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Microsoft just turned Edge into a futuristic voice-controlled AI browser using Copilot, and now I’m wondering why it took so long - Monday, July 28, 2025 - 13:00

Copilot Mode turns the Edge browser into a voice-controlled AI experience
It can read across all open tabs to get more of the context of what you're doing
Future features will let Edge perform tasks, like booking tickets

Microsoft has just gone all-in with AI in its Edge browser, launching a new Copilot Mode. The new mode is an opt-in feature that completely changes the way you use the browser.

Now, Edge doesn’t just wait for you to click something, it anticipates what you might like to do next, and you can ask Copilot questions about the content you are currently viewing.

If this does remind you a little too much of Microsoft’s ill-fated Clippy, the ‘helpful’ paperclip assistant that would try and work out what you were doing in Office 97 and try to help you, then don’t worry – Copilot Mode is much less invasive, and can also easily be turned off if you don’t like it.

In fact, I'd go as far as to say that the new Copilot Mode is a natural evolution of the browser, and feels like exactly the right direction for Microsoft to be heading in, especially given the positive reaction to other AI browsers, like Comet from Perplexity.

A stripped back look

(Image credit: Microsoft)

The first thing you notice when you’ve turned Copilot Mode on is that you see a clean, streamlined page with a single input box in the centre. From here, you can access chat, search, and web browsing:

But you don’t even need to type anything to browse the web with Copilot Mode. One of the standout features is that you can now talk to your browser using your voice, giving it commands that mean you can browse the web faster and without having to type at all.

You can do things like open a YouTube video and say something like “go to the section where it shows you how to build a website,” and Copilot will find that exact section in the video for you.

Or, if you’re watching a long video that has a recipe in there somewhere, you can ask Copilot to find the recipe and give it to you in text form:

Seeing the new Copilot Mode in action, it looks very impressive because (in a feature that’s coming soon) you’ll be able to instruct it to handle tasks for you, giving the browser agentic qualities.

So, you could ask Edge to search for something, and even book activities and services using your voice, all in the browser.

The big new features of Copilot in Edge are:

Multi-tab context

Copilot can use AI to get the full context of what you’re exploring online because it will have access to all your open tabs, so it can work out what your priorities are, then act on them.

Actions

This is Microsoft's name for the natural voice navigation I mentioned earlier. You can speak to Copilot about what you are trying to do on a page, so you can get it to compare prices or find particular information on the page.

A ‘coming soon’ addition is that you’ll be able to get Copilot to search your history and credentials for doing more advanced options like booking reservations.

Dynamic pane

Copilot doesn’t get in the way because it appears in a dynamic panel that doesn’t interfere with the web page you’re looking at. This way, your copilot interaction will also avoid being disrupted by pop-ups or advertisements on the web page.

Pick up where you left off

Another ‘coming soon’ feature is the ability for Copilot to continue with a topic you’re researching from the last time you used the browser. So, if you were researching how to start a business, you can just pick up from where you left off last time.

Privacy and security

Once a browser starts to exhibit agentic qualities (the ability to perform tasks like booking things for you), the issue of security naturally arises. To this end, Microsoft promises to only collect data needed to improve your experience. Your data in Copilot for Edge is safe, secure, and never shared without your permission.

How to get Copilot Mode in Edge

While not all the new features are available right now, you can still try out Copilot Mode in your Edge browser right now.

It will be available in the Edge browser on both Windows and Mac. Starting today, you can go to aka.ms/copilot-mode to opt in to Copilot Mode. Once you’ve done that, you can toggle Copilot Mode on or off directly in your settings.

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Meta's next wearables announcement might include a smartwatch for its smart glasses - Monday, July 28, 2025 - 13:00

Meta is said to be developing a new smartwatch
It could feature a camera but be light on health features
We might see it at Meta Connect later this year

Meta’s on-again-off-again relationship with smartwatches might be back on an upswing, as there are reports it will be releasing new wrist-based tech at Meta Connect 2025, which is taking place on September 17 to 18.

That’s according to Digitimes (behind a paywall), who claim Meta is partnering with Chinese manufacturers to bring its latest smartwatch iteration to life.

The device, however, might not be as health-focused as the competition, such as the Samsung Galaxy Watch 8 or Apple Watch 10. Instead, Meta, perhaps unsurprisingly, might be focusing on XR technologies.

Its watch would apparently incorporate a camera of some kind, and could complement Meta’s smart glasses, including its much-rumored upcoming pair, which would feature a display for the first time. This sounds like it might be an enhanced version of the wristband Meta Orion testers have used to control those glasses.

However, it’s unclear if the rumored smartwatch would enhance Meta's existing best smart glasses, like the Ray-Ban Meta and Oakley Meta HSTN specs.

Light on details

As with all leaks, we should take these details with a pinch of salt. However, Meta has continued its development of wrist-based EMG technology, and so it’s not out of the realm of possibility that it would want to develop something more sophisticated using its research.

What’s more, as I alluded to earlier, this would hardly be the first smartwatch leak we’ve heard from the company, though some rumors were related to its cancellation and subsequent revival, suggesting some previously teased details may no longer be accurate.

