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• Scaleout's onboard AI let a BAE Systems ALMA drone rank, select, and strike an armored engineering vehicle in a January 2026 demo
• Humans set the mission, started the system, and kept a pilot in reserve, but did not ultimately use them during the test
• The test underscores how small AI models can essentially take over not only the target-selection part of the equation, but also perform the actual mission end-to-end without human intervention needed

A small drone flying over a snow-covered Swedish test range in January 2026 found several objects, ranked an armored engineering vehicle as the most valuable, and made a beeline for it before dropping an explosive.

There was no human involvement in the entire process, which included selection, targeting, and then neutralization by the drone, making it a considerably more autonomous approach than what the current battlefield uses.

The flight, part of BAE Systems Bofors' Affordable Loitering Modular Ammunition (ALMA) program with onboard AI supplied by Uppsala-based Scaleout Systems, resurfaced this month as AI safety became a key topic among industry and government stakeholders alike.

A growing threat and capability for modern militaries

Scaleout Systems tested the AI in question with a pilot on standby and a continuous connection throughout the exercise, during which the drone used AI to detect, identify, and geolocate potential threats.

Depending on how you frame it, you can argue that this is both a threat to modern militaries and a boon: an autonomous drone that can select targets without oversight or a backlink is essentially immune to jamming, offering a much higher likelihood of completing its mission than alternatives.

At the same time, it becomes riskier when it is completely cut off from communications, malfunctions, or fails to select the correct target without human oversight.

Interestingly, BAE Systems Bofors' own release on Winter Demo 2026 does not mention the strike at all. It frames the three-day Karlskoga event around roughly 20 startups and technology companies, with Swedish Defense Minister Pål Jonson joining a panel and saying, "We need more actors and entrepreneurs in the defense industry."

The test, despite lacking human interaction in its end-game, still relied on human input to some degree: a user pushed a button to start the exercise, and humans set the parameters overseeing the entire exercise.

This isn't the first machine to choose its own target, however; Israel's Harpy loitering munition, fielded since the 1990s, can autonomously detect and attack radar emitters whose locations were unknown at launch.

This is awkward timing for regulators, to say the least: on September 5, the 128 states party to the Convention on Certain Conventional Weapons agreed on a non-binding text on lethal autonomous weapons, after the United States and Russia pushed late changes, including to a section on human judgment and control.

As a result, Nicole van Rooijen of Stop Killer Robots told Reuters that three years of work had been "substantially diluted in the last hours." For now, Scaleout has shown that detection, ranking, and targeting can run on a small airframe without a data link, within parameters that people set.

Whether this makes it to a modern battlefield is increasingly likely, even as the Russia-Ukraine conflict becomes more reliant on autonomous machines. The more pressing question is one that will be answered sooner or later: how does such a drone make decisions if it is jammed from its source without any human oversight?

• Researchers report a new upgrade for lithium-ion
• Added graphitic carbon nitride can boost capacity
• It would mean higher power delivery for longer

With so many modern-day devices dependent on rechargeable lithium-ion batteries, scientists are hard at work trying to figure out ways of improving the tech — and a team from the Korea Research Institute of Chemical Technology (KRICT) has just announced a significant breakthrough.

As reported by The Korea Times, the KRICT researchers have succeeded in boosting the power delivery capacity of lithium-ion battery chemistry by adding a small amount of a material called graphitic carbon nitride to the cathode end of the battery.

When a battery is charging, the lithium ions get pushed out of the cathode, through an electrolyte material, to the anode at the other end. When the battery is in use, the ions flow back in the other direction.

One potential way of storing more energy in a battery of the same physical size and weight is to make the cathode thicker, but there's a problem: this also makes it harder for the lithium ions to move and deliver all of the energy held in the battery. The new innovation that was successfully tested here could solve that problem.

Capacity boosting

Microscopic imagery showing the cathode mix (Image credit: Eun et al., Exploration, 2026)

The researchers have reported some impressive numbers from their tests, though the tech is still at an early stage. Adding the graphitic carbon nitride to the cathode resulted in a 166% increase in capacity during high-rate discharge, and an increase in power density of up to 2.85 times.

