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Generic AI tools promise to solve every problem under the sun, from running enterprise CRM to analysing why your cat isn't drinking enough water during a heatwave. And when you try to use one tool with no defined role for every task, results are disappointing and erode trust in technology.

Multiply that pattern across hundreds of employees, and you get tokenmaxxing: prompt after prompt, refining AI output until something usable comes out.

Some organizations, by instinct, default to blaming the employees for tokenmaxxing, or double down on training on ‘responsible use of AI’.

Tokenmaxxing is a symptom of capable people having to create solutions in an environment that lacks clear shape, scope, guardrails - and ways to analyze spend and outcomes.

Locking it down is not the solution

Traditional procurement systems were designed for traditional business software cycles. If building an enterprise system takes years, it’s not a big deal if procuring the right vendor takes years, too.

Routing AI through procurement to evaluate all options and keep the spend predictable initially felt to organizations like a safe and responsible choice. But software creation is very different today than it was even 5 years ago. Standard IT procurement still takes months, while opening a public LLM chatbot and asking it to generate a landing page is a matter of five seconds.

Policies tend to live their happy lives somewhere in the corporate portals, unbothered and forgotten unless an incident calls for a formal investigation. And when the approved systems are slow or restrictive, employees find workarounds. They turn to unvetted shadow AI tools for daily tasks and put proprietary corporate data into public models.

Look at the app prototypes that come out of it: the bad code is one problem, but the interfaces are off-brand, ignore corporate design systems and WCAG 2.2 accessibility rules, and lack basic authentication patterns.

Restricting AI use for employees in reality means they pay the £18 monthly subscription out of pocket and still use it. It moves the spend somewhere finance can't see it, at least not immediately and not until it’s too late, adding a data governance problem on top.

The other consequence is harder to put on a balance sheet. A company where only engineers can create software moves at the speed of engineering's queue, but opening options up to a wider group - product management, analysts, marketers - means a company can speed up innovation while having greater visibility into it.

The cost of ungoverned building

The pressure is already on. Teneo's Vision 2026 survey of more than 350 public company CEOs and 400 institutional investors found that 53% of investors expect to see a positive ROI on new AI initiatives in six months or less, while only 16% of large-cap CEOs believe they can deliver on that timeline. The same CEOs report that fewer than half of their current AI projects are ROI-positive. Investors want returns on a clock that executives don't think they can meet.

Volume is not the problem. Goldman Sachs Research forecasts that token consumption will multiply 24 times, to 120 quadrillion tokens per month, between 2026 and 2030, while semiconductor providers are already delivering 60% to 70% annual declines in cost per token. Tokens are getting cheaper, and we are going to use far more of them.

But who - or what - uses tokens is going to change. Organizations are building and deploying AI agents who act on their own. And agentic AI burns far more tokens than good old human prompting, because the queries repeat in sequence: a chatbot request multiplied by 20, or even 50, running unattended. Send an agent to work on an unscoped problem, and it will keep going long after a human would have stopped to ask whether this was worth it.

A lot of those tokens go into prototypes that never get to see the real world. Prototyping and sifting through ideas is how software evolves, but building with no eye on production drains resources. Gartner found that at least 50% of generative AI projects were abandoned after proof of concept by the end of 2025, citing poor data quality, inadequate risk controls, escalating costs, or unclear business value. If a prototype works in isolation but has to be scrapped because engineering would need to rebuild it from scratch, that's pure waste.

Then organizations have to pay the bill twice - for inflated tokens and lost engineering hours. When teams build with generic LLMs and no guardrails, senior engineers spend hours cleaning up the output. That deepens the trust gap in technical teams. Stack Overflow's 2025 developer survey found that 46% of developers distrust the accuracy of AI output. "Almost right" (but not quite) AI answers are the biggest frustration for 66% of developers, while 45% report that debugging AI-generated code is more time-consuming.

Access for everyone, accountability from everyone

The speed of code generation isn't the problem. Lowering the technology barrier for non-engineers produces better software, software shaped by the people who understand the business need. AI building is an edge, and an edge works best when everyone has it.

But alongside democratized access to technology, we need new ways to think about accountability for how you use it and the associated costs. Modern corporate culture can promote unnecessary complexity in how we think and speak about our work. Being able to explain in simple words how you spent your day is a useful exercise, and we should apply the same thinking to AI spend.

So, stated plainly: tokens should be used for a job somebody actually needed. In turn, the user needs to be able to explain, beyond the buzzwords, what the purpose was behind a particular token spend.

To work, rather than become another source of corporate frustration, this accountability needs to be part of the environment offered. One way to start is to retire the do-everything chat box as the default. Instead, organizations should start thinking about how to give people task-specific agent workflows tailored to their roles, and build execution limits into the software environment.

This way, non-technical staff get brand guidelines, fonts, security rules, and components pre-coded into the environment, so the apps they build are compliant and production-ready by default. They don’t need to file separate requests because the shape of the environment already includes the right guardrails on security and spend.

What it looks like when it works

Bounded workflows pay off in ways you can measure. In a recent mid-sized company implementation, a 3-person data analytics team built an agent that analyses data across all their systems; it saved each of them 12 to 13 hours of manual work a week.

Three analysts now produce what once took a team ten times their size, and their daily job also got way more interesting. They spend their time on high-value strategy instead of gathering data by hand.

That agent has a clearly scoped job and executes it in line with pre-defined parameters - it is not a chat box with a company credit card.

Bringing together abundance and accounting

Uncontrolled AI costs and falling trust in technology have the same solution, and it is not rationing of tokens. Tokens will be getting ever cheaper, and their abundance is the point of this technology.

The answer is in defining and understanding the scope of AI. Give everyone the tool but make it purpose-specific from the start rather than a generic catch-all.

Every company I talk to can tell me what it spent on AI last quarter, but when I ask what they wanted to get in return, the answer is murky.

This lack of understanding of what job AI should do for an organization is the problem, and the surprising bill is only its symptom. The first step is for the organization to articulate, in the plainest words possible, what the tools are for before the tokens start moving.

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• Anthropic is expanding Claude's role across several stages of drug development
• Generate Biomedicines reports a 70% reduction in CAR T-cell component length
• Modified immune cells produced roughly ten times more cancer-detecting receptors

Anthropic is expanding Claude’s involvement in pharmaceutical research, working with biotechnology developers on projects intended to accelerate the creation of new medicines.

The AI company has laid out in a new blog post how it is examining scientific and administrative obstacles affecting drug development, from molecular design to clinical trial preparation.

Its collaborations involve potential treatments for cancer, food allergies and rare muscular disorders, although most of the treatments remain at experimental stages.

Claude enters drug development programmes

At Generate Biomedicines, six scientists used Claude Code to modify a component of CAR T-cell therapy, traditionally employed against blood cancers.

Their work sought to create additional room for genetic instructions that could help the treatment address solid tumours.

The redesigned component was approximately 70% shorter, while laboratory experiments found that immune cells produced roughly ten times more receptors.

The modified cells also destroyed cancer cells more effectively and maintained their activity for longer periods, according to the reported findings.

Divergence Labs used Claude to develop antibody candidates for a potential food-allergy treatment involving the immune molecule IgE.

The system generated approximately 35,000 molecular designs within one month, producing potential molecules for both functions required by the proposed treatment.

Initial experiments identified three designs capable of binding to IgE and another 20 capable of detaching it from immune cells.

Three of the 20 designs appeared more effective than the standard medication at removing IgE from immune cells.

BigHat Biosciences combined Claude with automated laboratory equipment to improve two antibody fragments being considered for future medicines.

Researchers manufactured and tested approximately 1,010 variations over ten weeks, examining binding strength, stability and unwanted molecular aggregation.