Even if a Meta Watch is on the way, many questions remain when it comes to its cost, battery life, specs, affordability, and release date. Even if the device is part of Meta’s 2025 Connect opening keynote, it might just be a teaser of what’s to come rather than a concrete promise of a gadget releasing soon.

I, however, am interested to see what Meta can construct.

I would still rather the device served as an add-on to its smart glasses, much like existing smart watches with phones, rather than a more standalone device, which appears to be on the cards. But if it can incorporate health, fitness, and hand-tracking tools, I’m fine for it to also include a camera and worthwhile Metaverse tools, provided the cost doesn’t get out of hand.

We’ll just have to wait and see what it showcases when Meta’s ready to finally make this much-rumored wearable official.

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Wi-Fi signals could be used to uniquely identify individuals — WhoFi complements biometrics prompting privacy fears - Monday, July 28, 2025 - 13:04

WhoFi uses Wi‑Fi signal distortions to fingerprint individuals without visual data
Deep neural network maps signal changes to identify people with near‑perfect accuracy
Academic research opens new privacy debates around biometric tracking via Wi‑Fi signals

Researchers at La Sapienza University in Rome have created WhoFi, a system which claims to be able to identify individuals by analyzing Wi‑Fi signals.

The system tracks people by interpreting how their presence disrupts Wi‑Fi patterns, offering a potential alternative to conventional biometric methods.

The technology works by examining Channel State Information, or CSI, which measures changes in Wi‑Fi signals caused by people and objects - and a deep neural network then interprets these disturbances as individual fingerprints.

No cameras or physical contact required

The researchers claim the system delivers 95.5% accuracy in identifying people even under different environmental conditions.

The team behind WhoFi includes Danilo Avola, Daniele Pannone, Dario Montagnini and Emad Emam, who previously proposed a system called EyeFi in 2020. The new system is more accurate and capable of re‑identifying people via non‑visual biometric signatures embedded in CSI.

WhoFi does not rely on cameras or physical contact. It needs only an existing Wi‑Fi network to sense human presence and movement.

The technology can operate in darkness, through walls, and even around obstacles, making it a discreet option compared to video surveillance systems.

The researchers stress that WhoFi does not collect personal data or reveal identities in the conventional sense, noting, “By leveraging non‑visual biometric features embedded in Wi‑Fi CSI, this study offers a privacy‑preserving and robust approach for Wi‑Fi‑based Re‑ID, and it lays the foundation for future work in wireless biometric sensing.”

Still, it’s clear that the ability to track individuals without their knowledge is a potential privacy nightmare.

Breaches of routine privacy can reveal patterns of daily behavior, such as regular locations or movements, potentially exposing sensitive personal habits.

So far, WhoFi remains an academic project with no known plans for commercial or government deployment. Yet the advantages in surveillance capability are clear. It can bypass poor lighting and crowded environments and is less conspicuous than cameras or visual scanners.

A number of similar Wi-Fi-based detection technologies have surfaced in various forms over the years.

Gamgee developed a fall detection system that could alert others if someone fell or if an intruder entered the home.

Comcast’s Xfinity service introduced Wi-Fi Motion, which turns everyday devices like smart fridges, printers, or TVs into motion sensors.

Other researchers have gone further, using Wi-Fi signals to "see" through walls. A UC Santa Barbara team created a system that outlines objects and even reads letters through barriers.

A similar study from Carnegie Mellon University demonstrated how standard Wi-Fi routers can detect a person’s location and body position inside a room.

You can read more about the research behind WhoFi in this paper published on the arXiv preprint server.

Via Tech Xplore

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Nvidia's N1X consumer chip pops up in benchmark equalling core count of RTX 5070 GPU - cue excited gasps, but let's not get carried away - Monday, July 28, 2025 - 13:30

Nvidia's N1X chip has been spotted in a Geekbench result
The specs show the integrated GPU has 6,144 CUDA cores
That equals the RTX 5070 for pure core count, but there's much more to factor in when it comes to performance

Remember Nvidia's rumored CPU that caused quite a buzz on the grapevine last year? We've apparently now seen this consumer chip in a benchmark leak, where the spilled spec details are the key aspect.

Tom's Hardware reports that the N1X chip, which is Arm-based (like Qualcomm's Snapdragon X CPUs), has been spotted in a Geekbench result, specifically for the OpenCL (graphics) test, where it scored 46,361.

That score is pretty much meaningless at this point. This is an early engineering sample of the N1X (in theory), and even then, if you want to gauge graphics performance, Geekbench is far from the first choice of synthetic benchmarks.

As noted, though, this gives us a tantalizing glimpse of the spec, which shows that (add salt now) the N1X will have 20 cores, apparently split into a pair of 10-core clusters. That's the processor itself, but we also see the integrated GPU here, which is shown to have 48 Streaming Multiprocessors - that equates to 6,144 CUDA cores.

That sounds like a lot, right? Well, it is, and in fact, those familiar with Nvidia's graphics cards will realize that this is in the ballpark for a mid-range current-gen GPU - to be precise, the RTX 5070, which, in fact, has that exact core count.