Those figures don't mean a bigger capacity in mAh terms, but delivering more of a charge under heavy load, and for longer. In lithium-ion batteries, using a lot of energy quickly reduces how much total capacity you'll get from the battery compared to if you used the same amount of energy but more slowly.

In an EV, for example, this would mean that the vehicle could accelerate harder and sustain that high performance for longer without impacting total range as much. It would allow home batteries to better sustain their capacity if you use them with appliances that drain a lot of energy quickly, such as washing machines.

But smaller applications can benefit from it as well — drones can draw a lot of power suddenly to life themselves, or gaming and workstation laptops might suddenly draw a lot of power depending on the workload — they'd all benefit from tech that handles the power flow's effect on capacity better.

The tech could, in turn, result in batteries with thicker cathodes that do give you more mAh capacity in the same space, the researchers say — but that wasn't tested in this study. The next challenge is to try and scale up and expand the technology.

According to KRICT President Shin Seok-min, this alternative approach to lithium-ion batteries could potentially be used across electric vehicles, energy storage systems, and robotics — so it's very broadly applicable, especially for devices and systems that can take batteries that are physically larger.

CIOs and CFOs face rising AI costs, DevSecOps tool sprawl, and software supply chain risk. Learn how to strengthen oversight, cost controls, and ROI.

The post The CFO-CIO Reality Check: Governing DevSecOps and AI Costs appeared first on TechRepublic.

Amazon has its own agentic AI option called Buy for Me, which could be behind the agentic turf war.

• AWS deal with Nvidia adds 2 million Blackwell Ultra, Rubin, and Rubin Ultra GPUs, on top of more than 1 million committed in March 2026
• Totals more than 3 million Nvidia GPUs due before 2029, a ~1.9x multiple for each of Amazon's roughly 1.58 million employees
• Nvidia's CFO has said deliveries start this quarter, not in 2027, but neither company says what it counts as a GPU or what the deal costs

Amazon ended 2025 with about 1.58 million full- and part-time employees, most in fulfillment centers and delivery operations, with a much smaller share working in its AWS data center division (estimated at around 246,000).

By mid-2028, Amazon Web Services expects to have taken delivery of roughly twice that many new Nvidia GPUs, based on a recent deal it made with Nvidia.

The latest deal was announced on August 26, the same afternoon Nvidia reported quarterly earnings, and will see AWS plan to deploy two million additional Blackwell Ultra, Rubin, and Rubin Ultra GPUs across its global infrastructure in 2027 and 2028. This is on top of over a million Nvidia GPUs that AWS committed to at Nvidia GTC 2026 in March, and which Nvidia's Ian Buck told Reuters would ship from 2026 through 2027.

A mammoth deal that dwarf's Amazon's entire payroll

Together, this all amounts to over three million GPUs in play between the data center giant and the chip designer, which is also the world's most valuable company at the time of writing. At 3 million GPUs against a workforce of 1.58 million, that's nearly 1.9 Nvidia GPUs per employee.

This is only Amazon's commitment to Nvidia; it also has its own custom Tranium3 GPUs, which the company says are "nearly fully subscribed" or "almost fully booked" as of mid-2026.

At the same time, Amazon is not increasing job roles on its end; it cut around 30,000 corporate roles between October 2025 and January 2026, a restructuring its top HR executive, Beth Galetti, described as "reducing layers, increasing ownership, and removing bureaucracy."

Building on an already solid base

While AWS's current GPU base from Nvidia, consisting mainly of H100 and H200 GPUs, is smaller than Microsoft's 485,000 count, it is hardly a rounding error, with Omdia estimating that Amazon bought 196,000 Hopper GPUs in 2024 alone.

The interesting part is determining what counts as a GPU: Nvidia and Amazon's joint statement about 2 million GPUs across calendar years 2027 and 2028 might mean two very different things depending on how you count GPUs.

At GTC 2025, Nvidia said it would count Rubin-generation GPUs by compute die rather than by package, which is why the Vera Rubin rack was first unveiled as NVL144. It reversed course before CES 2026, and the flagship now ships as Vera Rubin NVL72, counting 72 two-die packages. To make matters a bit more complicated, Rubin Ultra, due in 2027, puts four compute dies in each package.

