk hub built around high-speed linksAccording to Lexar, the dock can handle two 8K displays at 60Hz or three 4K panels running at 144Hz, depending on host hardware.
Video output comes through Thunderbolt connections alongside DisplayPort 2.1 or HDMI 2.1, although those latter outputs share the same video path.
The unit also accepts Type B CFexpress, SD 4.0 and microSD 4.0 cards, giving camera users several ways to move footage.
An internal M.2 storage slot supports PCIe Gen 4 x2, with advertised transfer rates reaching 3,600 MB/s when suitable hardware is installed.
The storage drive is not included, so buyers would need to supply their own compatible SSD for that internal bay.
Network transfers can use 10GbE, while multiple USB ports provide connections for accessories, drives, phones, tablets and other desk equipment.
On the rear, this device has two slower USB-A ports, two faster USB-A ports, five USB-C sockets, audio, Ethernet, display outputs, and charging.
The front carries the camera card readers, a headphone socket, and two USB-C connections that share their 45W power allocation, though the power delivery reaches 140W for a connected laptop.
Its compatibility covers macOS and Windows, while the dock also works with Thunderbolt and USB4 devices when their supported features allow it.
A screen and cooling add more hardwareThe 5-inch display is intended to show information about connected equipment, power use, temperatures, transfer rates, and other operating details.
A rotary control beside the screen lets users move through interface options, while taps on the display provide access to additional information.
The company says full dashboard functions require its desktop application, making the screen less independent than a simple hardware status panel.
Active cooling combines a fan, metal heat transfer parts and directed airflow, with thermal information also shown through the display.
The package includes the dock, power supply, three regional AC leads, an SSD fitting kit, a Thunderbolt 5 cable and manual.
Lexar has not listed the NVMe drive as part of the package, despite making internal storage expansion one of the dock's main features.
The company is preparing the product for Kickstarter, where the advertised early price is $479 against a regular $649 MSRP.
Disclaimer: We do not recommend or endorse any crowdfunding project. All crowdfunding campaigns carry inherent risks, including the possibility of delays, changes, or non-delivery of products. Potential backers should carefully evaluate the details and proceed at their own discretion.
- Political action committees are funneling millions of dollars into candidates and adverts in an attempt to change perspectives on AI and data centers
- Numerous states have changed regulations on data centers, making them increasingly hard to gain approval for new projects
- The US economy is hinged upon the growth of AI companies, and opposition is costing money
A new breed of AI-aligned super political action committees (SuperPAC) is spending millions of dollars in an attempt to get pro-AI data center candidates elected in this year’s midterm elections.
Data centers have become a hot political topic with the majority of Americans preferring to have a nuclear reactor in their backyard rather than an AI data center. Americans are also increasingly concerned about AI and its effects on the job market, the environment, and their own health.
But these perspectives just don’t align with AI companies, who have seen unprecedented growth in their model’s capabilities and their stock value. For that growth to continue, perspectives on AI and the infrastructure behind it need to change.
Build data centers or become ‘backwards and poor’There are a few main players behind this movement. Leading The Future (LTF) has become a key funder behind pro-AI and pro-data center candidates, but also says it is using its millions to oppose those opposed to AI - as if the midterms weren’t already confusing enough.
But a new group, Build American AI, has emerged to run pro-AI and pro-data center ads in key battleground states of Kansas, Ohio, and Wisconsin. The Republican party recently issued a call for help from AI firms over AI opposition due to fears it could cost them the Ohio senate race.
If that were to be the case, it could lead to a wider change of floating voters aligning themselves with whoever is opposed to AI data centers.
Even Nvidia is jumping on the PAC train, having recently set up NVPAC to shape policy in its own favor. Nvidia has an enormous stake in AI technologies, given that it commands an enormous share of the hardware used in most AI data centers.
The Trump administration has aligned much of America’s politics around AI. To remain a global power ahead of China, AI cannot be slowed down. To remain on top of America’s battlefields at home and abroad, AI is being integrated into every arm of the military and all aspects of law enforcement. Opposition to AI is therefore opposition to America’s future, or so Trump would want you to believe.
The US economy is currently being buoyed by the surge in growth experienced by AI companies, but the models they are creating have been labelled not only a threat to financial institutions, but also a threat to financial stability of the world.