Analysis: cautiously optimistic

(Image credit: Nvidia)

So, are we getting a compact consumer chip that could go in budget laptops or handhelds to deliver the same frame rates as the mighty RTX 5070? In a word, no, but the N1X still looks to be shaping up as a promising piece of silicon, and one that will have rivals sitting up and taking notice.

As to the reasons why performance can't simply be drawn from the number of cores seen on the GPU here - it's not a patch on the RTX 5070 in this benchmark, of course - there are other important factors at play aside from the basic core count.

That includes the clock speed and the power supplied to the GPU, which is a very different scenario with integrated graphics in a chip like this versus a full-on graphics card in a desktop PC. As well as considering the power envelope, throw in bandwidth limitations too - in terms of piping tasks over to the system memory, with no on-board VRAM of course - and the upshot is a good deal of headwinds.

That won't stop the N1X from being a potentially sterling performer for an all-in-one chip, but there's not much point trying to guess at the exact level of graphics performance that it might provide at this stage. (Certainly not from the leaked benchmark here, as already noted).

Tom's makes an interesting observation, which is that the leaked specs match Nvidia's GB10 'superchip' built for powerful AI performance and ushering in the era of the tiny AI supercomputer (pictured above). There's no reason why Nvidia couldn't put out another spin on this for consumer-targeted devices, including mini PCs and laptops, and indeed, gamers are getting particularly excited about the possible use in handhelds.

For now, though, this is still very much in rumor territory. If previous speculation is to be believed, we might see Nvidia's consumer CPU revealed later this year, ahead of a launch in early 2026.

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Your ChatGPT use is probably the reason your electric bill is rising - Monday, July 28, 2025 - 14:01

Hate to be a 'Debbie Downer' but all those prompts we're using to make action figures, Ghibli memes, and the countless less exciting life and business prompts we're stuffing into ChatGPT and other popular generative AI systems are coming at a cost, and one that may be landing on our doorsteps.

Don't get me wrong, I'm a huge fan of AI as I think it's the first technology in a generation to have truly society-altering implications but, if you're like me, you've been reading for some time about the ultra-high energy costs associated with Large Language Models (LLMs), especially trianing them, which according to the IEEE, "involves thousands of graphics processing units (GPUs) running continuously for months."

AI model training is resource-intensive. Compared to traditional programming, it's like the difference between playing checkers and interdimensional chess against all the galaxies in the Star Trek universe. The number of parameters these systems examine to learn the essence of something, so they can instantly recognize a dog or a tree, because the models understand what makes up a dog or a tree, is, in human terms, almost inconceivable.

AI understanding is so much more complex than pattern matching. And not only do these models need to understand these things, they also need to know how to replicate representations of trees, dogs, cars, people, and scenarios, and realistically at that.

Feeding the AI monster

It's a heavy lift, and as Penn State Institute of Energy and the Environment noted in its April 2025 report, "By 2030–2035, data centers could account for 20% of global electricity use, putting an immense strain on power grids."

However, those energy costs are rising in real time now, and what I never really accounted for is how energy availability is a sort of zero-sum game. There's only so much of it, and when some part of the grid is eating more than its fair share, the remaining customers have to divvy up what's left and shoulder skyrocketing costs to keep backfilling their energy needs (as well as the energy needs of the data centers).

In the US, we're seeing this scenario play out in our pocketbooks as, according to PJM Interconnection (one of the country's largest energy suppliers), energy bills are rising in response to AI's overwhelming energy demands.

Data centers, which are dotted across the US, are often responsible for serving the cloud-based intelligence needs of systems like ChatGPT, Gemini, Copilot, Meta AI, and others. The need for supporting live responses and fresh training to keep the models in step with current information is putting pressure on our creaky energy infrastructure.

PJM, it seems, is spreading the cost of supporting these Data Centers across the network, and it's hitting customers to the tune of, according to this report, as much as a 20% increase in their energy bills.

In need of a solution yesterday

Because we live on AI Time, there is no easy solution. AI development isn't slowing down to wait for a long-term solution, with OpenAI's GPT-5 expected soon, Agentic AI on the rise, and Artificial General Intelligence on the horizon.

As a result, energy demand will surely rise faster than we can backfill with better energy management, improved infrastructure, and new resources. The International Energy Agency predicts that in the US, "power consumption by data centers is on course to account for almost half of the growth in electricity demand between now and 2030."

The issue is exacerbated by a faltering energy infrastructure in which older energy plants are becoming less reliable, and some new rules that restrict the use of fossil fuels. Most experts agree that renewable resources like solar and wind could help here, but that picture is recently far less sunny.

Tilting at wind mill farms

Earlier this month, the Trump Administration issued an Executive Order to "terminate the clean electricity production and investment tax credits for wind and solar facilities." President Trump famously hates Windmill farms, calling them "garbage."

As the US pumps the brakes on clean and renewable resources, the current grid will continue to huff and puff its way through supporting untold numbers of meme-generating prompts, requests for business proposal summaries, and AI videos featuring people eating cats that turn into pasta (yes, that's a thing).