The strongest cancer-targeting version bound its intended target more than 10 times as tightly and retained stability at temperatures 18°C higher than the original.

The other fragment, intended for longer-lasting medicines, aggregated more than 100 times more slowly than its original version.

Enveda applied Claude to manufacturing documentation, which had consumed up to 75% of some chemists’ working time.

During an assessment spanning 1,061 pages, the system identified all 11 problems previously discovered by human reviewers, as well as seven additional issues.

The approach reduced manual checking time by 89%, bringing the review process from more than 25 hours to under three.

Anthropic expands into clinical research and drug creation

Anthropic has also partnered with Bristol Myers Squibb to assess clinical study plans and estimate their chances of success.

Michael Pourdehnad, the pharmaceutical company's senior vice president for early clinical development, said: “From a single prompt, Claude generated a robust initial analysis.”

He explained that this helped evaluate development options that would otherwise have required several days of work.

The companies intend to extend their collaboration further, examining Claude’s potential contribution to decisions during early clinical development.

Anthropic says working directly with drug developers helps identify weaknesses in its models and opportunities for improvement across scientific research.

The company also intends to extend Claude's involvement through additional partnerships, research programmes and tools for life-science organizations.

• Chinese researchers report 3.2 Pb/s transmission across a 24-core optical fiber
• Spatial division multiplexing carries separate data streams through one fiber
• S+C+L transmission uses three wavelength bands to carry information

Researchers in China say they have transmitted data at 3.2 Pb/s through a 24-core optical fiber, setting a new real-time speed record.

At that capacity, data equivalent to thousands of ultra-high-definition films could theoretically move through the connection in just one second.

The new figure exceeds the team's previous 2.5 Pb/s record, set earlier this year using similar 24-core fiber technology.

How the researchers reached 3.2 Pb/s

The project brought together specialists from the National Key Laboratory of Optical Communication Technology, China Information and Communication Technologies Group, Pengcheng Laboratory, and Fiberhome Fujikura Fiber Optic Technology.

Their system combined spatial division multiplexing with S+C+L multi-band transmission, two methods intended to increase information carried through existing optical infrastructure networks.

Spatial division multiplexing separates information into distinct channels within one fiber, allowing multiple independent data streams to travel simultaneously through the cable.

The S, C and L bands use different wavelength ranges, enabling transmission across a wider section of the optical spectrum.

Combining the techniques created engineering difficulties, particularly interference between neighbouring channels carrying simultaneous signals through the fibre network and equipment.

The team also had to manage differing specifications across the three wavelength bands without allowing those variations to undermine transmission performance.

The test hit record figures with hardware architectures described as compliant with commercial requirements and operated continuously in real time.

That operating condition distinguishes the result from demonstrations relying on experimental equipment or signal-processing arrangements developed specifically for laboratory research.

The Hubei provincial government website compared the capacity with internet access for approximately 3.2 million households using separate 1 Gbps connections simultaneously.

The report describes the rate as sufficient to download “more than 20,000 4K movies” within one second, under ideal conditions.

These comparisons describe theoretical network capacity, rather than evidence that individual households could receive such speeds through ordinary broadband subscriptions.

The gap between commercial hardware and laboratory records

The new figure does not represent the highest speed reported for transmission through a 24-core optical fibre.

Laboratory research has reached 5.29 Pb/s using comparable multi-core fiber, exceeding the Chinese group's latest result by over two petabits.

Those experiments, however, may depend on advanced processing methods and specialist laboratory equipment that remain unsuitable for routine network deployment.

The Chinese group’s reported use of commercially compliant hardware is a significant feature of its claim, although it does not establish immediate commercial availability.

A successful real-time demonstration alone cannot confirm long-term reliability, affordable operation or compatibility with existing telecommunications infrastructure under demanding operating conditions.

At the moment, there is no official deployment schedule, pricing information or independent assessment of performance during sustained operation under everyday network conditions.

Thus, there is no certainty that the technology can move beyond controlled testing into dependable telecommunications networks serving customers at scale.

However, the research has shown that combining multiple fiber channels and wavelength bands can deliver substantial capacity under practical test conditions.

Via Tom's Hardware

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 Sunday's puzzle instead then click here: Quordle hints and answers for Sunday, November 1 (game #1742).

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 #1743) — hint #1 — VowelsHow many different vowels are in Quordle today?

• The number of different vowels in Quordle today is 4*.

* 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 #1743) — hint #2 — repeated lettersDo any of today's Quordle answers contain repeated letters?

• The number of Quordle answers containing a repeated letter today is 2.

Quordle today (game #1743) — 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 #1743) — 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 2.

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 #1743) — hint #5 — starting letters (2)What letters do today's Quordle answers start with?

• E

• A

• L

• E

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

Quordle today (game #1743) — the answers

(Image credit: Merriam-Webster)

The answers to today's Quordle, game #1743, are…

• EXTRA
• AMITY
• LUPUS
• EAGLE

It didn’t take me very long to work out that my final word contained two letter Us, but I really struggled to stop thinking about humus and finally get to LUPUS.

This was also a game that featured the rare letter X, although deciding on EXTRA was fairly easy once the start and ending letters had been revealed.

Daily Sequence today (game #1743) — the answers

(Image credit: Merriam-Webster)

The answers to today's Quordle Daily Sequence, game #1743, are…

• THIRD
• GOING
• SNAIL
• SOOTH

Quordle answers: The past 20

• Quordle #1742, Sunday, 1 November: DROVE, PRIED, SHELL, BEGIN
• Quordle #1741, Saturday, 31 October: ANIME, SWARM, CHALK, RAJAH
• 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

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 Sunday's puzzle instead then click here: NYT Strands hints and answers for Sunday, November 1 (game #973).

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

• Today's NYT Strands theme is… High and mighty

NYT Strands today (game #974) - hint #2 - clue words

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

• MULE
• FILE
• SNARE
• RACE
• TIME
• DATE

NYT Strands today (game #974) - hint #3 - spangram lettersHow many letters are in today's spangram?

• Spangram has 11 letters

NYT Strands today (game #974) - hint #4 - spangram positionWhat are two sides of the board that today's spangram touches?

• First side: bottom, 1st column

• Last side: top, 6th column

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

NYT Strands today (game #974) - the answers

(Image credit: New York Times)

The answers to today's Strands, game #974, are…

• CLIFF
• SNOW
• GLACIER
• PEAK
• RIDGE
• SADDLE
• SUMMIT
• SPANGRAM: MOUNTAINTOP

• My rating: Easy
• My score: Perfect

I love how today’s spangram jaggedly rises from one corner to the other.

However, despite my enjoyment of some top-level Strands craft I still managed to miss out on spotting it. Instead, I began with the game’s two most obvious words in CLIFF and PEAK.

The closest I’ve got to a MOUNTAINTOP is snowmobiling on a GLACIER in Iceland — an experience that was both exciting and terrifying, not least the moment when our guide pointed out a 120ft-deep crevasse we were inches away from falling into. I’m still having the nightmares.

Yesterday's NYT Strands answers (Sunday, November 1, game #973)

• SNOOZE
• SLEEP
• CATNAP
• DOZE
• SLUMBER
• DROWSE
• SPANGRAM: ZZZZZZZZ

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 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 Sunday's puzzle instead then click here: NYT Connections hints and answers for Sunday, November 1 (game #1239).