Whether the companies count each die as a separate GPU or the whole package as a GPU could make the numbers skew heavily in either direction. The deal also includes a national security element: approximately 100,000 GPUs are earmarked for US government AI workloads at Impact Level 6.

Amazon's limitation here is supply, not demand; AWS revenue rose 37% year over year to $42.2 billion in the second quarter, and its contracted backlog reached $496 billion, up from $364 billion three months earlier, as CloudTech News reported.

On Amazon's July earnings call, CEO Andy Jassy said capacity would fall short of demand this year and likely next, adding: "In fact, the demand we already have for 2028 is striking."

In addition to its own custom ASICs, including Tranium3, Amazon is gearing up for a few fiscal years of eye-watering AI infrastructure spend and AI demand combined, and it better be right: Amazon's free cash flow has already turned negative as it looks to fund its bid to be one of, if not the largest hyperscaler in play for the foreseeable future.

Via StorageNewsletter

Apple reportedly cut Fitness+ audio staff as it reviews the subscription service, with fewer Time to Walk and Time to Run releases expected.

The post Apple Cuts Fitness+ Staff as It Rethinks Its Fitness Subscription appeared first on TechRepublic.

OpenAI’s agent findings show why enterprises need scoped credentials, per-request authorization, audit logs, and data controls alongside AI guardrails.

The post OpenAI’s Agent Findings: Why AI Guardrails Need Data Boundaries appeared first on TechRepublic.

The fall equinox, which arrives Tuesday in the U.S., brings shorter days, and chances to witness alignment between Earth and the sun. It's a modern version of ancient observances of a celestial shift.

(Image credit: Bilgin S. Sasmaz)

My two sons are obsessed with 3D-printed toys, so a 3D printer is on their Christmas wish list, which makes this Amazon deal very appealing.

The Bambu Lab P1S is Amazon's number one best-selling 3D printer, and it just dropped to $499.99 (was $549.99). That's a $50 discount and the lowest price we've ever seen for the 3D printer.

• Shop more 3D printer deals at Amazon

The Bambu Lab P1S is a great introduction to 3D printing, with claims that it can be set up in just 15 minutes and offers hassle-free assembly for all skill levels. It supports up to 16 colors, so you can print endless, colorful creations, and it's fast too, with a max speed of 500 mm/s. It also includes a handy remote control and comes in an enclosed-body design with an activated carbon filter for improved performance.

Save on Amazon's best-selling 3D Printer

Lab P1S Combo 3D Printer: was $549 now $499.99
The Bambu Lab P1S is Amazon's number 1 best-selling 3D printer, and it's on sale for $499.99 - a record-low price. The Bambu Lab S1S takes just 15 minutes to set up, offers 16 colors for endless creations, and prints at lightning speed.View Deal

Keep in mind that today's discount on the Bambu Lab S1S is a limited-time offer and a record-low price. That $499.99 price tag is also an incredible deal for a high-quality 3D printer, as other models retail in the $600 to $800 price range.

OpenAI reportedly projects $280 billion in cash burn through 2030 as soaring compute and infrastructure costs continue to outpace its revenue growth.

The post OpenAI’s Compute Costs Could Burn Through $280 Billion by 2030 appeared first on TechRepublic.

Nvidia says Vera Rubin NVL72 delivers up to 30x more agentic AI throughput, but enterprises should weigh workload needs, power, cooling, and cost.

The post Nvidia Vera Rubin NVL72 Boosts Agentic AI Throughput by 30x appeared first on TechRepublic.

• So-called signal sharing between Microsoft and Google uncovered the RedVDS marketplace was behind large-scale cyber fraud
• RedVDS sold access to virtual machines running unlicensed software from which cybercriminals launched scams and directed attacks
• Threat data was shared securely via the Global Signal Exchange (GSE), a non-profit organization

A major cybercrime marketplace has been taken out of action thanks to cooperation between Microsoft and Google via a secure threat data sharing platform.

Known as the Global Signal Exchange, the collaboration led to the take-down of the RedVDS, an online cybercrime mall supplying virtual machines for launching phishing, business email compromise attacks, and more.