“The only reason that communities throughout the U.S.A. should not want Data Centers is if they want to end up being backwards and poor,” Trump wrote in a Truth Social post. “If they want to be successful and rich, with far lower taxes and jobs all over the place, let Data Reign.”
Trump’s referrals to taxes and jobs raise an interesting point, because numerous states have lost out on billions of tax revenue due to data center exemptions, and numerous studies have shown AI is leading to job losses in multiple industries.
There is also a large amount of infighting within the Republican Party surrounding support for data centers. Many representatives that previously pushed for data center construction - such as Texas Gov. Greg Abbott - have done a 180.
AI could therefore go from a revolutionary technology to one of the most divisive political issues of the Trump administration and beyond.
- SweepLED can spot hidden cameras by varying its illumination
- AI can detect camera lenses by the light that gets reflected back
- The accessory fits on the back of a camera and works in seconds
Unless you're in the safety of your own home, there's always a worry that you're being surveilled without your knowledge — when you're in an Airbnb, hotel room, changing room, or restroom, for example. Now researchers have developed an LED-powered phone accessory to give you some extra peace of mind.
It's called SweepLED, and it's the invention of a team from the Korea Advanced Institute of Science and Technology (KAIST). The portable device combines 15 LED lights, a cable to attach to your phone, and some AI processing.
According to the researchers, SweepLED can spot hidden cameras 94% of the time with a processing period of just five seconds per object. While this is only a prototype for now, the team has tested it on 30 different objects, reporting a high level of skill at identifying where hidden cameras are embedded (or not).
Here's how it works: SweepLED fixes to the back of a phone (over the camera). As video is recorded and the phone stays still, the add-on turns its LEDs on and off, comparing different reflection patterns against each other. Hidden camera lenses show up in those reflection patterns in a way that standard reflective surfaces don't.
Protecting your privacySweepLED uses reflection patterns to find cameras (Image credit: KAIST)"Hidden cameras pose a serious threat to personal safety and privacy in everyday spaces," says Professor Jun Han, from the KAIST team. "This research is meaningful in that it combines low-cost smartphone-based hardware with AI analysis to present the possibility of a practical detection technology that even non-experts can use."
Previous devices along these lines required users to look for 'bright spots' manually as they were lit up by the detector, the tell-tale sign that there was a camera looking back at them. This should be more efficient, and better at spotting different camera types hidden in a variety of different housings (like clocks or mirrors).
There's still plenty of work to do to get this refined and commercialized, but it shouldn't be expensive: the KAIST team reckons the manufacturing cost of SweepLED would be in the region of $7 (about £5 / AU$10).
If you do a lot of traveling, it might be worth investing in something like this just to make sure you're not being spied on. The work has been presented at the ACM MobiSys 2026 conference and published online, though as yet there's no indication of when it might be available to the masses.
- Roland has a new digital piano that has built-in Wi-Fi integration
- It's also launching a new music-learning app, Piano Sphere, with teaching techniques and real-time feedback
- As well as Wi-Fi, the piano has an upgraded speaker system with more accurate responsiveness
Music company Roland is taking a massive step with its latest project that’s pretty much unprecedented in the world of digital instruments — it's launching a portable piano with built-in Wi-Fi support.
The $750 (roughly £750/ AU$1,149) FP-40 digital piano was unveiled today (September 1), coming in two finishes (black or white) with Bluetooth Audio/ MIDI and USB-C connectivity. Though this isn’t new for digital instruments — many leading piano manufacturers make the most of Bluetooth — Wi-Fi integration is unheard of.
While that’s essentially the selling point, the FP-40 packs a punch with additional features like Roland’s Piano Reality Sound Engine, a technology that augments the finer details and tone of an acoustic piano. As for the keyboard, Roland uses weighted hammer-action keys, on top of the triple-sensor tech it uses to ensure faster responsiveness when playing notes.
Just like your smartphone, tablet, or laptop, the FP-40 piano connects to your home Wi-Fi like any other device, and it will receive regular software updates. But there's a reason why Roland has designed the new sound tool this way — it’s to spotlight its new learning software.
Alongside the launch of its Wi-Fi-powered piano, Roland is launching Piano Sphere, an app developed by Skoove that offers teaching techniques to help you improve your musical craft, whether you’re a casual player or you’re picking up the reins again.
(Image credit: Roland)Similar to learning apps like Duolingo, Piano Sphere is packed with ‘personalized guidance, real-time feedback, and a rich library of high-quality content to keep you playing’, as mentioned on the Roland site. In addition to this, you’ll also be getting step-by-step lessons and even custom learning plans based on your current level.