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 #1240) - today's words

(Image credit: New York Times)

Today's NYT Connections words are…

• MEDICINE CABINET
• COMPASS
• FOG MACHINE
• INCENSE
• WATERFALL
• DISCO BALL
• NETTLE
• HIKING BOOTS
• DRESSING ROOM
• DRY ICE
• WATER BOTTLE
• WIND UP
• PIQUE
• KALEIDOSCOPE
• HUMIDIFIER
• BACKPACK

NYT Connections today (game #1240) - hint #1 - group hints

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

• YELLOW: Equipment for a long walk
• GREEN: Raging
• BLUE: Wet not wet
• PURPLE: Watch your reflection

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 #1240) - hint #2 - group answers

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

• YELLOW: THINGS TO BRING ON A TREK
• GREEN: ANGER
• BLUE: MIST MAKERS
• PURPLE: THINGS WITH MIRRORS

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

NYT Connections today (game #1240) - the answers

(Image credit: New York Times)

The answers to today's Connections, game #1240, are…

• YELLOW: THINGS TO BRING ON A TREK: BACKPACK, COMPASS, HIKING BOOTS, WATER BOTTLE
• GREEN: ANGER: INCENSE, NETTLE, PIQUE, WIND UP
• BLUE: MIST MAKERS: DRY ICE, FOG MACHINE, HUMIDIFIER, WATERFALL
• PURPLE: THINGS WITH MIRRORS: DISCO BALL, DRESSING ROOM, KALEIDOSCOPE, MEDICINE CABINET

• My rating: Easy
• My score: Perfect

A straightforward Connections puzzle to begin the week, without any word games, traps, trickery or cultural gaps.

As is often the case with these types of Connections games I got each group in difficulty order and was able to experience that little tingle of perfection, but also disappointment that I wasn’t smart enough to spot a fairly easy purple group.

Games this easy also make me suspicious that the NYT puzzle setters are merely giving our brains a day off in order to soften us up before a difficult run. Bring it on!

Yesterday's NYT Connections answers (Sunday, November 1, 2026, game #1239)

• YELLOW: KINDS OF TEETH: BICUSPID, CANINE, INCISOR, MOLAR
• GREEN: KINDS OF LOVE: BROTHERLY, PUPPY, SELF, UNREQUITED
• BLUE: ENTHUSIAST: FIEND, HEAD, HOUND, LOVER
• PURPLE: SYNONYMS FOR "SOAKED" WITH FIRST LETTER CHANGED: DOGGY, MATURATED, TRENCHED, TRIPPING

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.

DJI is a household name when it comes to some of the best drones available to buy today, so the last thing you expect is for it to venture into the home appliances category. And yet that's exactly what it did and DJI's debut robot vacuum nailed every element.

Our DJI Romo P review gives it a high score of 4.5 stars out of 5, calling it an "extremely impressive smart-home debut" and it's all thanks to the company's existing drone technology that gives the robot vacuum practically perfect navigation and obstacle avoidance. And it doesn't compromise on cleaning either.

This powerful combination is what earned it a coveted TechRadar Product of the Year Award this year, where the DJI Romo P made it to the top in the Home category.

It typically retails for well over the two-grand mark, but if you're keen on grabbing one of the best robot vacuums in Australia and save over a thousand dollars, JB Hi-Fi is offering a massive 44% discount on the DJI Romo P right now in an early Black Friday deal. Honestly, that's excellent value — take it from someone who's been testing vacuums of all kinds for a decade.

Romo P: was $2299 now $1296
Looking like it would happily belong inside the Millenium Falcon, this futuristic robovac is a debut model from DJI and yet it can clean just as well as established competitors in the same price bracket. We call it a "hugely impressive package all-round" and, the best part, you can have it for a lot less than its retail price — it's not even officially Black Friday sales time yet!View Deal

There's very good reason that the DJI Romo P won our coveted Home Device of the Year. Let's begin with the obvious, shall we? It's futuristic good looks. There's no robot vacuum like it on the market at the time of writing and it gives off Nothing design vibes where you can see the insides of the machine. I think it would look fabulous inside any modern home.

While its 25,000Pa of suction might not seem like a lot compared to other premium models that now boast upwards of 40,000Pa, you really don't need that much and, in real-world use, the high suction spec doesn't always translate well — just take a look at my Mova V70 Ultra Complete review to find evidence of that. The DJI Romo P, instead, harnesses its suction ability well and, as our tests proved, it vacuums well, aided by extendable brushes.

It's also an excellent mop, but uses dual spinning pads rather than the roller that I personally prefer.

The dock is surprisingly compact and takes care of ongoing maintenance very effectively, giving you as much of an hands-off cleaning experience as is possible for a robot vacuum.

The DJI Home app is one of the rare robovac controllers that we actually like here at TechRadar, with our reviewer saying it's "almost everything a robot app should be".

All in all, the DJI Romo P is a worthy winner of our Home Device of the Year award and definitely worth considering if you're planning on purchasing a new robot vacuum for your home during the Black Friday sales in Australia this month.

• The state of Delaware wishes to add businesses run by AI agents to the already lengthy list of generous regulations in operation
• Rep. James Comer is demanding safety assessments and warning of potential federal legislation if the results are not satisfactory
• Delaware’s bill specifies a 30-month regulatory sandbox for testing, and allows any lawful business to be operated by an Artificial Intelligence Company except banking

The US state of Delaware is planning to add to its generous business rules by allowing companies to be run by AI agents – but Congress lawmakers are not so sure, with one Republican representative writing to the state's governor expressing his concerns, with demands for safety assessments.

Businesses with a Delaware address operate under a range of advantageous regulations, including low (or zero, depending on where the businesses conducts its sales) tax rates and specialized courts.

The prospect of an Artificial Intelligence Company (AIC) being founded is not unlikely, but law experts believe that Delaware’s bill could be used to implement a liability shield for businesses with AI interests.

Harmful actions

Delaaware’s plans have come under the scrutiny of the House Oversight Committee, wish its chairman, Rep. James Comer, pushing back, with concerns over the ability to place an AI in charge of a business.

According to the Financial Times, Comer wrote to the Delaware governor Matt Meyer.“We are concerned," he wrote, "that Delaware’s AIC proposal could be used to protect powerful AI companies and their investors from responsibility for reckless harmful actions.”

In short, if things go wrong, the AI is to blame and the owner of the business has no responsibility.

The draft bill states a 30-month regulatory period in which the AI would be sandboxed. During this time, the concept can then be tested, with an AI agent making the business decisions rather than a human. Like any other business, the company could be sued, and take legal action itself if warranted.

Delaware’s plan could aid in the establishing of AI-centric corporate structures (such as autonomous commerce businesses), something that many believe could happen overseas if no US state acts quickly.

Legal certainty

Various names in business and AI have previously supported the idea of AI-run businesses. Most notable is Mark Cuban, the billionaire investor who suggested earlier this year that as “First to market makes a killing,” any “governor of a state looking to grow their revenues” should allow “anyone to incorporate using an AI agent and stablecoins.”

Andrew Baker, a professor of law at the University of California, indicated to the FT that the Delaware legislation could be an attempt to reach a midway point, perhaps to achieve “legal certainty” for Delaware-registered businesses using agentic AI.

“Ultimately the most likely outcome appears to be an overly generous liability shield which seems unwarranted without some underlying policy rationale that hasn’t been developed or justified well,” Baker said.

As corporations operate as a shield to personal liability, this would not seem beyond the reach of business legislation. However, those cases involve businesses run by humans who have to be accountable to themselves if not the law, and an AI agent has no such moral restrictions.

• Intel and AMD discuss cooperation without revealing the project's purpose
• Intel's existing x86 partnership with AMD already supports shared processor standards
• AMD's ZenDNN optimizations are entering Intel's oneDNN software library

Intel CEO Lip-Bu Tan has discussed potential cooperation with AMD CEO Lisa Su, but neither executive has disclosed what the two companies might develop together.

