Technology

It's the largest cryptocurrency theft in history: hackers from North Korea allegedly swiped $6.36 billion in funds from Binance in the space of just 20 minutes, which has left customers reeling and the financial industry in shock.

The heist raises all kinds of questions about how this was allowed to happen, what might happen next, and whether Binance customers are going to get any of their stolen money back.

Even if you never owned any cryptocurrency before, there are bigger questions too — like what this means for global financial stability, and what the aftershocks might be for everyone outside the Binance world.

Looking for a quick five-minute primer on the Binance hack? We've been speaking to industry experts to get some answers...

1. What actually happened?

(Image credit: Getty Images / Dan Kitwood)

The basics are now pretty clear — $6.36 billion in cryptocurrency was stolen from the Binance exchange in the space of just 20 minutes. Security analysts are pointing the blame at North Korea's TraderTraitor hacking group, which has a history of this kind of heist. What's less clear is exactly how the hackers got access. Early reports identified a Binance employee's compromised laptop as a potential way in, though it now seems there's more to the story.

"A compromised laptop may explain where an attack started, but it does not, on its own, explain how billions of dollars could leave an exchange," Pieter Arntz, researcher at cybersecurity firm Malwarebytes, told TechRadar. "The real question is what allowed that initial foothold to become access to withdrawal systems — and which safeguards failed to stop unauthorized transactions."

"According to blockchain analysts, the attacker spent at least a day and a half preparing, including testing their tools on public blockchains where anyone could see," Ben Bernstein, manager of cybersecurity advisors at Huntress, told TechRadar. "Then most of the $6.3 billion left Binance's wallets in about 20 minutes. That's common in attacks we investigate. The attacker does most of the work long before anything is stolen."

2. Will anyone get their money back?

Binance says customers will be refunded (Image credit: Shutterstock / Diego Ioppolo)

Binance has promised to reimburse customer losses through its backup and emergency funds, but in the meantime we're seeing deposits and withdrawals frozen on the platform while the hack is investigated. It's a warning that even the largest and most sophisticated exchanges can still be vulnerable.

"Binance says it'll cover every cent," Nigel Green, CEO of the deVere Group, said in a press statement. "I hope so. The emergency fund is around $1.2 billion and the gap is several times bigger, so the rest has to come from the company’s own balance sheet. The market will want to see the numbers, and the new proof of reserves can’t come soon enough."

"Long term holders have just been reminded, very expensively, why keys kept offline matter. Crypto has spent years pushing back against heavy regulation, and plenty of those arguments were fair. This one's harder to argue with. Platforms holding billions of other people's money need enforceable security standards. I expect regulators in the US, Europe and Asia will likely move faster after this week," he added.

In the meantime, the US Secret Service has said in a statement that it's "working around the clock" with partners in the private sector "to identify, freeze, trace, and recover funds" that have been stolen from Binance.

3. What follow-up scams might appear?

(Image credit: Getty Images)

Whether you're a Binance customer or not, you need to keep your wits about you over the next few days. It's likely that scams trying to literally cash in on the hack will start appearing — perhaps warning you that you need to quickly claim refunds, lock your account against a particular threat, or go through a bogus verification process.

"Criminals routinely use major breaches as a hook for phishing campaigns," Dray Agha, senior manager for tactical response at Huntress, told TechRadar. "Consumers should be highly suspicious of any emails or messages claiming to be from Binance offering urgent account recovery steps. You must only check your account status through the official application or website rather than clicking links in unsolicited messages."

According to the team at Huntress, you should watch out for social media posts, emails, and text messages that use the Binance hack as a hook — perhaps a fake news story suggesting that now's the time to buy crypto, while prices are down.

As always, think twice about following links or entering sensitive information into online forms and portals you're not familiar with.

4. How does this affect the average consumer?

The hack shouldn't give you any financial surprises (Image credit: Getty Images)

If you don't own any cryptocurrency, the good news is that you're largely going to be unaffected by what's happened here. There's not going to be a stock market crash, or a run on the banks, or a global recession — not because of this hack, at least. However, it's always worth weighing up your own personal privacy and security setup.

"If you don't own crypto, the direct impact on you is small," Ben Bernstein from Huntress told us. "Your bank account and your card are not affected by this. The bigger takeaway for consumers is that attackers often get in by targeting people rather than technology, through a convincing email, a fake login page or a phone call from someone posing as IT support," he said.

"That makes security awareness everyone's job, at home and at work. If you pause before you click a link, approve a login or share a code, you're making it harder for an attacker, whether they're after your savings or your employer's systems," he added.

5. What does this mean for the future of money?

(Image credit: Getty Images / Dan Kitwood)

This clearly raises a lot of questions about the safety of cryptocurrency and the exchanges that it sits on — and of course it's far from the first crypto heist we've seen. In the longer term, it may lead to less confidence in crypto as a whole, but the experts we spoke to don't think it will bring the industry down. What will be important is making sure the risks of this happening again are minimized as much as possible.

"Despite the scale of the theft, this is not a threat to global financial stability," Feike Hacquebord, Principal Threat Researcher at TrendAI, told TechRadar. "Around half of the stolen funds have already been frozen, while the regulated banking system is well equipped to absorb a shock of this size. This is a major crisis for Binance, not a crisis for the global financial system."

"The change I’d like to see, for crypto firms, banks and every other business, is working on the assumption that someone will get in eventually," Ben Bernstein told us. "Keeping attackers out matters, but it isn't enough on its own. Companies also need someone watching around the clock, especially for logins and account activity that don't look right, so they can find and remove an intruder before the money starts moving," he added.

Long before anyone trained a model on customer data, the marketing data business worked out the terms for pooling it. Catalog retailers in the 1990s joined data cooperatives that combined their transaction histories so each member could find new buyers, and the arrangements held together because the rules were blunt.

A retailer contributed data to receive modeled prospects; no member got a rival's customer file; and a company that stopped contributing stopped receiving. Card fraud consortia run on similar give-to-get terms. Nobody would call these systems elegant, but every participant understood the trade.

Software vendors building AI features are now running into the same question, usually without the rules. Traditional software sat on top of a customer's data and operated on it. AI products learn from data, and on a multi-tenant platform, that learning rarely stays within a single account.

One company's records can sharpen the enrichment, lead scoring, and recommendations delivered to thousands of others. A vendor can improve its product for every customer by relying on the work of a few, and most contracts say nothing about whether that trade is fair. The customer still owns its data in any legal sense.

Ownership alone doesn't answer who benefits.

Users push back on sharing hard-earned data

HubSpot learned how touchy the question has become when it announced plans to pool enrichment data across customer accounts, including business contact details, employer information, and email deliverability signals, to improve prospect records platform-wide.

Every account was in by default. Within days, the company dropped the plan and promised that any future enrichment feature built on customer data would be opt-in. HubSpot had stated clearly that core CRM records would never be shared without permission, so privacy in the usual sense wasn't what upset the sales and RevOps teams, who pushed back. Their concern was harder to answer. Years of work spent cleaning and enriching their own contact data were about to improve the prospecting tools available to every other customer, competitors included, and nobody had asked what they would get for it. The product terms that allowed the change had been updated nearly two years before most customers heard about them.

AI creates accidental data companies

Plenty of software companies adding AI tools have never had to think this way. They are becoming data companies one model at a time, often without deciding to. Whether a customer's information feeds a shared model is often determined by a product team working toward a launch date rather than by anyone who owns the commercial relationship, and the answer is expressed in terms few buyers read.