The marketplace – which provided quickly-deleted and therefore virtually untraceable VMs – was meticulously monitored by Microsoft’s security team, Digital Crimes Unit, with both Microsoft and Google suspending the operation and action taken to seize domains and servers.

A secondary case featuring the GSE identified a Microsoft-impersonating tech support scam, resulting, highlighting the importance of secure thread data collaboration platforms.

Digital Crimes Unit

Finding massive scams is not easy. Even with its own Digital Crimes Unit, Microsoft has to rely on information sharing with third party organizations. In this case, the RedVDS marketplace was identified ahead of disruptive action taken by Microsoft in January 2026, which applied to courts in the UK and US to have the RedVDS web domains seized.

Data shared via the GSE enabled Google to follow suit, identifying related accounts on its networks and suspending them. Meanwhile, servers were impounded in Germany, and Europol took action against Europe-based RedVDS servers.

It’s an impressive account of cooperative, decisive action against cybercrime, a collaborative response to what has been described as a “$66 million fraud marketplace.”

An incredible 130,000 organizations were targeted by RedVDS-provided virtual machines between September and December 2025, with 191,000 Microsoft email accounts compromised during this period. All of this access to cybercrime was available from just $24 a month for a basic scam-ready virtual machine.

The importance of collaboration

The Global Signal Exchange is a UK-based non-profit, co-founded with Google in 2025 with the aim of providing real-time monitoring of the cybercrime supply chain.

"Fraud does not respect company boundaries, and no single organization ever sees the whole picture," noted Emily Taylor, CEO at Oxford Information Labs and Co-Founder of the Global Signal Exchange.

"That is exactly why we built GSE: to give trusted partners a secure way to share what they know, quickly. These two cases are a good example of GSE doing exactly what it was designed to do."

The Global Signal Exchange’s role in the sharing of information between Google and Microsoft has highlighted the importance in such collaborations. Both organizations have stated they plan to continue sharing information through the GSE, whose other partners include Meta, Amazon, Google, among many others.

The Federal Aviation Administration launched an ambitious $875-million-dollar push to make the U.S. airspace more efficient. But critics say it won't solve bigger problems with air traffic control.

(Image credit: Mario Tama)

The Clicks Communicator adds 12GB of RAM, a larger battery and Android 17 ahead of launch, turning the keyboard phone into a more complete smartphone.

The post Clicks’ $499 Keyboard Phone Is More Than a BlackBerry Throwback appeared first on TechRepublic.

Trump proposes an AI Force as the US and China discuss a safety channel for serious AI incidents. Here’s what IT leaders should watch closely.

The post Trump Proposes ‘AI Force’ as US, China Discuss AI Safety Channel appeared first on TechRepublic.

We're gearing up for the second wave of major marathons this year: runners will be heading for the start line in Berlin at the end of the week (27 September), with the Chicago marathon following on 11 October and New York rounding out the season on 2 November.

Perhaps you're wondering what kind of footwear is propelling elite athletes to these kinds of times? I've hunted out the shoes worn by a selection of marathon winners, and rounded up the results below.

The Adidas Adios range crops up time and time again. Sabastian Sawe and Yomif Kejelcha both sprinted to stunning sub-2 hour success at the 2026 London marathon while wearing Adidas Adizero Adios Pro Evo 3 shoes (currently sold out in the US, but a restock is coming in the UK on 24 September.) Sawe wore Adidas Adios Pro Evo 2 to take the gold at the Berlin 2025 marathon, as did Benson Kipruto for his 2025 New York win.

Hot on Kipruto's heels in Berlin 2025 was Alexander Mutiso Munyao, wearing the Adidas Adizero Adios Pro 4. Incidentally, women's champ Rosemary Wanjiru was also wearing Adios Pro 4. In Chicago 2025, Hawi Feysa took the gold in the women's race wearing Adidas Adios Pro Evo 1.

Nike's winning line is the Alphafly. Jacob Kiplimo won the 2025 Chicago marathon in Nike Alphafly 3 — also the running shoe of choice of record-breaker Eliud Kipchoge.