Intel is pursuing customized processors, new semiconductor technologies, and external manufacturing contracts, and Tan is looking to strengthen these businesses.

Both companies already cooperate on processor standards and AI software, although their latest discussions could involve different technologies or commercial arrangements.

Existing partnerships provide several possibilities

Intel and AMD established the x86 Ecosystem Advisory Group in October 2024 alongside other technology companies to coordinate improvements to their shared processor architecture.

The initiative addresses compatibility across x86 processors, helping software developers support products from both manufacturers while the companies continue competing for customers.

Their cooperation has also extended into AI software, with AMD integrating its ZenDNN optimizations into Intel's open-source oneDNN library for CPU-based PyTorch inference.

They have also worked on Advanced Matrix Extensions and other x86 capabilities, providing established examples of cooperation between competing processor manufacturers.

During a chat with Chinese American Semiconductor Professional Association President Jimmy Cheng, Tan discussed his plans to strengthen Intel's processor business.

“We have to reclaim the leadership in CPU. That is something that I am very determined to do,” said Lip-Bu Tan, Intel CEO.

“I'm modifying it for customer needs, and so that, to me, is a fast-growing area, and I'm double, triple down on it.”

He also described a shift towards accommodating individual customer requirements rather than relying exclusively on Intel's existing processor designs.

Intel's foundry business offers another potential area

Intel's manufacturing operations provide another possible area for cooperation, although no announcement has confirmed that AMD intends to manufacture chips through Intel's foundry business.

Tan said Intel's 18A manufacturing process had entered volume production, while development of its next-generation 14A technology continued.

The company has released version 0.5 of its 14A process design kit, with version 0.9 expected before version 1.0 becomes available for volume production in early 2027.

In January, two prospective customers were evaluating 14A test chips, with firm supplier decisions expected during the second half of 2026 and first half of 2027.

Tan said several customers wanted to expand their businesses through Intel's manufacturing services, but he did not identify them or disclose potential order sizes.

His strategy also includes application-specific integrated circuits, co-packaged optics, advanced packaging, and physical AI, with two or three of these businesses expected to contribute approximately 10% of Intel's revenue individually.

Customer confidence remains important to Intel's manufacturing ambitions because chip designers depend on reliable production schedules and manufacturing quality when developing commercial products.

According to Tan, a customer waited for six to eight months for him to become CEO and then raised 15 areas where Intel had fallen short.

The company said all the complaints were tackled effectively, after which the customer agreed to expand its relationship with Intel.

Tan's account appears intended to reassure prospective foundry customers that Intel can resolve manufacturing problems and retain business, but it does not confirm that AMD will use Intel's manufacturing process.

Via Tom's Hardware

• Google and NASA are developing a robot to assist astronauts medically
• Deep-space communication delays could make onboard medical assistance essential during emergencies
• NASA's robotic assistant could retrieve ultrasound equipment for astronauts experiencing severe pain

Google is developing a robotic medical assistant with NASA to help astronauts handle health emergencies and routine duties during future deep-space expeditions.

The system is intended to support onboard medical personnel while also performing maintenance, moving equipment, and managing supplies when medical assistance is unnecessary.

The project remains experimental, with laboratory testing indicating progress in basic robotic tasks rather than readiness for autonomous medical procedures.

A robotic assistant for astronauts far from Earth

The project brings together Google Cloud, NASA's Human Research Program, Johnson Space Center's robotics team, and the Jet Propulsion Laboratory to develop robotic assistance for spaceflight.

The work builds on the Crew Medical Officer Digital Assistant, an AI medical support system that Google and NASA have been evaluating since 2025.

That earlier system is designed to help astronauts assess health problems when distance and communication delays make immediate consultation with Earth-based doctors difficult.

“An astronaut on a future deep space mission to Mars could face severe operational challenges, including round-trip communication latencies of up to 44 minutes,” said Jim Kelly, Google's public sector vice president.

Such delays could complicate medical decisions during emergencies, making onboard resources increasingly important when astronauts cannot receive immediate instructions from mission control.

Rather than replacing the crew's medical officer, the robot would assist with practical tasks, leaving diagnosis and treatment decisions under human supervision.

For example, an astronaut experiencing intense back pain possibly associated with kidney stones could request an ultrasound examination using equipment retrieved and prepared by the robot.

The machine could then help position the necessary equipment while the medical officer examines the resulting images and determines the appropriate response.

Early tests show progress, with major limitations remaining

Google is also adapting navigation technology developed at NASA's Jet Propulsion Laboratory to help the robot move through its surroundings and locate equipment.

The team has also used DeepMind's MuJoCo physics simulator to assess movement and object handling before attempting more demanding applications.

According to Kelly, during the initial laboratory trials, the robot achieved an 85% success rate when locating and moving a medical bag.

That result concerns a relatively basic retrieval task and does not establish whether the system can reliably perform medical examinations or assist with complicated emergencies.

“To maximize its utility for a lean crew, the robotic system is designed as a versatile 'payload' handler capable of managing cargo, logistics, and equipment,” Kelly explained.

“When not needed for routine maintenance like organizing tools or securing compartments, it can pivot to medical support.”

Google has described the work as a proof of concept, with early laboratory demonstrations completed but no confirmed fully integrated, space-ready robot.

The agency has declined to provide detailed information about the project, stating that it is examining several advanced AI initiatives with partners for possible future missions.

The robot is also expected to handle cargo, organize tools, secure compartments, and support routine maintenance, allowing a small crew to allocate its time more efficiently.

Google's proposed system therefore combines physical assistance with AI-enabled support, although its practical capabilities will depend on further testing and successful integration with spacecraft operations.

“The ultimate goal is to build a robotic system that can execute a variety of tasks via simple voice instructions, under the astronauts’ direct supervision and command,” Kelly said.

“For instance, the robot might be directed to assist with routine health monitoring—such as capturing basic vitals or simple ultrasounds—under the strict guidance of a human crew medical officer.”

Via The Register

• Keybytes lets users assemble custom keyboards from magnetically connected individual keys
• Every Keybit contains its own RISC-V microcontroller for individual key operation
• A full-size Keybytes configuration could cost approximately $900 to assemble

MIT student Nathan Alspaugh has developed Keybytes, an open source keyboard project that lets users create custom layouts by connecting individual keys to a central controller.

The design uses magnetic connections and dedicated microcontrollers to support flexible arrangements.

Keybytes consists of two main elements: the Keyword controller and individual Keybit modules, which connect magnetically to form a personalised keyboard.

Magnetic keys allow custom layouts

Each Keybit contains a RISC-V microcontroller, allowing individual keys to operate independently rather than relying entirely on one central processor.

Every Keybit measures 19.05 x 19.05mm, corresponding to a standard 1U keyboard unit.

Its four-sided pogo pin connections carry power and I2C communications, allowing modules to connect through different edges and accommodate varied arrangements.

The central Keyword module contains two stacked circuit boards, with an Arm Cortex M4 microcontroller.

The Keyword controller contains two stacked circuit boards, with its upper board housing an Arm Cortex-M4 microcontroller, a Bluetooth antenna and flash memory.

Its lower board provides USB-C connectivity, charging functions and a buck-boost converter for power management.

Each Keybit accommodates a Cherry MX mechanical switch, giving builders the option of selecting compatible switches for their preferred typing experience.

The magnetic connections allow keys to attach around the Keyword controller or alongside other modules, removing the fixed layout restrictions found in conventional keyboards.

Alspaugh has published the project files, design assets and construction details on GitHub under the permissive MIT licence.

This allows others to examine the design, build their own units and modify the hardware according to their requirements.