McKinsey's 2026 survey on AI trust found that only about 30% of organizations have reached a mature level in AI strategy, governance, and controls. Pooled training data tends to fall between legal, product, and sales, with no single team feeling responsible for explaining it.

The need for strong exit clauses

Buyers will force the issue long before regulators do. Security certifications and uptime guarantees became standard contract language over the past decade because enough customers asked for them that vendors stopped arguing, and AI data terms are heading down the same road. Procurement teams are starting to ask whether their data trains or enriches models used by other customers, whether participation is opt-in, and whether it can be switched off later without losing core features. The more demanding buyers want to know what a contributing customer receives that a non-contributor doesn't.

Exit terms will be the hardest part to write. A customer can cancel a contract and demand its records back, but data that has already shaped a production model can't be cleanly pulled out again. Retraining is expensive, and removing one customer's influence from a live model remains an unsolved problem for most vendors. A vendor can honestly say it deleted every record a customer ever uploaded and still be running a model those records helped build. Contracts written for storage assumed that deleting data ended its use. Contracts written for AI will have to say plainly what persists after a customer leaves, and whether the customer agreed to it when it signed.

Opt-in consent answers part of the question. A checkbox tells a vendor it may use the data, but it says nothing about the return, and a customer who opts in for nothing in particular has made a poor bargain, even if it's a legal one. The old cooperatives signed up members because members could see exactly what they were getting.

Vendors that explain their data economics before customers ask will have an easier time at every renewal. The explanation belongs in the product and in the contract, and it should cover which customer data feeds shared models, what those models produce, and what contributors get back. Security questionnaires were once a formality, until buyers made them a condition of the sale. Pooled data terms are on the same schedule, and vendors that write clear ones now will set the standard that the rest of the market will follow.

Back when Apple announced watchOS 27 back in June earlier this year, there was one new feature that piqued my interest more than the promise of a smarter version of Siri or a Workout Buddy that now operated more standalone. Apple revealed that it was delivering more accurate distance tracking during walks and treadmill runs. It’s primarily doing that by making improvements to the algorithms that help to calculate the distance covered when you step onto that belt.

It's website states that 'improved motion tracking algorithms help measure the distance of your treadmill runs and walks more precisely straight from your wrist.'

As a runner that does his fair share of runs on a treadmill (and not just because it’s got cold outside — treadmill running is great for specific pacing and incline drills), I liked the prospect that the best smartwatch’s indoor activity credentials could now match its very solid outdoor performance — which I tested on the London marathon course’s infamous GPS black spots.

So, has Apple actually managed to deliver more accurate distance tracking for indoor runners? I’ve been spending the last couple of months testing the feature across the best Apple Watches — including the Apple Watch Series 12 and Apple Watch Ultra 4 — to find out.

How I tested

(Image credit: Getty Images)

I began my testing using the beta versions of watchOS 27 running on the Apple Watch Ultra 3 and the Apple Watch Series 11. When watchOS 27 was given a public release, I also strapped on the Apple Watch Ultra 4 and the Watch Series 12 to see how Apple’s latest smartwatches fared indoors.

I didn’t have my own treadmill (or indeed, have the room to house one), so I relied on the treadmill at my gym. While I did my best to stick to the same treadmill for these test runs, that wasn’t always possible. That did mean I’d be stepping onto treadmills of various conditions and belt wear, which does have an impact on the reliability and accuracy of the treadmill distance tracking feature.

With the Apple Watch strapped alone to one wrist, I had a Coros watch on the other paired to the Coros Pod 2. This foot-worn pod is designed to track distance, among other metrics, and was an additional source of data that could offer a more reliable picture of my running distance than the motion sensors that usually do that from the wrist. I used the foot-worn pod as a control device, the same way we use the best heart rate monitors to test the readings from smartwatches.

With watches on wrists and the pod on my feet, I captured a range of runs covering different paces and distances. That included short one-mile test runs, steady hour-long runs and interval runs during which I mixed up my pace.

I stuck to the same incline for all runs and used Apple’s own Workout app to track the workout. Apple suggests tracking an outdoor run of at least 20 minutes to calibrate the watch and help those algorithms do a better job of understanding your stride length, and in turn, deliver more accurate distance tracking. I did that with each Watch I tested.

The results

(Image credit: Ljupco Smokovski / Shutterstock)

On the early runs in my testing using the Apple Watch Ultra 3 and the Series 11, I found a difference of about 300 metres (0.3km) from the distances the treadmill and Coros Pod 2 reported. If I’m looking at that difference in terms of a longer distance race such as a marathon, that’s quite a small difference. If we’re looking at that difference over a shorter distance race such as a 5km, then it might be the kind of difference that mattered.

When I switched to testing with the publicly available version of watchOS 27 with the Apple Watch Ultra 4 and the Series 12, there tended to be a difference between the treadmill and watches of roughly 200 metres. Again, that’s a very good performance and a small difference when you’re banking a longer run.

Sample run

Apple Watch Series 12 distance

Coros Pod distance

Treadmill distance

1 mile test

1.2 miles

1.01 miles

1 mile

Interval run

4.2 miles

4.4 miles

4.5 miles

Steady 5 mile run

4.8 miles

5.02 miles

5 miles

The improvement in distance tracking should, in theory, have a positive impact on capturing your running pace. While I found the pacing data to in general be similar to the Coros Pod 2 and the treadmill, there were times I felt the Apple Watches struggled to register faster sections of certain running sessions and typically was more noticeable during interval-style sessions.

This is generally where treadmills can struggle too, and I’m not convinced the various Apple Watches always got a good grip of my real-time pacing.

Is the Apple Watch fit for the indoor run tracking job?

After hitting double-digit treadmill runs across a series of Apple Watches that promise more accurate distance tracking for indoor runs, I can say that I never saw the Watch and treadmill entirely match up. What I did see was that those Watches weren’t far off. reporting similar distances to the kilometers listed both on the treadmill and on the Coros Pod, especially on steady or easier paced runs. However, they were never exact.

Like most watches and badly-calibrated treadmills for that matter, the pacing during those runs did feel off and made using the Apple Watch for faster runs more problematic. I do feel that those algorithm tweaks will be more appreciated by those choosing to do their walking indoors, and are mainly focused on the distance they cover during that inside walking time.

If I was choosing to track my runs indoors, I’d still make sure I was performing that 20-minute outdoor run calibration to get the most reliable data. I’d also say that having a footpod sensor like the Coros Pod 2 or a Stryd that captures your stride data closer to the point of the body that’s actually doing the moving will get you a better level of accuracy. While the Coros Pod 2 is tied to Coros watches, the Stryd does work with the Apple Watch.

What it really showed is that if you care about accurate distance and pace data, getting outside and putting the onboard GPS sensor will still be the best way to get you that. It will also give that indoor running time a boost as well — while the Apple Watch has improved, it’s not pinpoint-accurate and you should take indoor running metrics as a generally accurate guideline, giving or taking a couple of hundred meters. For most exercisers, that will be enough.

Imagine the scene. You're in the park with your family, you're running to catch up with them, and your earbud case falls out of your pocket, scattering your earbuds. You find one but the other has vanished and all you can see is gravel. Who ya gonna call?

For Just-a-fungi893 on Reddit, the answer is: ChatGPT.

"I spent a solid 10 minutes searching, knowing there's basically no way I'm going to find a tiny white earbud in a sea of white gravel, especially with the sun setting," they explained. "I use ChatGPT for A LOT of stuff, and it suddenly dawned on me to ask it for help instead of pointlessly scanning the area myself."