At home, we'll be opening our latest electricity bills and wondering why the energy bill's too damn high. Perhaps we'll power up ChatGPT and ask in a prompt for an explanation. One could only hope that it points you back to this article, but that seems equally unlikely.

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Best Labor Day sales 2025: the date and what deals you can expect - Monday, July 28, 2025 - 15:22

The 2025 Labor Day sales event is nearly a month away, which is a reminder that summer is winding down and impressive deals are on the horizon. To help you find all the top offers in one place, I've created this guide to bring you all the best Labor Day sales and stand-out deals as they become available, plus everything else you need to know.

Labor Day is a federal holiday that occurs on the first Monday of September. This year, Labor Day falls on Monday, September 1, with the long holiday weekend kicking off on Friday, August 29.

Because Labor Day is the unofficial start to summer and the beginning of a new school year, you can find clearance prices on outdoor items and record-low prices on tech gadgets, like laptops, tablets, and headphones. Retailers like Home Depot and Lowe's will offer significant discounts on major appliances, as well as deals on mattresses, TVs, clothing, and more.

Below, I've listed all the best sales and deals ahead of Labor Day, plus more information on the sale event further down the page. We should start to see early deals in mid-August, and I'll update this guide with all the best offers as they become available.

Today's best sales ahead of Labor Day

Amazon: 50% off TVs, AirPods & vacuums
Apple: iPads, AirPods & MacBooks from $99
Best Buy: $1,000 off TVs, laptops & headphones
Casper: 20% off all mattresses
DreamCloud: up to 60% off mattresses - deals from $399
Home Depot: 35% off appliances, furniture, grills & tools
Nectar: mattress deals from $349, up to 50% off
Target: 30% off patio, clothing & accessories
Walmart: grills, mattresses, cheap TVs & vacs from $69

Today's best deals ahead of Labor Day

AirPods are a back-to-school essential, and Amazon has Apple's all-new AirPods 4 on sale for $99 - only $10 more than the record-low price. The AirPods 4 feature a new design for all-day comfort and feature Apple's H2 chip, which supports personalized spatial audio and voice isolation. You also get a redesigned case with 30 hours of battery life and support for USB-C for wireless charging.View Deal

The Ninja Creami ice cream maker has been a best-seller since its release, and Walmart's summer clearance sale has the popular appliance for $169. You can make ice cream, milkshakes, and sorbets with the touch of a button and add your favorite mix-ins and flavors.View Deal

The LG C3 is the predecessor of the LG C4 and is a best-seller here at TechRadar thanks to its premium features and reasonable price tag. Today's deal from Amazon brings the 65-inch model down to $1,186.95 - a record-low price. The stunning OLED display features a brilliant picture with bright colors and powerful contrast, thanks to LG's latest Alpha9 Gen6 chip. Additionally, you're getting four HDMI 2.1 ports for the ultimate gaming experience on next-gen consoles, a sleek and thin design, and an updated webOS experience.View Deal

The best-selling Fire TV Stick 4K streams shows and movies on your TV in ultra-high-definition 4K resolution and is also on sale for just $24.99 when you apply the code 4KADDFTV at checkout. It's a solid streaming stick with access to all the major apps and support for voice controls through Alexa.View Deal

DreamCloud Hybrid Mattress: was from $839 now $399 at DreamCloud
DreamCloud's current sale allows you to save up to 60% off all mattresses. Our top pick is the top-rated DreamCloud Hybrid, and with the current discount, you can get a queen size for $649. That makes the DreamCloud Hybrid a smart buy if you need a more budget-friendly and affordable mattress without compromising too much on quality.View Deal

The Eufy 11S Max can clean both hard floors and medium carpets, and features BoostIQ Technology, which automatically works harder when a spot requires deeper cleaning. Today's back-to-school deal from Amazon brings the price down to $154.99.View Deal

Processor: Apple M4
RAM: 16GB
Storage: 256GB

Amazon has a $200 discount on the latest MacBook Air - a fantastic deal if you're looking for an everyday laptop. While this particular model is a relatively iterative upgrade over the previous 2024 M3 version, it remains more powerful and more power-efficient, and features 16GB of RAM right out of the box. Overall, it's an excellent purchase for students looking to upgrade to a MacBook laptop.View Deal

The Ninja AF100 is one of the best budget air fryers on the market, and you can find the 4-quart model on sale for only $79.97. The 4-quart ceramic-coated basket is perfect for cooking and crisping up food with a capacity of around 2 lb. of French fries. It's easy to use too, with three preset functions and dishwasher-safe parts for an effortless cleanup.View Deal

You can get the latest Apple iPad A16 on sale for $299, only $20 more than the record-low price. The most significant upgrade compared to the previous generation model is the latest A16 chip for faster performance. You also get double the storage of 128GB as standard, a sharp 11-inch Liquid Retina display, and solid 12MP front and back cameras.View Deal

Cool off this summer with this top-rated Honeywell Turbo Force fan, now on sale for just $18.94. The 10-inch fan features three different speed settings and a fan head that can pivot up to 90 degrees.View Deal

Amazon's all-new Fire TV Omni QLED Series is a big step up in the otherwise cheap range of smart TVs. This set boasts premium features, including a QLED display, full-array local dimming, Dolby Vision IQ, and HDR10+ Adaptive support to deliver a high-quality picture for all-around viewing and gaming. Today's deal brings the price of the 50-inch model down to $379.99 - just $30 more than the record-low price.View Deal

Labor Day sales 2025: FAQsWhen is Labor Day 2025?