It's not all about Adidas and Nike, though. John Korir has won two Boston marathons in a row while wearing prototype versions of the Asics MetaSpeed Sky, and Sharon Lokedi wore Under Armour Veliciti Elite 3 to defend her crown at Boston 2026. Hellen Obiri took the women's crown at the 2025 New York marathon in On LightSpray Cloudboom Strike — particularly notable for their laceless, 'spray-on' style.

If you're a keen runner and find yourself gripped by marathon fever, perhaps these are some models worth considering for your next long-distance race. But a couple of important caveats, before we start: First, if you're already in training for one of the upcoming marathons, you definitely don't want to be switching up your footwear in the run-up to the event. Second, these shoes are aimed at experienced long-distance runners; if you're not at that stage yet, head to our general best running shoe roundup for more beginner- and intermediate-friendly recommendations.

US: Marathon-winning running shoes

Jump down to UK shoes

Adidas Adizero Adios Pro 4 (men's)

Adidas Adizero Adios Pro 4 (women's)

Nike Alphafly 3 (men's)

Nike Alphafly 3 (women's)

Under Armour Velociti Elite 3 (unisex)

Adidas Adizero Adios Pro Evo 1 (unisex)

Asics Metaspeed Sky Tokyo (men's and women's)

Adidas Adios Pro Evo 2 (unisex)

On Lightspray Cloudboom Strike 2 White unisex)

UK: Marathon-winning running shoes

Adidas Adizero Adio Pro Evo 3 (restock soon)

adidas Adizero Adios Pro Evo 2 (unisex)

Nike Alphafly 3 Glam (men's)

Nike Alphafly 3 (women's)

Adidas Adizero Adios Pro 4 (men's)

Adidas Adizero Adios Pro 4 (women's)

adidas Adizero Adios Pro Evo 1 (unisex)

Asics Metaspeed Sky Tokyo (unisex)

UnderArmour Velociti Elite 3

On LightSpray Cloudboom Strike

• BAN says 87% of data center hardware isn't actually accounted for in most figures
• Each 1GW of capacity equals 70,000 tonnes of hardware
• AI hardware needs more frequent replacing

A new Basel Action Network (BAN) report has claimed the ongoing AI boom could create a new stream of e-waste, with retired equipment from AI alone likely contributing 395-617 million tonnes between 2025 and 2050.

To put that into context, BAN says that waste would fill 15-23 million 40ft shipping containers, which, placed end-to-end, would be enough to circle the earth six times over.

Ultimately, Moore's Law is to blame because developers are no longer able to achieve such great improvements in performance year-over-year, so they're having to introduce whole new types of technology.

AI will likely lead to massive amounts of e-waste

For example, AI companies are now having to deploy huge numbers of specialized AI accelerators alongside GPUs, cooling equipment, networking and more.

BAN also highlights that global data center Capex is expected to hit $7 trillion between 2025 and 2030, with $4.3 trillion of this attributed to electronic hardware.

The paper goes on to criticize earlier estimates for only including servers and accelerators, which it says is only around 13% of the picture. The other 87%, which spans networking, power distribution, storage/backup, and cooling, is largely unaccounted for.

And with each additional 1GW of data center capacity estimated to need around 70,000 tonnes of electronics, and 100GW of additional capacity anticipated globally by the end of this decade, the true scale starts to become clearer.

There's also refresh cycles, because BAN predicts that AI accelerators, servers and racks are replaced every 2.5 years, versus the usual five to seven years of a general-purpose server.

While these may be speculative estimations and not actual quantities, one thing's for certain – more data centers means more e-waste.

To minimise some of the impacts, BAN first suggests designing AI data center equipment to last longer in the first place. Recycling and second use is also a big topic, but the report doesn't go into whether AI-specific hardware can then go on to be used in lesser functionalities, such as being shoehorned into regular server facilities.

Paramount's owners have made concessions to 12 Democratic state attorneys general to settle a lawsuit that endangered the media company's bid for its larger Hollywood rival, Warner Bros. Discovery.