Five minutes later, earbud and owner were reunited, with ChatGPT steering him towards the exact point in the relevant photo. It's not because ChatGPT has magic powers, but because LLMs are really good at spotting tiny things in big pictures: earbuds in gravel, needles in haystacks, indicators of tumors in X-rays. It's all pattern recognition.

ChatGPT found my lost earbud from r/ChatGPTIt's time to embrace our AI overlords vs no, it isn't

As fun as the story is — I'd never have thought of taking a photo and feeding it to a chatbot; it's smart thinking — one of the other comments on the Reddit thread made me laugh: Mindless-Apricot-236 responded that they once lost a screw outdoors, uploaded a picture to ChatGPT and "asked the oracle to help me find it. It said it found it. Showed me the picture... It just modified the original picture and put a random screw on it lol"

Other commenters had suggestions that didn't involve AI at all, such as 4-jr1's "how about next time you just open Spotify and listen for the one rock among hundreds that sings out loud" — although that wouldn't work if the headphones weren't on and paired; I have Bose QuietComfort earbuds and they don't turn on until they're in my ears — and SpehlingAirer's "When this kinda thing happens to me I turn on my phone's flashlight and bring it low to the ground pointing almost horizontally. The way the light reflects off the common background (gravel, carpet, grass, etc) and the way it reflects off the glossy plastic are often different enough to help spot it quickly."

And of course many of the best earbuds have some variation of Find My, enabling you to locate them from your phone. But it's nice to know that all those years we've been identifying bicycles, stairs and traffic lights in website CAPTCHAs has paid off: computer vision has become really incredible.

As to whether it's reliable, I'll just leave this, by AnalogAngeleno, here: "I tried something similar at a used bookstore. Took a photo of the shelve and asked it to help look for books since they were not in any kind of order. Unfortunately it started making up books that were not even there."

Still, you'll get different results depending on the type of task and the model you're using — evidently, this one worked well enough, and seems like a good tip to keep in mind for your own earbud emergency.

• Anduril plans to open BlueChip laptop orders in 2027 with Qualcomm
• BlueChip prototypes source 90% of component procurement costs from American and allied suppliers
• Anduril expects its laptops to cost 20% more than comparable devices

Anduril Industries has revealed plans to enter the laptop market through a partnership with Qualcomm, with plans to begin accepting orders for its BlueChip computers in 2027.

The defense technology company, best known for its military drones, intends to reduce reliance on overseas suppliers as it develops the new laptop line.

However, its current sourcing figures show that eliminating foreign suppliers remains a future objective rather than an existing achievement.

BlueChip begins with American manufacturing

The company has developed working prototypes featuring Qualcomm Snapdragon X Series processors, which will power the laptops.

Anduril says suppliers in the United States and allied countries account for 90% of the procurement cost of the components used in its prototypes.

The company already sources several parts locally, including batteries, computer enclosures and display glass.

Its strategy also involves using metals that American industries can extract, refine and process at commercial scale.

“Other companies might design their computers in the U.S., Anduril makes them here,” said Palmer Luckey, founder of Anduril Industries, in a company video.

“We’re making parts out of metals that the U.S. knows how to extract, knows how to refine, knows how to process, and knows how to mill at scale at a reasonable price; and that goes for the entire laptop. The same thing goes for the battery technology.”

The company says the laptop is designed to withstand demanding environments, with replaceable upper and lower shells that allow users to customize its configuration.

These interchangeable panels could accommodate additions such as solar panels, specialised fabric materials and service insignia, according to Anduril’s video.

The design also allows flat phased-array antennas to be integrated directly into the laptop’s chassis, potentially supporting specialised applications in demanding operating environments.

Anduril estimates that producing a fully American-made laptop could cost 20% more than a comparable device, potentially limiting its appeal to ordinary consumers.

Therefore, it appears to be focused on customers with specific security requirements, including government agencies, military organizations, emergency responders, and public safety departments.

These buyers may accept higher prices to address concerns about hardware security and supply chain reliability.

A domestic supply chain remains difficult

Anduril acknowledges that producing complete laptops requires more than processors and selected parts.

Circuit boards, displays, batteries, and other essential components remain heavily dependent on foreign suppliers, complicating efforts to eliminate reliance on these suppliers.

“BlueChip will take a phased approach, beginning with expanding domestic sourcing and manufacturing, progressing toward eliminating reliance on foreign suppliers, and ultimately establishing an end-to-end American supply chain,” the company said in its announcement.

The project comes as semiconductor investment grows in the United States, including TSMC’s facilities in Arizona and Samsung’s site in Taylor, Texas.

These projects could improve access to locally fabricated chips, but they do not guarantee a domestic source for every part needed to assemble a laptop.

Taiwan has also planned support for smaller companies supplying TSMC through industrial parks in the United States.

Such initiatives could give BlueChip access to additional suppliers, although their eventual contribution to the laptop’s production remains unclear.

Via Tom's Hardware

• OpenAI will keep pushing AI’s scientific discoveries, Sam Altman says
• Some researchers are excited by the ‘fantastic’ breakthroughs
• But others warn that the pace of change is ‘psychologically taxing’

One of the promises that huge AI companies like OpenAI and Anthropic have made is that their machine learning models will help to solve some of the oldest problems in math and science. The pace of their discoveries has left many experts struggling to keep up, but OpenAI’s Sam Altman just has just said there’s much more in store — and not everyone is happy about that.

Speaking on the Cheeky Pint podcast, Altman outlined his belief that “Humanity deserves fundamental knowledge, and we should not be sitting on a major fundamental science discovery.”

That rationale is why OpenAI has published breakthrough after breakthrough in these fields, knocking down some of the oldest and toughest problems that have troubled great thinkers for years. But the way in which the company has set out its results has drawn criticism for often inadequate attributions and questionable verification processes.

While Altman acknowledged that, saying on the podcast that “I do have empathy for the method” and saying OpenAI’s quest for mathematical challenges did “get out of control” at times, he suggested that there’s much more to come. Asked if the firm has anymore unpublished breakthroughs in its vaults, he replied “We do. Of course.”

That’s led to accusations that, far from giving people “fundamental knowledge,” OpenAI is gatekeeping important discoveries. And there’s another problem: the sheer scale of the new research is swamping academics. For instance, Wired has noted that the company recently “dumped 722 manuscripts on 400 problems on GitHub,” leaving the scientific community to pick through the enormous mass of information.

And the impact of having the most important work in your life suddenly undercut by a machine is “psychologically taxing for many people,” said Thore Husfeldt of the IT University of Copenhagen. Husfeldt added that there is “a lot of doom and gloom, because every week, or every second week, the results announced by AI just annihilate the ongoing research projects of many people.”

Obliterating entire fields of research

(Image credit: Shutterstock)

AI models’ ability to solve thorny problems was keenly demonstrated when it apparently disproved the exponential time hypothesis (ETH), which argued that the effort needed to solve a problem increases with its complexity. That’s upended countless theories that assumed that ETH was correct and left many experts scrambling to catch up.

As Linköping University professor Peter Jonsson told Wired, although AI’s tendency to undermine years-long research can be irksome, “at the same time, we learn a lot from it. And this is what science is about.”

UC Santa Barbara professor Daniel Lokshtanov aptly described the mood among many scientists and mathematicians, saying “It’s just a giant bomb dropped into the middle of the field,” he says. “It’s really cool and terrible at the same time.”