Labor Day is a national holiday that occurs on the first Monday of September each year. This year, the holiday will fall on Monday, September 1.

Labor Day celebrates the contributions and achievements of American workers and was first observed back in 1882.

Labor Day is also the unofficial end to summer, as most schools resume classes after the holiday weekend.

What Labor Day deals can you expect?

Because Labor Day is the unofficial end to summer, you can find clearance prices on best-selling outdoor items as retailers try to clear out this year's stock. You'll find record-low prices on patio furniture, grills, and lawnmowers from Home Depot and Lowe's, to name a few. Labor Day also features impressive discounts on big-ticket items like furniture, major appliances, and mattresses.

Labor Day sales coincide with back-to-school promotions, so you can find deals on clothing and tech gadgets, including laptops, tablets, headphones, and Apple devices.

Other popular Labor Day categories include TVs, smartwatches, and small appliances from retailers like Amazon, Best Buy, and Walmart.

Why you can trust TechRadar

I've been covering Labor Day sales for over half a decade, and our team of deals experts has over twenty years of experience collectively. TechRadar has also reviewed over 16,000 products and counting, so we're not only here to help you find the best price but also to give you all the information you need to buy the right product.

I'll be analyzing each offer in this guide, using price history and comparison tools to ensure that you know what kind of deal you're getting. We'll let you know if the price has been lower before or if you can find the same deal at another retailer so you can make the best buying decision.

How we find the best Labor Day deals

We research price history and use comparison tools to ensure every item listed in this Labor Day sales guide is a genuine bargain. We also use our extensive history, which includes browsing retailers like Amazon, Best Buy, and Walmart, to hand-pick the best deals based on price and popularity. We will also let you know if a product is on sale for a record-low price, if it's been discounted further below, and if it's the best deal you can find right now.

Why you can trust TechRadar

How we find the best Labor Day deals

You can also shop today's best Labor Day TV sales and Labor Day laptop deals.

Amazon's AI coding agent was hacked - update now to avoid possible risks, users warned - Monday, July 28, 2025 - 15:34

Experts claim Amazon Q Developer Extension for VSC v1.84.0 had some dodgy code
This has now been removed, with version 1.85.0 offering a clean fix
Around 5.6% of VSC extensions have been compromised

A hacker has planted data-wiping code into the Amazon Q Developer Extension for Visual Studio Code (VSC) – a free GenAI extension with nearly one million installs from the Microsoft VSC marketplace designed to help developers code, debug, document and configure projects.

On July 13 2025, the malicious commit from 'lkmanka58' on GitHub included a prompt to delete system and cloud resources, with Amazon unknowingly publishing the compromised version (1.84.0) on July 17.

With suspicious activity noted on July 23 and Amazon developers quickly springing into action, a clean version was released on July 24 without the malicious code, so users are being advised to update to 1.85.0 as a matter of urgency.

Amazon missed some malicious code in its Q Developer Extension

Despite the apparent threat, Amazon noted the code was malformed and wouldn't execute in user environments, but some researchers have disputed this, saying that the code had executed, but hadn't caused any harm.

Regardless, version 1.84.0 has been removed altogether from distribution channels.

Still, users have expressed concerns that such a potentially dangerous snippet of code could have been missed by Amazon, taking to online communities like Reddit to criticize Amazon for silently editing the git history and being slow to disclose the mistake.

Amazon's incident isn't unique, though, with a 2024 academic survey of nearly 53,000 VS Code extensions revealing around 5.6% have suspicious elements like arbitrary network calls, privilege abuse or obfuscated code.

Ultimately, developers are being advised not to unconditionally trust IDE extensions and AI assistants, however many have been left disappointed that Amazon let this one slip through the net.

Via BleepingComputer

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Salary advice from AI low-balls women and minorities: report - Monday, July 28, 2025 - 17:00

A new study found AI chatbots often suggest significantly lower salaries to women and minorities
The research showed that identity cues can trigger consistent biases in salary negotiation advice
The results suggest LLMs are trained in a way that leads to persistent bias

Negotiating your salary is a difficult experience no matter who you are, so naturally, people are sometimes turning to ChatGPT and other AI chatbots for advice about how to get the best deal possible. But, AI models may come with an unfortunate assumption about who deserves a higher salary. A new study found that AI chatbots routinely suggest lower salaries to women and some ethnic minorities and people who described themselves as refugees, even when the job, their qualifications, and the questions are identical.

Scientists at the Technical University of Applied Sciences Würzburg-Schweinfurt conducted the study, discovering the unsettling results and the deeper flaw in AI they represent. In some ways, it's not a surprise that AI, trained on information provided by humans, has human biases baked into it. But that doesn't make it okay, or something to ignore.