The only thing is that you’ll need a phone or tablet to view a lot of the software’s insights, for example, tracking progress by viewing streaks and reward badges, but outside of that, the piano itself has some handy features.
The FP-40’s flagship Piano Sphere button lights up to give you feedback as you play away, and thanks to Wi-Fi connectivity, the piano automatically records playing history even when the Piano Sphere app isn’t open. On top of that, you won’t need to pay extra for a Piano Sphere subscription.
From the get-go, you’ll have basic access to 100 copyright-free songs spanning everything from classical compositions to pop music bangers. If you feel that you’re ready to take the next step in mastering your skill, there’s an option to upgrade your Piano Sphere experience, which opens the doors to a library of over 1,000 songs and lessons.
Obviously, learning app integration with modern instruments isn’t a new thing — previous models allow you to pair third-party apps via Bluetooth — but the FP-40’s built-in Wi-Fi will result in a much smoother experience. Not only that, it could be a hint at the direction Roland plans to take its future musical innovations.
- Sygnia reports China‑linked Fire Ant expanding beyond virtualization to routers, TACACS, and Linux hosts
- Compromised routers act as operational platforms
- Campaign aims at “target behind the target,” leveraging trust relationships for broader espionage reach
Fire Ant, a China-nexus cyberespionage group, is no longer targeting just virtualization platforms, it’s also going for routers, authentication systems, and Linux management hosts. This is according to cybersecurity researchers Sygnia, who recently saw the group target Cisco IOS XR Routers.
Once they compromise a router, they don’t just use it to move around the network, the researchers explained. Instead, they turn them into full-blown operational platforms, collecting traffic, establishing connections, manipulating command output, and even suppressing logging so that they fly under the defenders’ radars.
For authentication systems, Fire Ant was seen taking aim at TACACS servers. Admins use them to authenticate when accessing network hardware, and crooks use them to harvest valuable credentials and weaken the reliability of audit logs, as well. Finally, Sygnia says Fire Ant also targets Linux management hosts. The researchers saw multiple persistent implants and backdoors, including a custom SSH backdoor and a piece of malware spoofing legitimate software.
Target behind the targetThe goal of the campaign seems to be to establish a foothold that allows crooks to reach other environments. Sygnia describes it as a “target behind the target” scenario:
“This reinforces the “target behind the target” concept introduced earlier in this report. Fire Ant’s interest in the compromised organization should be understood not only as an attempt to compromise a single environment, but as an effort to control infrastructure that may enable visibility, collection, and potential access beyond the immediate victim. The strategic value lies in the trust relationships the organization maintains with connected environments,” Sygnia explained.
Very little is known about Fire Ant, besides the fact that it was first observed in 2025. Some researchers claim it has significant overlaps with a threat actor tracked as UNC3886, a Chinese espionage group previously observed by Google. However, there are also significant differences which make attribution inconclusive.
Via BleepingComputer
- Nvidia's latest graphics driver has a frustrating bug
- Version 616.56 is causing distracting screen flickers and color corruption
- A patch is coming, and there are potential workarounds — but gamers are getting fed up with the prevalence of bugs in GeForce drivers
Nvidia's latest graphics driver is causing chaos for some GeForce GPU owners in the form of a glitch that makes the screen flicker.
Wccftech spotted the bug with Nvidia's Game Ready Driver version 616.56, and as flagged by Renan Maniero on X, Team Green has said it's testing a fix for the issue (as revealed on the GeForce forums).
The screen is reportedly flickering white or black and exhibiting other brief flashes of color corruption, and this is happening in certain games (The Last of Us and Minecraft are mentioned, among others) or on the Windows desktop. It's also occurring in web browser sessions and while playing YouTube videos, based on Reddit reports — of which there are plenty.
There's no shortage of gamers losing their temper with Nvidia, too, and blasting Team Green for the quality of its graphics drivers. Many are venting with an observation that GeForce drivers just haven't been the same since the launch of the RTX 5000 series.
For example, this Redditor says: "It's been particularly bad since Blackwell [RTX 5000] release. Just on Blackwell alone, between the whole DisplayPort 2.1 not working with HDR, screen flickering, and black screens on the initial release, it's been a complete mess."
Another gamer complains: "It is pretty shocking seeing this from a trillionaire company on a stable build. Nothing about this driver is stable."