(Image credit: Noam Galai/Getty Images for Paramount)

• Hackers took down a Flock camera and extracted a copy of its storage drive
• There, they were able to acess 1.6 million images and 27,000 videos taken over 21 days, despite claims that the encryption system should prevent this
• Morale is reportedly so low at Flock that many workers are ready to quit

Another day, another Flock controversy. As if things couldn’t get any worse for the embattled maker of automatic license plate recognition (ANPR) cameras, hackers have just managed to extract 1.6 million images and 27,000 video clips from one of its systems — something Flock has previously claimed should be impossible.

According to a report from 404 Media, members of a hacker collective named stegan0gram took down a Flock camera and managed to make a “near-complete copy” of its stored data.

When they did that, they found a treasure trove of privacy-compromising information and shared it with both 404 Media and the Distributed Denial of Secrets nonprofit, who then sent it on to Wired.

The report from 404 Media identified around 50,200 vehicles in Flock’s media files. The storage contained approximately 1.6 million images and more than 27,000 video clips taken over the course of 21 days. Older logs were either overwritten or inaccessible.

Perhaps more concerning, Flock’s cameras were able to detect people as well as vehicles and license plates, raising serious questions about how well the privacy of innocent members of the public is being protected. That said, 404 Media found no evidence of any kind of facial recognition being put to use.

The hackers said that they discovered two partitions when they accessed the Flock camera’s Android operating system. Inside one labeled “media,” they found a decryption key that unlocked a storage area housing the vast collection of images and video clips.

That all goes against public statements from Flock. The company has previously claimed that images and videos are only briefly stored on the device after being sent to Flock’s servers, and that no decryption keys were stored on the devices.

But with the hackers discovering stored media going back many weeks, plus the means to decrypt it, it appears that Flock’s statement might be inaccurate.

‘The writing is on the wall’

(Image credit: Getty Images)

As you can probably imagine given the near-constant barrage of negative press Flock has been facing in recent weeks, its own employees are reportedly starting to feel the strain. And with morale through the floor, many are seeking to leave the company.

Wired has reported that Flock recently opened up a voluntary separation program for employees that would offer a “generous” severance package to anyone who seeks a way out of the firm. The scheme is open until October 2, with decisions being announced on October 9.

And according to “people familiar with the program but not authorized to discuss it publicly” cited by Wired, morale is so low at Flock that “a significant number of the startup’s roughly 1,500 employees may try to depart.”

That backs up comments from Flock’s own CEO, who said on the All-In podcast in August that “internal moral” has been the biggest casualty amid escalating hostility to the company’s devices.

For many Flock workers, the severance offer is likely to come at a good time. As one apparently disgruntled employee told Wired, “When you see enough of the vandalism [aimed at Flock cameras], you know the writing is on the wall.”

If you're the kind of person who only dabbles in ChatGPT now and again, you might be getting a bit bored.

Maybe you use it to proofread work, plan a trip or make images sometimes. But with the cost of a subscription, and growing concerns about AI’s environmental impact, its effect on our cognitive abilities and what it might mean for jobs, you might reasonably be wondering: is ChatGPT actually useful enough to justify using it?

Well, you're not alone. Plenty of AI users have been telling me the same. So I went looking through Reddit threads where ChatGPT users were sharing the more unusual and genuinely useful ways they use it. And I found a few that might actually be worth experimenting with.

One Redditor asked: What's the most unexpectedly useful thing ChatGPT has done for you? Another posted: What are the most useful ChatGPT features and use cases that most people do not know about?

So, I went through the most upvoted replies looking for ideas that went beyond the usual writing, brainstorming and summarizing suggestions. Some of them made me think about ChatGPT's capabilities in a different way.

But a quick caveat before we start, I haven't tested every suggestion below and we know ChatGPT can make mistakes, so be cautious when an answer could affect your health, safety and finances. Think of these more as inspiration for using ChatGPT more creatively rather than fully vetted recommendations.

1. Declutter your junk drawer

(Image credit: Future)

I know this one might seem a bit silly. And maybe you thought you'd have to wait until ChatGPT gets a robotic body to help you tidy up. But I promise it might make your dull organization tasks a little less boring.

One Redditor said they use ChatGPT to: “organize and declutter a junk drawer or a box of power adaptors just using pictures.”

Rather than sitting there examining every mysterious cable and adapter you’ve accumulated over the past decade, you can just take a photo and ask ChatGPT to help you work out what everything is and, most importantly, how to sort it.