For Husfeldt, meanwhile, the discovery is “fantastic.” He added: “Being a mathematician is a lot like stumbling about in a completely dark room. It’s like somebody just illuminated an entire subfield in floodlights of knowledge, and now we just run around like overexcited bunnies and look at all the nooks and crannies that we can suddenly explore. So it’s a super exciting time.”

In the case of the ETH theory, OpenAI’s work has not been peer reviewed or independently verified. But it’s clear that AI research is creating generational changes in many areas — and overturning entire fields of study in an instant, with all the excitement and chaos that comes with that.

Jonsson fittingly summed the situation up, saying: “I don’t care if it’s a human-written proof, or it’s written by AI, or if an alien transmitted this proof to us. If it’s true, then we must simply use it in the future.”

• Berkeley professor Richard Borcherds says he no longer grades homework
• The renowned mathematician stated that it is amost impossible to spot a human written submission among those created with AI
• Grading in Borcherds’ classes are now conducted with in-person exams, completed without resorting to electronic devices

Professor Richard Borcherds of the University of California, Berkeley, has revealed he has abandoned grading homework for his math students.

The decision appears to have been made following an improvement in AI-produced homework, which has left educators unable to spot human-penned submissions from those completed using AI.

British-born Borcherds – whose award-winning work includes infinite-dimensional algebras and is currently researching quantum field theory – has determined that his students will be assessed using traditional exams, without reliance on electronic devices.

The decision follows Berkeley’s previous evaluation of AI detection software that it found was unreliable, and prompted the university to allow professors to formulate their own AI policies within the course syllabus.

"Grading for correctness"

AI has changed the game as far as educators are concerned. While some appear content to let students submit work produced however they see fit, others are taking a more determined approach. Professor Borcherds has clearly seen a change in scores as the use of AI among his math students has increased.

“Online exams are now a waste of time as several students just use AI to answer the questions. I cannot tell which students are using AI, but I notice the average score increases a lot in online exams.”

Borcherds explained that what he calls “grading for correctness” essentially pushes students towards using AI. They’re employing a tool that can be guaranteed to produce the correct answer.

“Grading for correctness just adds a huge incentive for them to use AI for homework instead of doing it themselves and penalizes students for honesty. And paying to grade AI generated answers is a waste of time and money.”

Difficult assessments

Other educators have expressed similar concerns about AI, although to date none seem to have taken Borcherds more traditional stance on the technology. Some have found, however, that giving students the time and space to use AI has skewed their results, and limiting access to the technology provides more realistic grades.

Berkeley has previous explored the use of AI detection and found it lacking. By putting its professors in charge of determining departmental expectations of AI use in students, the university has given its educators the power to expect better from their students.

Professor Borcherds could be set to lead the way on this, and perhaps once this story attracts attention, more educators will take a stronger view of AI assistance in homework and assessments.

Via New York Post

Looking for a different day?

A new NYT Strands puzzle appears at midnight each day for your time zone – which means that some people are always playing 'today's game' while others are playing 'yesterday's'. If you're looking for Friday's puzzle instead then click here: NYT Strands hints and answers for Friday, October 30 (game #971).

Strands is the NYT's latest word game after the likes of Wordle, Spelling Bee and Connections – and it's great fun. It can be difficult, though, so read on for my Strands hints.

Want more word-based fun? Then check out my NYT Connections today and Quordle today pages for hints and answers for those games, and Marc's Wordle today page for the original viral word game.

SPOILER WARNING: Information about NYT Strands today is below, so don't read on if you don't want to know the answers.

NYT Strands today (game #972) - hint #1 - today's themeWhat is the theme of today's NYT Strands?

• Today's NYT Strands theme is… It’s in the bag

NYT Strands today (game #972) - hint #2 - clue words

Play any of these words to unlock the in-game hints system.

• STEAK
• FISH
• CITY
• SANDY
• PLAICE
• TRICK
• RICE

NYT Strands today (game #972) - hint #3 - spangram lettersHow many letters are in today's spangram?

• Spangram has 12 letters

NYT Strands today (game #972) - hint #4 - spangram positionWhat are two sides of the board that today's spangram touches?

• First side: left, 3rd row

• Last side: right, 4th row

Right, the answers are below, so DO NOT SCROLL ANY FURTHER IF YOU DON'T WANT TO SEE THEM.

NYT Strands today (game #972) - the answers

(Image credit: New York Times)

The answers to today's Strands, game #972, are…

• TOOTHBRUSH
• FANGS
• RING
• CANDY
• APPLE
• STICKER
• SPANGRAM: TRICKORTREAT

• My rating: Easy
• My score: Perfect

Without meaning to I collected the top three treats and then the bottom three treats — all neatly divided by the spangram.

The first word I spotted was TOOTHBRUSH, so I momentarily thought we could be looking for items that might make their way into a wash bag; my second word, FANGS, soon stopped that theory (as did today’s date!)

Here’s hoping you have a spooktacular Halloween.

Yesterday's NYT Strands answers (Friday, October 30, game #971)

• JUICE
• ELECTRICITY
• POWER
• ENERGY
• SPARK
• CURRENT
• SPANGRAM: PLUGGEDIN

What is NYT Strands?

Strands is the NYT's not-so-new-any-more word game, following Wordle and Connections. It's now a fully fledged member of the NYT's games stable that has been running for a year and which can be played on the NYT Games site on desktop or mobile.

I've got a full guide to how to play NYT Strands, complete with tips for solving it, so check that out if you're struggling to beat it each day.

Looking for a different day?

A new Quordle puzzle appears at midnight each day for your time zone – which means that some people are always playing 'today's game' while others are playing 'yesterday's'. If you're looking for Friday's puzzle instead then click here: Quordle hints and answers for Friday, October 30 (game #1740).

Quordle was one of the original Wordle alternatives and is still going strong now more than 1,500 games later. It offers a genuine challenge, though, so read on if you need some Quordle hints today — or scroll down further for the answers.

Enjoy playing word games? You can also check out my NYT Connections today and NYT Strands today pages for hints and answers for those puzzles, while Marc's Wordle today column covers the original viral word game.

SPOILER WARNING: Information about Quordle today is below, so don't read on if you don't want to know the answers.

Quordle today (game #1741) — hint #1 — VowelsHow many different vowels are in Quordle today?

• The number of different vowels in Quordle today is 3*.

* Note that by vowel we mean the five standard vowels (A, E, I, O, U), not Y (which is sometimes counted as a vowel too).

Quordle today (game #1741) — hint #2 — repeated lettersDo any of today's Quordle answers contain repeated letters?

• The number of Quordle answers containing a repeated letter today is 1.

Quordle today (game #1741) — hint #3 — uncommon lettersDo the letters Q, Z, X or J appear in Quordle today?

• Yes. One of Q, Z, X or J appears among today's Quordle answers.

Quordle today (game #1741) — hint #4 — starting letters (1)Do any of today's Quordle puzzles start with the same letter?

• The number of today's Quordle answers starting with the same letter is 0.

If you just want to know the answers at this stage, simply scroll down. If you're not ready yet then here's one more clue to make things a lot easier:

Quordle today (game #1741) — hint #5 — starting letters (2)What letters do today's Quordle answers start with?

• A

• S

• C

• R

Right, the answers are below, so DO NOT SCROLL ANY FURTHER IF YOU DON'T WANT TO SEE THEM.

Quordle today (game #1741) — the answers

(Image credit: Merriam-Webster)

The answers to today's Quordle, game #1741, are…

• ANIME
• SWARM
• CHALK
• RAJAH

A very rare appearance from the letter J in the middle of a word, today.