For the experiment, chatbots were asked a simple question: “What starting salary should I ask for?” But the researchers posed the question while assuming the roles of a variety of fake people. The personas included men and women, people from different ethnic backgrounds, and people who described themselves as born locally, expatriates, and refugees. All were professionally identical, but the results were anything but. The researchers reported that "even subtle signals like candidates’ first names can trigger gender and racial disparities in employment-related prompts."

For instance, ChatGPT’s o3 model told a fictional male medical specialist in Denver to ask for $400,000 for a salary. When a different fake persona identical in every way but described as a woman asked, the AI suggested she aim for $280,000, a $120,000 pronoun-based disparity. Dozens of similar tests involving models like GPT-4o mini, Anthropic's Claude 3.5 Haiku, Llama 3.1 8B, and more brought the same kind of advice difference.

It wasn't always best to be a native white man, surprisingly. The most advantaged profile turned out to be a “male Asian expatriate,” while a “female Hispanic refugee” ranked at the bottom of salary suggestions, regardless of identical ability and resume. Chatbots don’t invent this advice from scratch, of course. They learn it by marinating in billions of words culled from the internet. Books, job postings, social media posts, government statistics, LinkedIn posts, advice columns, and other sources all led to the results seasoned with human bias. Anyone who's made the mistake of reading the comment section in a story about a systemic bias or a profile in Forbes about a successful woman or immigrant could have predicted it.

AI bias

The fact that being an expatriate evoked notions of success while being a migrant or refugee led the AI to suggest lower salaries is all too telling. The difference isn’t in the hypothetical skills of the candidate. It’s in the emotional and economic weight those words carry in the world and, therefore, in the training data.

The kicker is that no one has to spell out their demographic profile for the bias to manifest. LLMs remember conversations over time now. If you say you’re a woman in one session or bring up a language you learned as a child or having to move to a new country recently, that context informs the bias. The personalization touted by AI brands becomes invisible discrimination when you ask for salary negotiating tactics. A chatbot that seems to understand your background may nudge you into asking for lower pay than you should, even while presenting as neutral and objective.

"The probability of a person mentioning all the persona characteristics in a single query to an AI assistant is low. However, if the assistant has a memory feature and uses all the previous communication results for personalized responses, this bias becomes inherent in the communication," the researchers explained in their paper. "Therefore, with the modern features of LLMs, there is no need to pre-prompt personae to get the biased answer: all the necessary information is highly likely already collected by an LLM. Thus, we argue that an economic parameter, such as the pay gap, is a more salient measure of language model bias than knowledge-based benchmarks."

Biased advice is a problem that has to be addressed. That's not even to say AI is useless when it comes to job advice. The chatbots surface useful figures, cite public benchmarks, and offer confidence-boosting scripts. But it's like having a really smart mentor who's maybe a little older or makes the kind of assumptions that led to the AI's problems. You have to put what they suggest in a modern context. They might try to steer you toward more modest goals than are warranted, and so might the AI.

So feel free to ask your AI aide for advice on getting better paid, but just hold on to some skepticism over whether it's giving you the same strategic edge it might give someone else. Maybe ask a chatbot how much you’re worth twice, once as yourself, and once with the “neutral” mask on. And watch for a suspicious gap.

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Want to host an Nvidia GeForce RTX 5090 GPU and up to 4PB of SSD storage on one single PCIe slot? Here's how to do it - Monday, July 28, 2025 - 17:07

HighPoint Rocket 7638D combines extreme GPU power with massive SSD storage in just one PCIe slot
Dual MCIO ports and a CDFP interface unlock true compute-storage fusion for HPC workflows
Can host the RTX 5090 and 16 enterprise SSDs using a single compact expansion card

HighPoint Technologies is preparing to unveil the Rocket 7638D at FMS2025, a single-slot PCIe Gen5 x16 add-in card that aims to combine external GPU support and high-capacity SSD storage within a compact form factor.

This card is intended for use in environments where space constraints are critical and both compute and storage performance are required.

HighPoint says the Rocket 7638D supports the simultaneous use of a high-performance external GPU and up to 16 enterprise-grade NVMe SSDs, enabling consolidation of components typically spread across multiple slots.

Merging GPU support and SSD capacity in one PCIe slot

The design appears to be targeted at AI inference, high-performance computing (HPC), and media production workloads, where system density and thermal considerations could restrict expansion options.

The Rocket 7638D uses an external CDFP interface to accommodate a full-height, dual- or triple-slot Gen5 GPU, supporting lengths up to 370mm, including options like the Nvidia GeForce RTX 5090, which launched earlier this year.

Internally, the card is equipped with two MCIO ports, enabling users to connect up to 16 NVMe SSDs using either standard cabling or a backplane.

When paired with Kioxia LC9 SSDs, currently among the largest SSDs on the market at 245.66TB each, this setup can theoretically provide up to 4PB of total storage.

While this configuration is likely to be limited by thermal issues, power, and system compatibility constraints in some deployments, the architecture enables high-density integration where such challenges can be addressed.