You can ask it to suggest categories for what you’ve decided to keep and where each group should live. The same trick could work for a toolbox, kitchen cupboard, art supplies or that box of cables you’re keeping because you're convinced one of them will become extremely important as soon as you throw it away.

So, I decided to give it a go. I took a picture of a box that sits on my desk packed full of contact lenses, medication, a bunch of different cables, notes and hair ties.

The advice was helpful, ChatGPT told me what each thing was and how to sort everything. The most useful thing it then did was send my photo back to me with annotated and color-coded notes so I could quickly go about sorting. This was perfect for my ADHD brain.

(Image credit: Future)

There are obvious limits here, you wouldn't throw away something valuable just because ChatGPT told you too. But as a starting point for tackling a chaotic collection of stuff, it might be helpful.

2. Talk yourself out of buying something

AI shopping tools are usually designed to help you find more things to buy. But one Redditor uses ChatGPT for the opposite purpose: "[It] talks me out of purchases. I upload a potential purchase and ask it to talk me out of it. I’ve saved quite a bit of money!"

I love the reversal here. Instead of asking ChatGPT whether you should buy the $200/£200 headphones currently sitting in your basket, tell it you want them and ask it to make the strongest possible case for why you shouldn't buy them.

You could give it the price, tell it what you already own, explain what you think the new product will improve and ask questions, like: What problem am I actually solving here? Do I already own something that does this? What are the strongest reasons to wait a month?

I gave this one a go. I love working out outside and at the gym, but in the depths of winter I find it really hard to stay motivated and I'm considering getting a small treadmill or walking pad. There's nothing wrong with them, but it's not my favorite way to workout, I don't have much room for one and the good ones aren't cheap. I really need someone to talk me out of getting one. Would ChatGPT be up for the challenge?

Here's how it responded:

"Don’t buy it. You already know the case against it. You don’t enjoy treadmill workouts, don’t have much space, and don’t want to spend the money. You’re considering buying a fairly large object to solve a problem that exists for a few dark months a year."

The response felt a little short and sickly sweet. If my finger was genuinely hovering over the "buy it now" button I'm not sure this would have stopped me. But I do love the idea of using AI to actually add some perspective and friction back into our lives.

3. Streamline your skincare routine

(Image credit: Future)

This one is similar to the idea above, but given how much people spend on skincare these days and how confusing the advice is about how to build the perfect routine, I think it's well worth testing out.

One Redditor said: “I gave it all my skincare. It cross referenced, compared and analyzed all the ingredients and items I had and recommended what I don’t need based on the overlaps. Saved me a lot time and money.”

In other words, don't ask ChatGPT what else you should buy. Show it what you already own and ask where you're duplicating things and if something does genuinely need adding.

For skincare, that could mean listing your cleansers, serums and moisturizers and asking it to identify products containing similar active ingredients. You could potentially apply the same principle to all sorts of collections too.

I took a quick snap of my core skincare staples and asked it to analyze the ingredients, tell me if there's overlap and ask what I could add, but stressed I'm on a budget and want to keep things simple.

It responded with a detailed breakdown of each product, its ingredients and what they do. It was also very measured about suggesting new products, and even told me my eye cream wasn't necessary. I was also happy it included sources for every claim, which it doesn't always do but that's important for skincare.

(Image credit: Future)

I then asked it to present this information on the image itself because I found that really useful for the junk drawer sorting example, and it was such a handy visual.

There are limitations here too. ChatGPT isn't a dermatologist, and ingredients alone don't determine how suitable a skincare product is for you. But I like the broader idea of using AI to audit your consumption rather than constantly optimize it by adding more.

4. Identify plants, animals and trees

(Image credit: OpenAI / Apple)

“I use it a lot to ID plants and animals,” one Redditor explained, adding that although ChatGPT occasionally produces “a weird incorrect response”, it's usually quite good.

This is another use for ChatGPT's camera capabilities that could be easy to overlook if you mostly interact with it through text.

Photograph a plant, insect or bird and ask ChatGPT what it thinks you're looking at. Better still, ask it what features it's using to make the identification and what similar species it could be confusing it with.