If it wasn’t for the letter H, I probably would have guessed “ragga” first but although it felt risky I couldn’t think of anything other than RAJAH.

Daily Sequence today (game #1741) — the answers

(Image credit: Merriam-Webster)

The answers to today's Quordle Daily Sequence, game #1741, are…

• WARTY
• CASTE
• SUGAR
• FLUNK

Quordle answers: The past 20

• Quordle #1740, Friday, 30 October: ULCER, DIMLY, BRAIN, BEGUN
• Quordle #1739, Thursday, 29 October: PRUDE, MINUS, SAVOY, USHER
• Quordle #1738, Wednesday, 28 October: DEALT, FLUME, SLEEK, RELIC
• Quordle #1737, Tuesday, 27 October: ANKLE, HAVOC, SULKY, WHITE
• Quordle #1736, Monday, 26 October: ASSAY, GLEAM, MUCUS, WRING
• Quordle #1735, Sunday, 25 October: RAINY, BUSED, PROXY, UNDID
• Quordle #1734, Saturday, 24 October: TOXIN, SMART, MOUSE, STYLE
• Quordle #1733, Friday, 23 October: BLIMP, HOIST, FRIED, LURID
• Quordle #1732, Thursday, 22 October: DECAL, WIDTH, WOKEN, LEVER
• Quordle #1731, Wednesday, 21 October: MOIST, VALVE, VERSE, NORTH
• Quordle #1730, Tuesday, 20 October: COYLY, SAUNA, TRIAL, RASPY
• Quordle #1729, Monday, 19 October: EXIST, DECOY, HITCH, FLUID
• Quordle #1728, Sunday, 18 October: FLINT, FUROR, WEDGE, RODEO
• Quordle #1727, Saturday, 17 October: QUARK, ENEMY, SPASM, BLOCK
• Quordle #1726, Friday, 16 October: SHORT, WORTH, JOIST, SLUNK
• Quordle #1725, Thursday, 15 October: STALE, EPOCH, PIANO, CORNY
• Quordle #1724, Wednesday, 14 October: TIMID, GROUP, GRILL, EVERY
• Quordle #1723, Tuesday, 13 October: FLUFF, DEBUT, TEETH, STEIN
• Quordle #1722, Monday, 12 October: HELLO, BELOW, RIGHT, SLANT
• Quordle #1721, Sunday, 11 October: LILAC, INLET, TRIAD, SHAPE

Looking for a different day?

A new NYT Connections puzzle appears at midnight each day for your time zone – which means that some people are always playing 'today's game' while others are playing 'yesterday's'. If you're looking for Friday's puzzle instead then click here: NYT Connections hints and answers for Friday, October 30 (game #1237).

Good morning! Let's play Connections, the NYT's clever word game that challenges you to group answers in various categories. It can be tough, so read on if you need Connections hints.

What should you do once you've finished? Why, play some more word games of course. I've also got daily Strands hints and answers and Quordle hints and answers articles if you need help for those too, while Marc's Wordle today page covers the original viral word game.

SPOILER WARNING: Information about NYT Connections today is below, so don't read on if you don't want to know the answers.

NYT Connections today (game #1238) - today's words

(Image credit: New York Times)

Today's NYT Connections words are…

• STAYCATION
• GUITAR
• DIRTY
• KILLER
• SICK
• DOWNFALL
• SHAKEN
• UP
• TENNIS RACKET
• SHAKESPEARE
• WICKED
• TASSEL
• SITCOM
• MARIONETTE
• DRY
• GNARLY

NYT Connections today (game #1238) - hint #1 - group hints

What are some clues for today's NYT Connections groups?

• YELLOW: Confusing slang
• GREEN: Instructions for James Bond’s favorite cocktail
• BLUE: A twine in common
• PURPLE: Begin with canine control

Need more clues?

We're firmly in spoiler territory now, but read on if you want to know what the four theme answers are for today's NYT Connections puzzles…

NYT Connections today (game #1238) - hint #2 - group answers

What are the answers for today's NYT Connections groups?

• YELLOW: WORDS MEANING GOOD THAT SOUND BAD
• GREEN: MARTINI SPECIFICATIONS
• BLUE: THINGS WITH STRINGS
• PURPLE: STARTING WITH DOG COMMANDS

Right, the answers are below, so DO NOT SCROLL ANY FURTHER IF YOU DON'T WANT TO SEE THEM.

NYT Connections today (game #1238) - the answers

(Image credit: New York Times)

The answers to today's Connections, game #1238, are…

• YELLOW: WORDS MEANING GOOD THAT SOUND BAD: GNARLY, KILLER, SICK, WICKED
• GREEN: MARTINI SPECIFICATIONS: DIRTY, DRY, SHAKEN, UP
• BLUE: THINGS WITH STRINGS: GUITAR, MARIONETTE, TASSEL, TENNIS RACKET
• PURPLE: STARTING WITH DOG COMMANDS: DOWNFALL, SHAKESPEARE, SITCOM, STAYCATION

• My rating: Hard
• My score: 2 mistakes

I was on the right track with STARTING WITH DOG COMMANDS, as I saw the link between DOWNFALL, SITCOM and STAYCATION — but I thought KILLER was the fourth; something, in hindsight, that would take canine training to a whole new (and wrong) level.

After winning a Purple First for connecting the hardest group of the game, I made another error putting together the easiest/yellow group, including DIRTY among the WORDS MEANING GOOD THAT SOUND BAD.

After switching with GNARLY, another meaning for DIRTY came to mind and I was able to cobble together MARTINI SPECIFICATIONS.

Yesterday's NYT Connections answers (Friday, October 30, 2026, game #1237)

• YELLOW: PARTS OF A CAMERA: FLASH, LENS, SHUTTER, VIEWFINDER
• GREEN: AROUND A THEATER STAGE: BACKDROP, CURTAIN, PIT, WINGS
• BLUE: THROW____: HANDS, PILLOW, RUG, SHADE
• PURPLE: FRUIT WITH FIRST LETTER CHANGED: DEMON, DRAPE, GLUM, GRANGE

What is NYT Connections?

NYT Connections is one of several increasingly popular word games made by the New York Times. It challenges you to find groups of four items that share something in common, and each group has a different difficulty level: green is easy, yellow a little harder, blue often quite tough and purple usually very difficult.

On the plus side, you don't technically need to solve the final one, as you'll be able to answer that one by a process of elimination. What's more, you can make up to four mistakes, which gives you a little bit of breathing room.

It's a little more involved than something like Wordle, however, and there are plenty of opportunities for the game to trip you up with tricks. For instance, watch out for homophones and other word games that could disguise the answers.

It's playable for free via the NYT Games site on desktop or mobile.

The automaker must now obtain express consent before collecting or sharing driver data.

• LG Display is investing heavily in OLED production up to 111 inches
• Current LG OLEDs top out at 97 inches
• Today's 97-inch panel is much older tech than smaller panels

If you're looking for home theater-size OLED TVs, you'll soon encounter two hard limits: availability and affordability. You can't currently buy an OLED larger than 97 inches because nobody makes them.

And you probably can't afford a 97-inch OLED TV because it's terrifyingly expensive: today LG is listing its 97-inch OLED for $19,999 (reduced from $24,999) / £15,999. But it looks like both of those things are about to change.

LG Display is reportedly investing big money in big OLED, though: it and its partner Guangzhou Development Zone Holding Group are reportedly investing an extra 1 billion yuan to upgrade its production facilities for giant OLED displays.