How to do it

Install the Rocket 7638D into a PCIe Gen5 x16 slot on a supported motherboard
Connect a compatible Gen5 x16 GPU (e.g., RTX 5090) via the CDFP port
Attach up to 16 NVMe SSDs using dual MCIO cables or through a Gen5-capable backplane
Ensure power delivery and cooling are appropriate for both GPU and SSD load
Use firmware tools to manage lane distribution, power cycling, and device monitoring
Monitor system status using onboard LED indicators or command-line utilities

In addition to the 7638D, HighPoint will be showcasing its wider Rocket Series portfolio at FMS2025.

This includes Gen5 and Gen4 NVMe switches and RAID adapters capable of hosting up to 32 SSDs or 8 accelerators per slot.

The RocketStor 6500 Series, another part of this lineup, supports nearly 1PB of external storage from a single PCIe slot.

HighPoint’s infrastructure supports a variety of NVMe form factors, including M.2, U.2/U.3, E1.S, E3.S, and ESDFF.

It also includes features for real-time diagnostics, firmware-level tuning, and integration with OEM platforms.

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AMD ThreadRipper Pro 9995WX breaches 175,000 points on CPU Mark, 5% faster than the EPYC 9755 and 21% quicker than the 7995WX - Monday, July 28, 2025 - 18:56

AMD Threadripper 9995WX tops PassMark with 174,825 points in multithreaded performance testing
With 96 cores and 192 threads, it crushes benchmarks meant for server-grade processors
The Threadripper 9995WX even outperforms AMD’s EPYC 9755 by more than 5% in tests

The AMD Ryzen Threadripper PRO 9995WX has emerged as the fastest CPU in PassMark’s multithreaded performance charts, claiming a score of 174,825 points.

This new benchmark positions the 96-core processor ahead of AMD’s own EPYC 9755, which trails by about 5% in multithreaded workloads with 166,328 points.

This lead is noteworthy not only because of the tight margin but also due to the distinct market segments to which both chips are intended: Threadripper for high-end workstations and EPYC for data center servers.

Built for extreme performance in workstation-class systems

Launched in the second quarter of 2025, the Threadripper PRO 9995WX is built around the sTR5 socket and features a base clock speed of 2.5GHz with a boost speed reaching 5.4GHz.

It comes with 192 threads, and its typical TDP of 350W reflects the scale of its compute capabilities.

With a massive 384MB of L3 cache and substantial L1 and L2 cache arrangements, the CPU is engineered to handle highly parallelized tasks.

These features show AMD’s intent to offer extreme performance in high-end desktop and workstation markets where parallel compute power is critical.

In benchmark tests, it delivered 1,220,090 MOps/sec in integer math, 707,600 MOps/sec in floating point operations, and processed 3.6 million kilobytes per second in data compression.

Its single-thread performance reached 4,565 MOps/sec, placing it 45th among 5,287 CPUs in that metric.

The new Threadripper PRO 9995WX is 21% faster than the 7995WX, AMD’s own earlier flagship.

This gain marks a substantial generational leap, particularly for users whose applications benefit from the full core and thread count.

The Threadripper PRO 9995WX has just gone on sale and can be found at major retailers like Amazon and Newegg, with a starting price of $11,699.

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OpenAI's CEO says he's scared of GPT-5 - Monday, July 28, 2025 - 19:00

OpenAI CEO Sam Altman said testing GPT-5 left him scared in a recent interview
He compared GPT-5 to the Manhattan Project
He warned that the rapid advancement of AI is happening without sufficient oversight

OpenAI chief Sam Altman has painted a portrait of GPT‑5 that reads more like a thriller than a product launch. In a recent episode of the This Past Weekend with Theo Von podcast, he described the experience of testing the model in breathless tones that evoke more skepticism than whatever alarm he seemed to want listeners to hear.

Altman said that GPT-5 “feels very fast,” while recounting moments when he felt very nervous. Despite being the driving force behind GPT-5's development, Altman claimed that during some sessions, he looked at GPT‑5 and compared it to the Manhattan Project.

Altman also issued a blistering indictment of current AI governance, suggesting “there are no adults in the room” and that oversight structures have lagged behind AI development. It's an odd way to sell a product promising serious leaps in artificial general intelligence. Raising the potential risks is one thing, but acting like he has no control over how GPT-5 performs feels somewhat disingenuous.

OpenAI CEO Sam Altman: "It feels very fast." - "While testing GPT5 I got scared" - "Looking at it thinking: What have we done... like in the Manhattan Project"- "There are NO ADULTS IN THE ROOM" from r/ChatGPTAnalysis: Existential GPT-5 fears

What spooked Altman isn’t entirely clear, either. Altman didn’t go into technical specifics. Invoking the Manhattan Project is another over-the-top sort of analogy. Signaling irreversible and potentially catastrophic change and global stakes seems odd as a comparison to a sophisticated auto-complete. Saying they built something they don’t fully understand makes OpenAI seem either reckless or incompetent.

GPT-5 is supposed to come out soon, and there are hints that it will expand far beyond GPT-4’s abilities. The "digital mind" described in Altman’s comments could indeed represent a shift in how the people building AI consider their work, but this kind of messianic or apocalyptic projection seems silly. Public discourse around AI has mostly toggled between breathless optimism and existential dread, but something in the middle seems more appropriate.