Building a full keyboard could cost $900

Despite its flexibility, Keybytes remains an early-stage project, with Alspaugh reporting that the basic system had only recently reached a working state.

Publicly available project documentation currently shows limited combinations of modules rather than a completed, full-size keyboard layout.

The developer estimated that assembling a full-size version using approximately 2 Keyword controllers and 110 Keybits would cost around $900.

That figure indicates how quickly expenses could accumulate when each additional key requires its own circuit board, microcontroller, and other electronic components.

Builders must also account for printed circuit board production, component purchases, soldering, and custom 3D-printed enclosures.

These requirements could make large layouts considerably more demanding than smaller configurations designed around a handful of shortcuts.

The current design also has limitations in its lighting options, since the Keyword includes a status indicator while individual Keybits lack dedicated illumination.

Future versions could add features such as customisable RGB lighting, rotary controls, fingerprint recognition modules or a compatible touchpad. These remain proposed additions rather than confirmed developments.

• ICE has requested numerous social media platforms to hand over data on users who are critical of its agents and operations
• Tech companies have complied, but are now expecting Democrat-led investigations into their compliance following the midterm elections
• Executives want to shield themselves from Congressional inquiries into their conduct

The US midterm elections are just days away, and big tech companies such as Google and Meta are already quietly defying Trump’s orders to hand over data on users who have criticized his stance on immigration.

The incumbent party usually loses seats in the midterm elections, and with a wave of Democratic governors potentially on the horizon tech companies are attempting to stave off future scrutiny.

“They need to be prepared to say, under oath, why they did what they did,” Rep. Shri Thanedar (D., Mich.) said, referring to an investigation into companies who have complied with Trump administration subpoenas.

T&C update: your data may be handed to the authorities

Numerous tech companies with platforms upon which people have voiced critical views of Trump’s handling of immigration policy have begun updating their terms of use to include transparency on how user data could be handed over to the authorities.

Much of the criticism has centered around how Immigration and Customs Enforcement (ICE) have conducted operations investigating illegal immigrants.

As a recent Department of Homeland Security breach exposed, ICE agents have conducted undercover surveillance operations of protestors, critics, and journalists using wiretaps.

The DHS has also expanded its definition of doxing - the revealing of personal information such as a home address for malicious purposes - to include names and titles. Social media platforms and search engines such as Google, Facebook, Instagram, Reddit, TikTok and X have then been scoured by ICE to identify anything it deems a threat to its agents or operations.

Many of these platforms have been handed administrative subpoenas that do not require approval from a judge. Citizen journalists with channels on YouTube have also been targeted by ICE, with requests to hand over customers’ personal information.

“Violence, threats, and conspiracies to impede law enforcement operations are not protected by the First Amendment,” said White House spokeswoman Lauren Bis.

People familiar with the matter told the Wall Street Journal that the DHS has increased the number of grand jury subpoenas submitted to platforms that handle user data, which carry heavy consequences for noncompliance.

In order to prepare for potential Democrat inquiries into how tech companies have conducted themselves in line with such subpoenas, some companies have delayed or pushed back on some requests to help insulate themselves from investigations.

A letter from Sen. Ron Wyden (D., Ore.) and Rep. Pramila Jayapal (D., Wash.) to the chief justice of the Supreme Court and the acting head of the Government Accountability Office accused ICE of using subpoenas to “surveil, intimidate, and suppress the free speech of ordinary citizens and even the free press.”

An ICE spokesperson told the WSJ that all of its operations are “conducted in accordance with applicable law and policy.”

• Nvidia has quietly cut Rubin's listed HBM4 bandwidth from 22 TB/s to 19.2 TB/s per GPU and NVLink 6 from 3.6 TB/s to 3 TB/s
• The eight-GPU HGX Rubin NVL8 fares worst, losing 26% of its memory bandwidth and dropping from 2.3 TB to 2 TB of HBM4 capacity
• On paper, AMD's MI455X now leads on per-GPU memory bandwidth and Helios on scale-up bandwidth, though neither side's figures are benchmarked

Nvidia has quietly lowered the memory and interconnect bandwidth it publishes for Vera Rubin, cutting per-GPU HBM4 bandwidth by about 13% and NVLink bandwidth by about 17%, without a press release or explanation.

The Vera Rubin NVL72 product page now rates each Rubin GPU at 19.2 TB/s of HBM4 bandwidth, down from 22 TB/s, and 3 TB/s of NVLink 6 bandwidth, down from 3.6 TB/s.

Memory capacity holds at 288 GB, and the headline 50 PFLOPS of sparse NVFP4 inference remains unchanged; however, at rack scale, aggregate memory bandwidth slips from 1,580 TB/s to 1,400 TB/s and the NVLink total from 260 TB/s to 216 TB/s, while the two-GPU Vera Rubin Superchip drops from 44 TB/s to 38.5 TB/s.

An edit without an announcement?

The revision surfaced in a report from IT Home, which compared Nvidia's October documentation with a copy saved in June 2026. Wccftech then narrowed the window with Wayback Machine snapshots, placing the edit between September 1 and September 11. Nvidia, as Hardware Busters observed, went "the quiet way: by editing the product pages."

The timing matters here: the change landed shortly after Nvidia's August second-quarter results said Vera Rubin racks were already running at partners including CoreWeave, Google Cloud and Microsoft Azure, months after early systems began reaching select customers, and just as the fall production shipments Nvidia promised in May 2026 were due to begin.

This suggests the new figures describe hardware going out the door rather than a distant goal, and the nerfed figures sat on Nvidia's site for at least six weeks before anyone reported them.

The downgrade wasn't completely proportional, though, with some configurations taking a bigger hit.

Most noticeably, the HGX Rubin NVL8, Nvidia's standard eight-GPU server board, fares worst. The HGX page now lists 2 TB of HBM4 at 130 TB/s for the whole system, down from 2.3 TB and 176 TB/s, a 26% bandwidth cut.

NVLink Switch bandwidth falls from 28.8 TB/s to 24 TB/s, and dense training figures slip from 280 to 270 PFLOPS of NVFP4 and from 140 to 130 PFLOPS of FP8. Scale-out networking is the only line that rises, by 12.5% in most configurations, and Nvidia hasn't said why.

Scaling back to ensure delivery?

Interestingly, the math does not hold completely anymore: its per-GPU table still advertises 288 GB at 22 TB/s with 3.6 TB/s of NVLink, figures that no longer add up to the system totals printed beside them, and Nvidia's July Rubin architecture deep dive still promises 22 TB/s. Split across eight GPUs, the new totals come to about 16.25 TB/s and roughly 250 GB each.

This fits two potential readings: eight smaller HBM4 stacks running at just under 8 Gbps per pin, the industry baseline, or one of the usual eight stacks disabled per GPU, a trick Nvidia used on the 80 GB H100, but Nvidia hasn't said which approach it took.

The retreat makes more sense given the history here: JEDEC's HBM4 standard, published in April 2025, specifies up to 8 Gb/s per pin across a 2,048-bit interface, or 2 TB/s per stack. Nvidia wanted far more, but it might have had to settle for less.

According to a TechPowerUp report from March, Rubin's per-GPU target climbed from 13 TB/s at GTC 2025 to 20.5 TB/s by that September and 22 TB/s at CES 2026, and a SemiAnalysis note it relayed said SK hynix and Samsung were struggling to reach the final figure, with early shipments expected to be nearer 20 TB/s.

TrendForce reported in September 2025 that Nvidia was pressing suppliers for 10 Gbps per pin as AMD readied Helios, and warned that if volumes fell short or costs ballooned, Nvidia "may abandon the upgrade or segment its platform products."