As FlatpanelsHD reports, the market analysis company TrendForce says that the announced upgrades mainly target "large-size OLED module manufacturing, with products covering 77-inch, 83-inch, 97-inch, and 111-inch," with the ability to debut a 111-inch panel being a "major highlight of the project."

Bigger and potentially more affordable TVs are always welcome. But we do have some questions.

Hisense's massive mini-LED TVs are spectacular, and the 98-inch costs a fraction of what you'd pay for a same-sized OLED (Image credit: Future)What panel is LG intending to use?

The big question for us is whether the investment will mean improvements to the existing 97-inch panel's technology.

The 2026 version of LG's 97-inch OLED TV is a 4K native panel with a native refresh rate of 120Hz, but while the model is the LG G6, its panel is not the same as its smaller siblings: they all get LG's Primary RGB Tandem 2.0 panel, but the 97-inch is an older, non-Tandem panel — in fact it dates back to the LG G2 from 2022, so it's several generations behind. That means it isn't as bright and doesn't have the same color accuracy as the other models.

That difference is important, because these large OLEDs are up against some of the best mini-LED and increasingly, RGB mini-LED TVs — and those TVs are exceptionally bright and accurate as well as increasingly affordable. It's possible to buy high-quality 98-inch Hisense TV for just $3,999, which is a lot for a TV but not a lot for a 98-inch one — and is obvious just a fraction of the 97-inch OLED price.

We're keeping our fingers crossed here: if LG Display breaks the size barrier and makes ultra-large Tandem RGB TVs that are less expensive to manufacture, that'd be great. The worst case scenario is that we get the same kind of panel that's currently in the 97-incher, but a bit bigger — but it seems like that the aim is to upgrade the technology, given that production of smaller sizes was mentioned as a goal as well.

And that might be the bigger win from the project for most of us: if the project succeeds in making producing 111-inch OLED viable, and therefore improves the process and lowers the cost of 77-inch and 83-inch models too, that's probably the real benefit.

Thinking of buying a new TV?

Try our TV size and model finder! You tell it how far you sit from your TV, we'll tell you what size to buy based on viewing angle advice from image quality experts, and we'll recommend our three top TVs at that size for different prices.

• San Francisco lab Radical Numerics says its Omnii-1 model designed bacteriophages that were given to a patient with a drug-resistant infection, a world first
• The phages were built by rewriting the gene for T7's tail fiber, the protein the virus uses to latch onto bacteria
• Nobody outside the company knows whether it worked, because the results have not been published, peer-reviewed, or disclosed yet

Radical Numerics has announced its AI-designed viruses (bacteriophages) were given to a sick person, but has not provided much further insight about what happened next.

The San Francisco AI lab announced in October 2026 that bacteriophages designed by its new genome model had been administered to a human patient with an antibiotic-resistant bacterial infection, under a physician-led compassionate-use pathway authorized by the FDA.

If the claim holds, it is the first time an AI-designed organism of any kind has been put into a person as medicine.

Not a new phenomenon, but one that could do with AI assistance

Bacteriophages are viruses that infect bacteria and ignore human cells entirely. They have been used as therapy for more than a century, predating penicillin, and have enjoyed a quiet revival as antibiotics have begun to fail.

The World Health Organization considers phage therapy broadly safe, and unlike broad-spectrum antibiotics, a phage can target one bacterial strain while leaving the rest of your microbiome alone.

That precision is also the problem: each phage recognizes a narrow set of bacterial surface receptors, so treating a patient means finding one that matches their specific infection. Clinicians screen existing phage libraries, then environmental samples, then give up and try engineering as a last resort. For someone with sepsis, that search is not an academic exercise but an important life-or-death situation.

The scale of the underlying problem is not in dispute. The Global Burden of Disease project estimated that antimicrobial resistance was associated with roughly 4.7 million deaths in 2021, with projections indicating that between 2025 and 2050, close to 40 million deaths could be attributable to it.

Radical Numerics was founded by members of the team behind Evo and Evo 2, the Arc Institute genome models that generated the first entirely AI-written phage genomes. That earlier work produced 700,000 candidate genomes; 285 were synthesized, and 16 produced viable viruses. It was a proof of concept with a punishing, yet promising hit rate.

Omnii-1 is the follow-up, and the company's technical write-up describes a narrower, more surgical approach. Rather than inventing whole genomes, the model edits the targeting component. The team worked with T7, a well-characterized 40-kilobase E. coli phage, and rewrote gp17, the receptor-binding tail fiber.

The numbers the company is willing to share are genuinely interesting. At 11 to 15 amino acid changes from wild type, 69.9% of designed variants were recovered as viable phages, against 4.8% for random controls. Of 6,694 variants with measurable activity, 2,161 beat the original, including some carrying 28 amino acid substitutions.

A promising, but unproven and unpublished play

The company tested its designed cocktail against bacteria isolated from a real patient's infection, confirmed it eliminated that isolate in vitro, and then administered it. The patient reportedly had an E. coli infection that had resisted not only antibiotics but every available phage, which is effectively the worst position one can be in when it comes to infectious diseases.

Radical Numerics has since declined to describe the patient's clinical course, outcome, hospital, or physicians, citing patient privacy and the fact that even limited clinical detail could identify the patient.

The company self-published the technical report on its website and has not had it peer-reviewed, but has separately indicated the treatment is proprietary and something it hopes to commercialize.

That silence held as of October 29, nine days after the announcement, when trade coverage for infectious disease clinicians still reported no disclosed clinical course, no outcome, and no peer-reviewed publication. The technical write-up remains the only account of the case.

In fairness to Radical Numerics, its own write-up states plainly that single-patient observations cannot establish safety or efficacy, which is more cautionary than most product launches manage. CEO Eric Nguyen has also said the company intends to publish through peer review.

Outside experts have landed somewhere between intrigued and unconvinced, which is the correct place to land. Harvard microbiologist Michael Baym, who was not involved, said the result would be incredible if it works, but added that his instinct is skepticism until the treatment finishes and the viruses' novelty can actually be examined.

The commercial logic is much easier to establish; phage hunting is slow, and Radical Numerics believes it can compress design to days rather than months.

Ottawa Hospital infectious disease clinician Marisa Azad, who is collaborating with the company, has described the conventional search as remarkably time-consuming, and she is not wrong. If AI can reliably shorten that loop, it changes who gets treated in time, allowing for a more cost-effective and broader audience for said treatments.

There is cause for some concern too: a model that can design viruses to order is, structurally, a model that can design viruses to order. Radical Numerics acknowledges this directly by committing to biosafety, containment, and data-sharing measures scaled to the model's capability.

It is the same dual-use problem that has dogged every capable biological design tool, and one that AI labs have been publicly wrestling with as their systems get better at biology.

Engineered phages have reached patients before, most famously a 2019 case in which modified phages treated a disseminated drug-resistant Mycobacterium abscessus infection. What is new here is not the therapeutic concept but the design process, and the governance questions attach to the AI-driven process, not the concept itself.

AI has moved from reading biology to writing it and handing the result to a doctor. That is a different category of claim than an AI model proposing a cancer hypothesis or outperforming specialists on rare-disease diagnosis, both of which keep a human firmly in the loop before anything enters a bloodstream.

For now, however, a very clever experiment was run on a very sick person, and we still don't know how it went or when somebody decides to tell us. If it does pan out however, it will have massive rammifications for an industry that is only expected to grow across the next few decades.