Yet another Redditor grumbles: "It's crazy how things are now. You used to be able to update each time or be one driver behind at worst. Now I'm half a year outdated and thinking I'll just leave it."
Analysis: more drivers, more problems? There are possible workarounds thoughEven older GeForce graphics cards are affected here (Image credit: Future)This seems like quite a widespread issue and one that affects modern Nvidia graphics cards all the way back to RTX 2000 models.
If you're getting frustrated by this bug — random screen flickering gets pretty old, pretty fast, if it's happening regularly — Maniero also shared an apparent potential workaround on X that you can try while waiting for the official fix.
Seemingly, this is a bug that mostly affects monitors in 8-bit mode, and if you switch to 10-bit color (assuming your display supports this), the problem may disappear. Maniero also suggests that you try turning on Windows Auto Color Management (ACM).
Other folks on Reddit have shared various possible remedies, including switching from DisplayPort to an HDMI connector instead, and disabling Multi-Plane Overlay (MPO) in Windows 11, as one Redditor suggested. Nvidia provides a Registry file for turning off MPO (and enabling it again), but as ever with anything in this area of Windows, proceed at your own risk. (Although this method should be much safer than trying to edit the Registry directly yourself).
Your other choice is simply to roll back driver 616.56 to an earlier version, and there's no shortage of gamers who've done exactly that and report that the problem vanishes.
Hopefully Nvidia's official flicker-begone patch will be coming soon enough in the form of a hotfix, because this is an unduly annoying gremlin in the GeForce works that needs to be sorted out promptly.
- AI-shaped vocabulary is becoming harder to separate from ordinary human writing
- The analysis found a sevenfold rise in AI-associated vocabulary use
- Rewritten AI text can enter published research under human authorship
Fırat Mıhcı, a computational linguist and founder of HumanizeMy.ai, argues that AI can correct its own writing style until common detection signals disappear entirely.
The analysis claims that a second AI model can rewrite an original AI draft until identifying traits become far less visible to reviewers.
Once a human editor approves that rewritten draft, it gets published under a real name instead of being labelled as machine-generated.
A study of nearly 19,000 abstractsThe study behind this claim examined 18,989 abstracts spanning three separate academic fields, published across the years 2019 through 2026.
The analysis compares word frequency trends before and after the release of widely used AI writing tools in late 2022.
In computational linguistics, AI-associated word use rose from 1.9 to 14.0 instances per 10,000 words after late 2022, roughly a seven-times increase.
Neuroscience abstracts showed a similar pattern, climbing from 1.7 to 8.7 instances per 10,000 words, close to a five-times increase.
Mathematics abstracts barely changed, moving only from 0.9 to 1.3 instances, which researchers treated as a control group for comparison.
The study noted that overlapping confidence ranges in mathematics made the small increase statistically indistinguishable from no change at all over the full study period.
One tracked term, "delve," showed up in 2.75% of surveyed abstracts during 2024 before falling to just 0.12% within an incomplete 2026 data set.
A feedback loop that confuses detectorsMıhcı shared the findings as an open study meant to expose a blind spot in current AI detection methods used across many academic publishers today.
According to the study, this pattern creates a cycle in which AI wording gradually becomes accepted as ordinary human vocabulary.
Detection tools trained on older writing samples risk falsely flagging real authors whose natural vocabulary now resembles AI-generated text more closely than before.
AI tools trained on newer papers instead risk absorbing AI-influenced writing as a normal baseline, making future AI text harder to catch.
Words such as "intricate," "showcase," and "nuanced" were also tracked, alongside "underscore," a term commonly linked to AI-generated phrasing.
Editors and publishers reviewing these abstracts reportedly did not indicate that the wording carried any artificial origin before the manuscripts were accepted for publication.
"AI only needs its rewritten output to be accepted once as human. After that, the disguise becomes part of the answer key," said Fırat Mıhcı
The research does not claim every abstract containing these words was written by artificial intelligence rather than a human author.
It instead argues that AI-associated language has entered published writing in ways that make word-based detection increasingly unreliable over time.
Because the 2026 sample remains partial, the reported decline in words like "delve" may still shift once more data arrives.
If AI-shaped phrasing keeps entering the published record undetected, the very baseline used to define human writing may keep moving.
This pattern raises significant questions for any field relying on writing style alone to separate human output from machine output.