By January, TrendForce said the request had passed 11 Gbps and sent all three HBM makers back to redesign, though an Nvidia spokesperson told Tom's Hardware that "our HBM4 memory partners remain on track for production shipments." SK hynix finished HBM4 development first, and Samsung began shipping in February at 11.7 Gbps, above Nvidia's stated requirement.

More than a year after TrendForce's warning, the revised sheet reads like its fallback scenario: a lower overall ceiling, plus a further-reduced HGX tier, and this seems to be because Nvidia needs to deliver solutions to its customers as a higher priority than chasing an elusive memory bandwidth goal.

Team Red for the win?

Because of the retreat, perceived or otherwise, the competitive picture shifts considerably, at least on paper. AMD's Instinct MI455X spreads 432 GB across 12 HBM4 stacks for 23.3 TB/s, which needs only about 7.6 Gbps per pin, below the JEDEC baseline. AMD bought its bandwidth with width rather than speed, so it never needed above-standard memory.

When it launched Helios in July 2026, AMD claimed 6% more HBM bandwidth than Vera Rubin NVL72's published figure; against the revised 1,400 TB/s, Helios' 1.67 PB/s is roughly 19% ahead. Scale-up bandwidth, Nvidia's traditional stronghold, was level at 260 TB/s per rack and now favors AMD by about a fifth, while the scale-out increase trims AMD's claimed 50% lead there to about a third.

For buyers running inference, the bandwidth line matters more than the FLOPS line. Nvidia's engineers write in that July deep dive that decode is bound by the memory subsystem, though they argue that what counts is how efficiently kernels use it, and that it is "not about peak bandwidth specs."

The marketing hasn't moved, however: the NVL72 page still promises up to 10x more tokens per megawatt and one-tenth the cost per million tokens versus GB200 NVL72, footnoted as subject to change, and Nvidia hasn't said whether it reran those projections on the lower figures.

None of this makes Rubin slow. At 19.2 TB/s, it still offers about 2.4 times a Blackwell GPU's 8 TB/s, rather than the 2.8x Nvidia's blog still claims. Jensen Huang said in August that "Vera Rubin, now in full production, was built to power exactly this moment." The moment, it turns out, arrived with a little less bandwidth than advertised.

On my recent unboxing of the brand-new Kindle Colorsoft Signature Edition (the one with the brushed aluminum back), I noticed someone asking about the quality of colors in dark mode, and I realized I didn't have a good answer.

Dark Mode, which became popular on modern screens over the past 15 years or so — a throwback to the original CRT displays — has never been my thing. As a result, I don't use it on phones, browsers, or Kindle e-readers. Still, the more I thought about this question (below). The more I wondered about it.

"This might be a dumb question," started one TikTok commenter, "but do the colors still show when in Dark Mode? I've only seen photos in light mode."

I instantly tried to imagine what a comic or graphic novel might look like in Dark Mode and realized I'd never seen it that way either.

Let's try the Colorsoft Dark mode

The Kindle Colorsoft shares a menu system with the rest of the monochrome Kindles, with the Dark Mode option sitting right up top. You access the quick menu with a swipe down from the top of the display. You can also dig into settings to turn on the control from there.

I turned on Dark Mode on the Kindle Colorsoft Signature Edition and noticed that my library immediately reversed, turning all the white borders black, but the book, magazine, and graphic novel covers remained untouched. If I opened a book, I saw white text on black pages.

The other thing I noticed is that the screen looked a lot dimmer. Basically, Dark Mode automatically lowers the screen brightness by half.

I opened a graphic novel. As with the rest of the Colosoft interface, the borders around each graphic novel page were black. However, each page was still white, with the untouched color panels inside. Honestly, this makes sense, since I can't imagine any artist would want dark mode reversing their work. It would probably look terrible.

Lance Ulanoff / FutureLance Ulanoff / FutureLance Ulanoff / FutureLance Ulanoff / Future

I could see all the colors, but the pages looked too dim. Fortunately, I could still push the front-lit LEDs brighter (I turned them up to max) to return some of that vibrancy, though I'm not sure if that defeats the purpose of Dark Mode.

The other option is to take advantage of the Kindle Colorsoft's reflective display (unlike an LCD, there are no traditional backlights). If you have a good external light or even sunlight, the page looks great with or without dark mode, which can reduce eye-straining screen glare and save some battery life (not much of an issue with Kindles).

Here's what I learned: Yes, you can still see colors in Dark Mode, but as Amazon confirmed to me, "When setting Colorsoft devices to dark mode, the screen may appear dimmer overall due to the color E-Ink layer."

If the screen looks too dim, adjust the brightness or find a good light source and enjoy your colorful graphic novels.

Against a backdrop of component shortages and price hikes, 2026 has been a challenging year for camera companies, and it's been a quieter year for new gear as a result. That being said, we were still treated to some cracking cameras — but standing tall above them all was the Sony A7R VI, with a new 66.8MP full-frame stacked sensor, Bionz XR 2 processor, Sony's latest subject-detection autofocus, and its first new battery for 10 years.

It's a formidable camera whatever your genre of photography, and won both our Best Professional Camera and overall Camera of the Year awards for 2026 at the TechRadar Product of the Year Awards 2026. Here's what makes the A7R VI so special, in my opinion.

Bird photography with the 400-800mm lens was one of the many occasions I made good use of the Sony A7R VI (Image credit: Tim Coleman)Can a camera really be ‘perfect’?

It's possible that I got carried away slightly when I said the A7R VI “had no weaknesses”, but after weeks testing the full-frame mirrorless camera across landscape, portrait and wildlife photography, I had no doubt in my mind that it deserved a perfect 5-star rating.

I’ve been reviewing cameras for almost two decades, and the A7R VI genuinely feels like peak camera. In my A7R VI review, I was even compelled to say “Sony can stop making cameras now.”

The A7R VI is a powerful all-rounder, as opposed to a pure pixel monster

First up, I must point to the new sensor, which had an admittedly modest bump in pixels from the already class-leading A7R V’s 61MP sensor, to 66.8MP. But that’s not the exciting part about this sensor — it’s also a ‘stacked’ type with a faster read-out speed.

Faster read-out speeds can improve a camera’s performance in multiple ways, not least by reducing rolling shutter (an ugly distortion effect that appears when recording video and taking photos of high-speed subjects).

For me, I preferred having the smaller bump in resolution and a greater emphasis on speed, as opposed to an even bigger bump in resolution but no speed improvement. The A7R VI is a powerful all-rounder, as opposed to a pure pixel monster.

The camera packs Sony’s Bionz XR 2 processor, which combines two chips, including one that’s tasked with subject-detection autofocus. Whether I was photographing small birds or large mammals in a nature reserve, or taking portraits, the A7R VI never skipped a beat.

The versatile multi-axis screen can tilt, pull out, and flip out to the side (Image credit: Future / Tim Coleman)

Then there’s the camera’s handling. Historically, for me Sony's design and user experience haven't matched those of other leading mirrorless camera brands — I’m a sucker for Nikon in particular. But the A7R VI is spectacularly well designed.

There’s a tilt-and-flip touchscreen, meaning the screen can be pulled out and used as a tilt screen for waist-level shooting, or flipped out and rotated for selfies — traditionally you’d have to pick either / or (or have neither). It’s the most versatile design on the market, and one which you can also find on the latest Lumix S1 II cameras. If I had one wish, it would be that Sony increased the size of its 3-inch display in the future, even if only to 3.2-inches like Nikon.

The viewfinder is big, bright and highly detailed class-leading 9.36m-dot display, while the button layout makes perfect sense, and the camera’s grip is nice and deep and comfortable to hold.