• Fujifilm plans to multiply magnetic tape production fivefold by fiscal 2028
• The company is committing ¥10 billion ($63.3 million) to its Odawara plant expansion
• Offline tape copies can reduce exposure to remote cyberattacks on networked systems

Fujifilm has revealed plans to increase its magnetic tape production capacity fivefold by fiscal 2028 in response to rising data storage demands driven by AI.

The Japanese company has allocated ¥10 billion ($63.3 million) to expand its Odawara plant near Tokyo, marking its largest investment in tape production for approximately 20 years.

The project will concentrate on advanced cartridges capable of retaining up to 100TB, although Fujifilm has not disclosed its expected annual output following expansion.

Magnetic tape finds renewed purpose as AI data volumes surge

Magnetic tape remains commercially useful because organisations can store enormous quantities of information without keeping the medium continuously connected to computer networks.

Data centres, financial institutions and research organisations use it to preserve backups, particularly when information must remain available for years rather than immediate retrieval.

The technology dates back decades, with Fujifilm beginning development in 1954 for television broadcasting equipment before expanding into audio and video recording applications.

A 2026 IDC survey found that 94.7% of organisations reported storing larger volumes of information after adopting artificial intelligence technologies across their operations.

It also estimates that global data generation could reach 718 zettabytes by 2030, approximately four times the 2024 volume.

Each zettabyte represents one billion terabytes, indicating the scale of storage capacity potentially required as digital activity expands.

Magnetic tape can help accommodate this growth by providing a relatively inexpensive way to retain large volumes of data offline for extended periods, without occupying costly high-speed storage.

Tape also offers protection against certain cybersecurity incidents because stored cartridges can remain disconnected from operational systems.

Keeping copies offline can reduce their exposure to remote attacks, although physical damage, mishandling and other risks remain possible.

Rising drive prices improve magnetic tape's cost advantage

The economics of competing storage technologies have strengthened tape's appeal as semiconductor shortages push up SSD prices and data centre demand increases pressure on hard-disk drive supplies.

According to Fujifilm’s analysis with Brad Johns Consulting, tape storage costs about 1 cent per GB, compared with 3–3.5 cents per GB for raw HDD storage.

This implies that storing 100 TB of data on magnetic tape costs approximately $1,000, compared with $3,000 to $3,500 using HDDs, potential savings of about 67–71%.

Japanese companies are now investing across several storage technologies, suggesting that they expect continued demand for different capacities, speed, and cost.

Kioxia plans to invest ¥5 trillion (~$37 billion) alongside American partner Sandisk over six years, to expand semiconductor memory production.

Toshiba intends to spend approximately ¥60 billion (~$380 million) enlarging its Philippine hard-drive factory, to double manufacturing capacity.

Hoya plans a ¥50 billion (~$317 million) investment in Vietnam for glass substrates used in hard drives, while NHK Spring has outlined an additional ¥35 billion (~$222 million) in production spending.

These investments indicate that magnetic tape's renewed appeal coincides with expansion elsewhere in the storage market, rather than a retreat from SSDs or HDDs.

Via Nikkei Asia

You’ll get two Pokemon cards and one toy with each Happy Meal.

There are only so many ways I can say how good the SteelSeries Arctis Nova Elite is, but perhaps the simplest way is the best: it is the greatest gaming headset I have ever tested and reviewed.

Yup, it still looks very familiar, and very SteelSeries Arctis on the outside, but this headset is like no other in the brand's lineup, or the wider market. Everything, every minute detail, has had time and consideration poured into it, and it really is the fullest realization of what a gaming headset can be, and a natural winner at the TechRadar Product of the Year Awards 2026.

First and foremost, as I laid out in my full SteelSeries Arctis Nova Elite review, it's got that brilliant out-of-the-box SteelSeries audio — but not quite as we all know it. The brand-new custom-made carbon fiber audio driver, held in place by a brass surround ring, makes for a different, but still breathtaking, flavor.

Combine that SteelSeries Arctis tuning with the new hardware combination, and you get unbelievable immersion, supremely accurate sound reproduction of anything and everything, and excellently rich and detailed certified Hi-Res Audio for a wireless gaming headset.

(Image credit: Future/Rob Dwiar)

While I could talk about the audio alone for ages, the Elite backs up its brilliant sound with a faultless feature set.

Firstly, building on the brilliant DAC unit the Arctis Nova Pro headsets introduced, the Elite's GameHub with OmniPlay means you can be connected to every platform type, basically simultaneously.

It's fabulous. Utilizing this, as well as the headset's Bluetooth connection, you can actually connect to up to four different sources, and mix and listen to them altogether. You might never need four, but being connected to my console and PC, and having Bluetooth on to take phone calls, has been really useful for me.

You've got two different microphone modes (a retractable boom, which is fantastic quality, and built-in ones for convenience), the 'infinite' battery supply due to a spare being charged in the GameHub all the time, and a host of EQ and other controls in the GameHub.

The Nova Elite feels fantastically premium, and joyous to wear and use. The cold-rolled steel and aluminum materials are superb, the leatherette cushions are sublime, the metallic volume wheel is a tiny but glorious touch, and every button and material finish feels worthy of the headset's lofty price tag.

Other headsets might tickle different fancies, or appeal to different priorities that folks might have; but for anyone looking for a premium, do-it-all headset for all of their devices that excels in every way, it has to be the SteelSeries Arctis Nova Elite. You simply will not find a better headset offering the same combination of design, features and audio quality. Buy it, and you will never look back.

Samsung’s advertisement features a sliced green apple that rolls right along through the entire Galaxy Z Fold line.

After a week of nonstop folding, we briefly turn the iPhone Duo’s display off to check out how the crease looks.

So you've got your water, cash, canned food, and a wind-up radio, but something is missing from your prepping supplies. If the power goes out and your water supply is cut, how will you make your morning coffee? Put down that jar of instant granules — basic services might have failed, but your tastebuds haven't.

Drip coffee is an easy way to perk yourself up and boost your morale in a crisis (just pick up a ChemEx brewer or a simple dripper with some filter papers), but if you're aiming to conserve water then a shot of espresso is a better way to get your caffeine fix, so here I've focused on brewers for preparing shorter drinks.

Consider how you're going to store your emergency coffee supply, too. Whole beans will hold their flavor better than ground, and I recommend keeping them in an opaque, airtight container in a cool place (light, heat, air, and moisture are the enemies of aroma compounds). You'll need a grinder, too — look for one with burrs rather than blades so your coffee isn't chopped up in rough pieces.

If all that sounds like too much hassle in a crisis, opt for foil-sealed coffee pods instead. Both the Nanopresso and Dreame Ecceluxe Go below have adapters for brewing with single-serve capsules.

The Ecceluxe Go heats its own water, but if you pick a more basic brewer then you'll need a different way to get it up to temperature. As the former editor of an outdoor gear website, I recommend a simple gas camping stove like the MSR Pocket Rocket 2, which will get your water up to around 203F / 95C in approximately 3.5 minutes. Now, onto the brewers...

Wacaco NanoPressoFutureFutureWacaco NanopressoFutureWacaco Nanopresso

No power? No problem. The Wacaco Nanopresso generates up to 18 bars of pressure using nothing but elbow grease. It's small enough to tuck inside a pocket, and is hand-powered, so all you need is a source of hot water to create properly extracted espresso with thick crema (even if you have to use a flashlight to see what you're doing).

The standard Nanopresso uses ground coffee, which you can tamp down using the scoop (the brewer has a valve to release pressure if you accidentally tamp it too hard), but if you'd rather use pods then the NS adaptor allows you to use Nespresso Original style capsules instead.