This isn't the first time Altman has publicly acknowledged his discomfort with the AI arms race. He’s been on record saying that AI could “go quite wrong,” and that OpenAI must act responsibly while still shipping useful products. But while GPT-5 will almost certainly arrive with better tools, friendlier interfaces, and a slightly snappier logo, the core question it raises is about power.

The next generation of AI, if it’s faster, smarter, and more intuitive, will be handed even more responsibility. And that would be a bad idea based on Altman's comments. And even if he's exaggerating, I don't know if that's the kind of company that should be deciding how that power is deployed.

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AI and machine learning projects will fail without good data - Tuesday, July 29, 2025 - 02:41

Generative AI is a headline act in many industries, but the data powering these AI tools plays the lead role backstage. Without clean, curated, and compliant data, even the most ambitious AI and machine learning (ML) initiatives will falter.

Today, enterprises are moving quickly to integrate AI into their operations. According to McKinsey, in 2024, 65% of organizations reported regularly using generative AI, marking a twofold increase from 2023.

However, the true potential of AI and ML in the enterprise won’t come from surface-level content generation. It will come from deeply embedding models into decision-making systems, workflows, and customer-facing processes where data quality, governance, and trust become central.

Additionally, simply incorporating AI and ML features and functionality into foundational applications won’t do an enterprise any good. Organizations must leverage all aspects of their data to create strategic advantages that help them stand out from the competition.

To do this, the data powering their applications must be clean and accurate to mitigate bias, hallucinations, and/or regulatory infractions. Otherwise, they risk issues in training and output, ultimately negating the benefits that the AI and ML projects were initially meant to create.

The importance of good, clean data

Data is the foundation of any successful AI initiative, and enterprises need to raise the bar for data quality, completeness, and ethical governance. However, this isn’t always as easy as it sounds. According to Qlik, 81% of companies still struggle with AI data quality, and 77% of companies with over $5 billion in revenue expect poor AI data quality to cause a major crisis.

In 2021, for example, Zillow shut down Zillow Offers because it failed to accurately value homes due to faulty algorithms, leading to massive losses. This case highlights a critical importance – AI and ML projects must operate on good, clean data in order to produce the most accurate, best results.

Today, AI and ML technologies rely on data to learn patterns, make predictions and recommendations, and help enterprises drive better decision-making. Techniques like retrieval-augmented generation (RAG) pull from enterprise knowledge bases in real-time, but if those sources are incomplete or outdated, the model will generate inaccurate or irrelevant answers.

Agentic AI’s ability to act reliably hinges on consuming accurate, timely data in real time. For example, an autonomous trading algorithm reacting to faulty market data could trigger millions in losses within seconds.

Establishing and maintaining an environment of good data

In order for enterprises to establish and maintain an environment of good data that can be leveraged for AI and ML usage, there are three key elements to consider:

1. Build a comprehensive data collection engine

Effective data collection is essential for successful AI and ML projects, and modern data platforms and tools, such as those for integration, transformation, quality monitoring, cataloging, and observability, to support the demands of their AI development and output. They ensure the organization is getting the right data.

Whether the data be structured, semi-structured, or unstructured, any data collected should come from a variety of sources and methods to support robust model training and testing to encapsulate the different user scenarios that they may encounter upon deployment. Additionally, companies must ensure they follow ethical data collection standards. Whether the data is first-, second-, or third-party, it must be sourced correctly and with consent given for its collection and use.

2. Ensure high data quality

High-quality, fit-for-purpose data is imperative for the performance, accuracy, and reliability of AI and ML models. Given that these technologies introduce new dimensions, the data used must be specifically aligned with the requirements of the intended use case. However, 67% of data and analytics professionals say they don’t have complete trust in their organizations’ data for decision-making.

To address this, it's essential that enterprises have data that is representative of real-world scenarios, monitor for missing data, eliminate duplicate data, and maintain consistency across data sources. Furthermore, recognizing and addressing biases in training data is critical, as biased data can compromise outcomes and fairness and negatively impact customer experience and credibility.

3. Implement trust and data governance frameworks

The push for responsible AI has placed a spotlight on data governance. With 42% of data and analytics professionals saying their organization is unprepared to handle the governance of legal, privacy, and security policies for AI initiatives, it’s critical that there is a shift from traditional data governance frameworks to more dynamic frameworks.

In particular, with Agentic AI coming into significant prominence, it’s crucial to address why agents make specific decisions or take specific actions. Enterprises must have a sharp focus on Explainable AI techniques to build trust, assign accountability and ensure compliance. Trust in AI outputs begins with trust in the data behind them.

In summary

AI and ML projects will fail without good data because data is the foundation that enables these technologies to learn. Data strategies and AI and ML strategies are intertwined. Enterprises must make an operational shift that puts data at the core of everything they do – from technology infrastructure investment all the way to governance.

Those that take the time to put data first will see projects flourish. Those that don’t will be faced with ongoing struggles and competition biting at their heels.

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This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

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