Housed inside the grip is an all-new battery — Sony’s first for 10 years since the legendary NP-FZ100. The new unit has a higher capacity, and increases shot life by 20%; not bad, considering the previous battery already delivered class-leading power.

The downside to the new battery is that it’s not forwards / backwards compatible with the NP-FZ100, so upgraders are going to have to splash out on additional batteries should they need them.

Sony's new high-capacity battery debuted in the A7R VI (Image credit: Future / Tim Coleman)

Video specs are decent, though arguably not as strong as those of some lower-resolution rival cameras. For example, Sony again omitted open-gate recording (this would finally appear later in the yet-to-go-on-sale FX5 cinema camera).

But if photography is your beat, and you need a high-resolution sensor with huge scope for cropping — the A7R VI’s Super 35 (APS-C / 1.5x crop) mode is still a healthy 28MP — and don’t need the absolute top speed and buffer performance of cameras like the A9 III and A1 II, there really is no better camera.

The A7R VI was so good, in fact, that it put the (much) pricier A1 II’s position in doubt, given that it can do 90% of what that camera can, while boasting a higher-resolution sensor.

I reviewed some fabulous cameras in 2026, but my absolute favorite was without doubt the A7R VI — it’s the camera I wish I owned, along with some of Sony’s spectacular recent pro GM lenses. It was the crowning achievement for Sony in a year in which it also scooped our Brand of the Year award, and comfortably maintained its #2 market position behind Canon.

Sony A7R VI image galleryTim ColemanFuture / Tim ColemanFuture / Tim ColemanFuture / Tim ColemanFuture / Tim Coleman

Oracle co-founder Larry Ellison has pushed back at the suggestion that artificial intelligence could end software and SaaS businesses like his, arguing that AI will actually just make enterprise applications even more capable than they ever have been.

Speaking during his keynote at the company's annual AI World conference, Ellison directly addressed ongoing concerns that businesses could use AI to build their own software – we've already seen many popular apps and suites like Adobe's Creative Cloud be imitated by AI, for example.

"There's been some talk about there's going to be a SaaSpocalypse because everyone's going to use AI to build their own applications," he said. "I don't think that's quite true. I think companies will continue to build applications, but they will be quite different because of AI."

Future apps will be fully tailored to geographies and industries

Rather than making today's software redundant, Ellison believes AI will allow developers to make their apps far more comprehensive, capable of handling entire business processes and fine-tuned for every type of sector and business need.

He argued that even the most established enterprise applications today are only so good, automating just a proportion of the processes businesses actually need.

"They may be the best things that are commercially available... [but] they're not done," he revealed, acknowledging that many sectors still need to build their own extensions and buy other third-party apps and connectors.

"For the first time... [the] software industry can actually finish the applications if we start doing them industry by industry."

Oracle's biggest clear push is in the healthcare sector currently, with Ellison speaking on stage about the notoriously complex and highly regulated nature of this industry – immense challenges for one global software company when navigating endless geographical variabilities is a must.

SaaSpocalypse doesn't kill off apps – but it certainly shifts the focus from interface to functionality

Ellison also believes that AI could fundamentally change how workers interact with applications, replacing complicated menus, dashboards and multi-step processes with smoother, natural language interaction.

"If you can ask a question describing what you want to see, you should then immediately see it. Any other user interface is nonsense."

"There should be no training required to use any of these applications," he added.

While Ellison remains confident about the future of commercial software, that doesn't necessarily mean businesses will continue to interact with apps in the same way, and it seems that a company as big as Oracle is singing from the same hymn sheet.

In two separate interviews with TechRadar Pro, company execs pointed toward the same trend. Brian Chess, NetSuite's Chief Operating Officer, implied that the underlying business software could eventually become invisible to users.

Discussing customers who might prefer to access NetSuite through AI assistants like ChatGPT or other platforms like Slack, Chess said "If they never log in, that's ok with us." Oracle knows that as long as it can still serve as a company's system of record, adapting to new ways of access is a must.

But what this means is that, for software vendors, the value of their products will likely come more from the data, logic and processes they manage, rather than the polished interface they've been used to building for potentially decades.

Ultimately, earlier SaaSpocalypse concerns remain valid, but it's not so much about AI wiping software from the world entirely. It just marks the next chapter in software, where interfaces become less critical and functionality becomes the biggest USP.

Shares in Oracle rose around 14% to $144.14 in the couple of days that Oracle AI World took place, likely partly in thanks to Ellison's thoughts on the future of software as well as the company's whole suite of product announcements, but share prices are still down markedly on their late 2025 high of $330.34.

The RAM crisis has grown even more limbs during the month of October. If the memory shortage was incarnated in physical form, it'd have more legs than a spider at this point, and be a multi-limbed monstrosity with a bite that's getting nastier by the day as more negative news seems to roll in at a frightening pace.

Just this week, we've witnessed SK Hynix predicting that RAM supply woes are going nowhere and will persist through to 2030, after Dell's CEO recently warned that we're stuck with this crisis until the end of the decade, and Intel's chief exec agreed – on top of other similar forecasts from earlier this month.

The latest nugget of doom is from Samsung, with the memory chip maker giving out similar vibes to its rival SK Hynix when reporting its financial results (as Wccftech spotted), informing us that RAM shortages will get worse next year, and supply will remain thin on the ground in 2028, too.

You can barely catch a breath between the various dire predictions during the past month. Naturally, in the face of such grimness, it's human nature to try to look on the bright side, or in this case, at least attempt to find a glimmer of light shining through from somewhere. There must be something, right?

Well, there is: Black Friday. An event with a distinctly gloomy name, ironically, but I'm increasingly of the opinion that this is going to be a very important sales season from the computing and PC point of view (and likely other tech, too). Mainly because I expect that the deals you'll get this year will likely be the best prices to be had in a long while, and possibly this entire decade, if those 'it's here until 2030' voices are correct in their assertions about the RAM crisis.

But I hear you (possibly) cry: given all these price hikes, isn't Black Friday going to be a wash anyway? At least based on what we saw with Amazon's recent Prime Day sales? And yes, that's a fair point. You should manage your expectations with the discounts that'll be on offer, certainly, and don't expect to snag a bargain on RAM sticks or that beefy SSD you've been dreaming about. That just isn't happening (to no one's surprise).

However, on Prime Day, there were some decent deals to be had, for example on GPUs. Notably on the RTX 5080, where if you grabbed the deal I highlighted back then, you saved yourself 20% (£300) compared to the price of the cheapest model of that Nvidia GPU on Amazon now (at the time of writing).

So, given that, what should you be looking at buying this Black Friday, which is less than a month away now (with early offers starting already)? Well, the best deals will likely be in the products set to be more affected by the memory shortage as time rolls on, and I'm going to highlight what I believe are a few key areas bargain hunters should focus on when it comes to the PC sphere.

Graphics cards

(Image credit: Future / John Loeffler)

I'm putting this one front and center because I believe this should be a priority for PC owners who are looking at a GPU upgrade at some point in the not-too-distant-future. As I already mentioned, there were some decent graphics card deals on Prime Day earlier this month – albeit when it comes to the higher-end GPUs, the word 'decent' translates to 'not inflated', which isn't quite the same thing.

Still, the problem is that prices are likely to rise a good deal more next year, and if you do need a higher-end GPU in particular, during 2027 I think there's a good chance pricing will get a lot worse. Meaning that what you'll pay on Black Friday, with the odd scattered deal on the likes of an Nvidia RTX 5070 model or AMD RX 9070 XT – and maybe even an RTX 5080 – will be a relative bargain (maybe for quite some time to come).