I tried this out with a bunch of trees, asking ChatGPT to identify them based on their leaves. I then fact-checked everything and it identified them all correctly. It also provided details about the history of the trees too. Most of the trees in my area are pretty standard, like Oak, Ash and Beech, so it'd be interesting to see how it fares with trees, plants or insects that are a little more unexpected.

If it’s bird song you’re interested in though, I highly recommend using the identification app Merlin, it’s one of my most-used and much-loved apps.

And also remember that ChatGPT doesn’t always get image identification right, and you shouldn't eat, touch or otherwise interact with a potentially dangerous plant, fungus or animal based purely on a chatbot's identification.

5. Plan a walking tour

(Image credit: Future)

This tip came up in several forms. One Redditor said: “If I'm taking a walk in an interesting place, like a historic district, I show it a particular building or place and it gives me the history behind it. Like having a walking tour guide.”

Another user takes a screenshot of a hiking route and asks ChatGPT for interesting facts about the geology, history and place names they'll encounter along the way.

This is one of those ideas that feels obvious once somebody else has suggested it. Before a walk, you could upload a map and ask for five interesting things to look out for. Or when you encounter an unusual building, monument or landscape feature, take a photo and ask what you're looking at.

I’d be wary of confidently repeating every historical fact ChatGPT gives you to your hiking companions without checking it first. We know that chatbots can still invent plausible-sounding details. And never rely on it for route planning, especially though difficult terrain. There have been far too many horror stories about AI sending people in completely the wrong direction recently.

(Image credit: Future)

I tried this one myself and shared a Google Maps screenshot of Saltaire, a picturesque village in the UK. I asked ChatGPT to mark up the map with the best things to see on a trip there.

It showed me all of the key things to visit in the area. Granted there wasn't anything on here I couldn't have found from a very quick search. But it's still handy if you're in a new area for a few hours and want a quick overlay of the map you already have.

6. Troubleshoot a broken appliance using photos

(Image credit: OpenAI / Apple)

Plenty of people already ask ChatGPT technical questions. What I hadn't really considered was combining those questions with its ability to “see” what you're seeing.

One Redditor described doing exactly that when their dishwasher stopped working. They wrote: “Fixing appliances. Our dishwasher stopped working. I gave it the error message and took a photo of the dishwasher and it walked me through every step to fix it.”

They say ChatGPT eventually helped them identify a blockage and suggested ways to clear it. This seems useful for those frustrating household problems where you don't know the correct name for the thing you're looking at. Instead of trying to Google “the little plastic thing underneath dishwasher filter is broken”, you can simply show ChatGPT the little plastic thing.

Give it the appliance's make and model if you can, photograph the problem and provide the exact error message.

I tried this with the water heating system in my new flat because my landlord gave me the wrong manual. ChatGPT needed a lot of additional details but did end up giving me the right instructions for basic tasks, like setting a timer.

There’s a big safety caveat here. I wouldn't follow AI-generated instructions involving electricity, gas, dangerous machinery or anything else where getting it wrong could injure you. But for basic troubleshooting, identifying components and understanding error codes, the combination of text and images could be genuinely useful.

7. Find the glasses that'll suit your face

One Redditor uploaded a photograph of themselves and asked ChatGPT for help choosing prescription glasses:

“It helped me identify prescription eyeglass frames to fit my face. Uploaded a picture and it gave me the size, shape and website with model and frame number. Turns out I was wearing the wrong shape most of my life.”

I need new glasses so decided to try this idea out for myself.

(Image credit: Future)

I'd take the idea of a "right" or "wrong" glasses shape with a big pinch of salt. Style rules about which frames supposedly suit particular face shapes are subjective.

But doing this did help me start thinking about which glasses I should try on when I have my appointment at the optician's in a few weeks and narrow down the enormous number of options that are available.

You could also show it frames you already like and ask it to describe their characteristics so you know what terms to search for.

I think what's really interesting about all of these suggestions is that most of them aren't about building the cleverest or most elaborate prompt. Instead, they started with something in everyday life that needed identifying, organizing, checking, fixing or remembering.

So if you want to get creative about how ChatGPT could be more useful, maybe you need to look around more and ask, what do I really need help with?