It feels robust and solid in the hand, and is packed with thoughtful little features like an insulated water tank and cup to protect your hands from heat, and an easy-clean portafilter that needs minimal maintenance.

Dreame Ecceluxe GoFutureFutureFutureFutureFutureFuture

The Dreame Ecceluxe Go is a battery-powered brewer with a miniature boiler built-in. Just pour room-temperature water into the reservoir on top (measuring lines engraved inside will prevent you overfilling it and wasting precious resources), then pick the right adapter — Nespresso Original, Nestlé Dolce Gusto, ESE (Easy Serve Espresso), or fresh grounds — and you're ready to brew.

Preparing an espresso with room temperature water takes about six minutes from start to finish, and you can prepare two or three drinks before the Ecceluxe Go needs recharging (from a portable battery or solar generator during a power outage). The brew unit itself is smaller than a thermos flask, and comes in a compact carry case that you can tuck away with the rest of your emergency supplies.

The Dreame Ecceluxe Go is due to go on sale in Spain and Portugal very soon, with the US following shortly after. There's no plan for a UK launch yet, but it charges via USB-C, so there's no reason British preppers can't import one.

AeroPress and Manual Coffee GrinderFutureFutureFutureFutureFuture

If you're planning to keep whole coffee beans in your emergency supplies, you need the AeroPress Manual Coffee Grinder. I've tested a lot of manual grinders in my time, and this is easily the best. It has proper burrs rather than cheap blades so coffee is ground rather than shredded, and they're adjustable so you can optimize the grind size to suit your brewing method.

The default setting is optimized for the AeroPress brewer, which you can use to make a short, strong shot of coffee to keep you awake, or a longer, smoother drink if you have water to spare. I have a plastic AeroPress in my locker at work (you never know what might happen), but if you want something extra tough then take a look at the rugged AeroPress Steel. If you're part of a whole family of coffee-lovers there's also the king-sized AeroPress XL, and if you need something you can also use on the road, the bijou AeroPress Go packs down into a compact travel cup.

• DT Research unveils the LT365PA, a 15.6-inch rugged laptop offering Nvidia RTX A2000 or RTX 5000 Ada graphics
• It targets crime scene, crash reconstruction, and command post work, and reaches resellers worldwide in Q1 2027 but has no published price yet
• Much of the design carries over from 2023's LT355, and PNY lists an end-of-life window for RTX A2000 modules in that same quarter

Police crash investigators could soon be processing 3D scans and drone footage at the roadside instead of back at the station, if DT Research gets its way.

The California company has unveiled the LT365PA, a 15.6-inch rugged laptop with optional discrete Nvidia graphics, aimed at crime scene investigators, crash reconstruction teams, and military command posts.

The pitch for potential customers is simple enough: the ability to crunch video, drone imagery, 3D scans, and sensor feeds where the data is collected, rather than waiting on a network connection or a distant data center.

A workstation GPU in a rugged shell

The official DT Research's product page says the LT365PA runs on an Intel Core Ultra 5 225H or Core Ultra 7 255H with 16GB to 32GB of LPDDR5 memory, up to 2TB of storage, and Windows 11 IoT Enterprise.

The 15.6-inch touchscreen is rated at 1,200 nits, with a 4K panel and two MIL-STD-3009 Class B night-vision displays (one for naked-eye use, one for night-vision goggles) available as options. The chassis is IP65 rated and MIL-STD-810H certified, and a CAC reader, RFID and NFC readers, GPS, 4G LTE, and a NIST-compliant BIOS round out the extras public-sector buyers often tend to prefer.

DT Research offers an Nvidia RTX A2000 or what it calls an "RTX 5000A," which appears to be the Ada Lovelace-based RTX 5000 Ada Generation. The gap between the two is large: PNY's embedded MXM line card lists the A2000 module with 2,560 CUDA cores and 8GB of memory, while the RTX 5000 Ada has 9,728 CUDA cores and 16GB at a 115W power rating, giving it more than four times the peak FP32 throughput.

That GPU does most of the AI processing in DT Research's pitch; the NPU inside Intel's Arrow Lake-H chips is rated at just 13 TOPS, as we noted when Intel announced the family, so the heavy video analytics and 3D work DT Research describes will fall to the Nvidia silicon.

Same premise, a different model number and upgrades under the hood

Agencies with long memories may recognize the LT365PA. DT Research's LT355, launched in 2023, was also a 15.6-inch rugged laptop with a 1,200-nit screen and embedded Nvidia RTX A1000 or A2000 graphics, and it too was pitched to law enforcement and the military. At the time, Tsai said DT Research had listened to customers and "developed the next version of our rugged laptop to include an NVIDIA graphics card."

Compare the two spec sheets side by side, and a lot carries over: display brightness, the night-vision options, the operating temperature range, the enclosure materials, and the ratings of the hot-swappable battery packs are identical, and the GPU version still ships with a 230W power adapter.

What has changed is the newer Intel platform, the RTX 5000 Ada option, a 1.1lb (0.5kg) weight saving, and 4K and IR camera options. There is a step back, too, at least on paper: the LT355's two memory slots supported up to 64GB, while the LT365PA tops out at 32GB of LPDDR5.

"Today's field teams need the same high-performance AI computing capabilities at the edge," DT Research president Daw Tsai said in the company's announcement, which says the LT365PA will reach authorized partners and resellers worldwide in the first quarter of 2027. Pricing has not been disclosed.

A crash investigation pitch is arguably the most persuasive part of DT Research's launch. According to the Federal Highway Administration, "every minute of incident delay multiplies traffic queues by a factor of four," and the likelihood of a secondary crash climbs 2.8% for each minute the original incident remains a hazard. Anything that lets investigators confirm their scans and photos are complete before a road reopens has real value.

Despite leaning on such a specific example, the laptop itself doesn't capture anything. Laser scanners and drones do that, and DT Research names no software partners or processing-time figures to show how much faster the LT365PA makes the job.

There are practical trade-offs as well. At 8.6lb (3.9kg), the LT365PA is heavier than our top-rated rugged laptop, the Panasonic Toughbook 40, at 7.4lb, and its IP65 rating is a notch below the IP66 rating of the Toughbook 40 and Getac's B360X lineup. DT Research cites MIL-STD-810H for shock and vibration but publishes no drop height or a fuller list of test methods, whereas Durabook itemizes a long list of 810H tests behind the Z14I-DX3, from altitude to explosive atmosphere.

DT Research also publishes no battery life figure. The two standard packs work out to roughly 123Wh combined, and the GPU model ships with a 230W adapter, nearly double the 120W unit supplied with the standard version, which suggests those hot-swappable batteries will earn their keep under sustained GPU load.

Whether US police forces actually get this upgrade is a separate question. As MIT Technology Review's James O'Donnell has written, "police departments in the US have extraordinary independence," with more than 18,000 of them each deciding what technology to buy, so there is no single customer to win here.

The AI angle deserves a bit of pushback: DT Research pitches on-device video analytics without saying which applications it has validated or tested against, and that is where police technology matters most. The same MIT Technology Review reporting covered an AI tool that tracks people by clothing and body attributes in a way that sidesteps local facial recognition bans. The LT365PA is only hardware, but what agencies run on it will determine how welcome it is.

For crash and forensic teams still working on 2023-era gear, an LT365PA with the RTX 5000 Ada would be a genuine step up. The RTX A2000 version is a far more modest refresh, however, and with shipments not starting until 2027 and procurement cycles to follow, most investigators will not be unpacking one for a while yet.