I think this is especially true given the rumors around the RTX 5090 being discontinued (Nvidia has insisted it isn't, but even so, something's clearly amiss with the flagship GPU somewhere), and the ridiculous inflation the RTX 5080 has seen over the past month. All of this indicates a rocky picture with Nvidia's GPUs, and with memory (VRAM) difficulties set to worsen next year – and AMD also rumored to be implementing price hikes with Radeon graphics cards – my advice is to get in ahead of wider GPU price spikes next year.

The catch is that Black Friday deals on graphics cards could be thin on the ground, but we may actually get some decent price cuts in the mid-to-lower-end of GPU territory.

Gaming laptops

(Image credit: Canva)

If you're thinking about buying a gaming laptop, I think there's scope for some good deals on Black Friday – traditionally laptop discounts are plentiful among the massed ranks of portables, and gaming devices have more headroom for cuts, too.

What you need to consider here is that serious gaming laptops run with a discrete GPU, and as noted above, graphics card price increases are very much on the table. Indeed, this is already happening, and XMG is pushing up prices for its top-end gaming laptops with the RTX 5090 in a major way, while promising that "other laptop GPUs are also facing supply constraints." Further price rises are coming, then, and with RAM getting more costly next year too, we can expect some painful hikes.

As a result, I'd be inclined to keep a careful watch on what Black Friday presents in the way of gaming laptop price cuts, and move sooner rather than later if at all possible.

Laptops

(Image credit: Shutterstock)

Outside of the gaming arena, everyday laptops are another area where I'd seriously think about trying to nab a Black Friday bargain. As mentioned, there are usually a lot of laptop deals – we highlight the top offers at TechRadar, of course, and notebooks represent quite a number of the bargains we pick out – and while there may not be so many this year, expect them to be there.

With the rising tide of RAM prices and the worsening of the crisis next year, it seems inevitable that this will jack up the asking prices of all laptops (and especially gaming laptops, as noted, due to the extra pressure added by the video RAM of discrete GPUs).

Analyst firms are already predicting that laptop manufacturers are soon going to ramp up pricing as they run short of stockpiled components (purchased at a cheaper cost). And one analyst outfit, IDC, recently advised that the only positive glimmer here is that some retailers are carrying too much notebook stock (given flagging PC sales this year) which may result in "promotions and some short-term relief for consumers," which is clearly referring to Black Friday.

I agree, of course, and think that if you want a new laptop in the next couple of years, Black Friday 2026 is likely to be the best time to make your move.

What else?

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On the PC side, then, I feel that laptops – particularly gaming notebooks – and desktop GPUs are the key areas to focus on for Black Friday bargains.

The trouble with other key desktop PC components aside from graphics cards is that pricing has got so high with RAM and SSDs that even a 'bargain' with a big price cut feels like a very sour purchase compared to prices last year. These components are just depressingly expensive (especially system memory), so it's difficult to recommend buying at all unless you're absolutely forced to. (Top-end GPUs are now in this territory too, of course).

That said, there may just be a half-decent deal on storage somewhere (we did see one or two of those in the most recent Prime Day).

On a lighter note, you might well see some solid deals on CPUs if you're on the hunt for a new processor. This is likely to be the exception in terms of the other core PC components aside from GPUs, although I'm not expecting CPU prices to face the same upward pricing pressures that graphics cards will encounter next year, so there isn't the same sense of urgency to buy in that respect. I could be wrong in that, mind – and the same goes for all my musings here – so season this advice liberally.

Elegoo, known for its hobbyist 3D printers, is changing, and its more recent hardware shows big changes in both design and manufacturing quality. The M1 Ultra is one of the signs of this change yet, with a premium design and build that put it firmly in competition with established 3D scanning manufacturers such as Creality.

The M1 Ultra combines blue laser and infrared structured-light scanning, with five main scanning configurations that cover everything from small mechanical components and intricate objects to larger structures and even humans. The scanner offers a top accuracy of 0.02mm in the finest blue laser mode, and other standout features include full wireless operation, a 3-inch touchscreen and a swappable battery.

I’ve recently tested quite a few handheld 3D scanners, and there’s no doubt the market is getting competitive; however, whilst it’s a surprise to see Elegoo launch into the market, it’s even more surprising when I lifted the scanner from the hard case to discover the quality of the design and build.

The M1 Ultra is beautifully finished with a well-balanced design, with part rubberised grip that makes it comfortable to manoeuvre around objects. If anything, I would have liked the grip to be slightly longer, but otherwise the physical design is excellent.

The scanner connects through either wired USB or Wireless connection, with a slide switch enabling you to quickly switch between the two. This link connects you to the software, which initially guides you through the scanning process, and for first-generation software it’s all extremely well thought out.

The most important factor is scan quality, and while scanning a selection of household ornaments, mechanical components, and structural parts, it produced detailed, dimensionally accurate models that I could then export for direct 3D printing or import and edit within Blender.

One of the biggest surprises that I had during the scan process was firstly the speed and then the difference between the initial scanning preview that appeared in the software and the processed model. The preview scans looked OK, if a little rough, but after completing the scan and running the first processing stage, the detail suddenly appeared.

The Elegoo Scan software, being an early release, is surprisingly good and avoided any freezes or glitches through the testing. Scan processing typically took a couple of minutes, depending on complexity and the size, while editing and removing unwanted geometry was straightforward, partly due to my ever-increasing familiarity and use of these scanners. The usage and workflow of the software is very similar to other systems.

Wireless scanning on a scanner of this price is great to see, and I was quickly able to connect to the scanner over Wi-Fi. Once that connection was made, I found the live preview on the scanner’s touchscreen made moving around larger objects much easier.

Through the test, I did find many of the usual limits, such as scanning glossy black plastic and highly reflective surfaces still requiring scanning spray. In all cases, how easily something scans rests solely on careful preparation and marker placement. When using the scanner wirelessly, the scanner also takes over the computer’s Wi-Fi connection, preventing access to a normal workshop wireless network, which I also found was a little inconvenient.

Considering that this is Elegoo's first 3D scanner, the speed, quality and ease of use make it feel like a product that has already undergone several iterations. This is a great option for small businesses, makers, enthusiasts, and other 3D professionals looking for a decent 3D scanner at a reasonable price.

ELEGOO M1 Ultra: Price and Availability

The Elegoo M1 Ultra has a recommended retail price of $1,699 in the US, £1,399 in the UKand €1,699. The scanner is being sold through the official website here.

Elegoo M1 Ultra: Design

(Image credit: Alastair Jennings)

One of the first things that impressed me about the M1 Ultra was the physical design and quality of the build. In contrast to their range of hobbyist 3D printers, Elegoo has clearly aimed this at a more professional level, and it feels significantly more refined than many of their previous product lines.

Elegoo's hardware design improved dramatically, as I saw with its H1 HT filament dryer a few months back and again when it comes to finish and build quality; this feels premium and much like the quality that I’ve come to expect from companies like Bambu Lab.

Weighing in at just over half a kilogram, the M1 Ultra is relatively compact compared with several scanners I’ve used recently. The weight is well balanced for the size, and it's comfortable to hold while moving around objects, with the grip featuring a rubberised texture that provides excellent purchase.

Grip in the scanner is especially important when scanning smaller mechanical components, where controlled movements can affect tracking and the quality of the capture. If anything, I do feel that the grip could have been slightly longer, but overall it’s comfortable enough to handle.

The front of the scanner features the optical system, including the laser emitters, cameras and illumination; these all look like lenses. These are neatly integrated into the casing, while the controls on the large touch screen enable you to start, pause and access the hardware settings.

The 3-inch touchscreen is more than just a monitor for settings and enables less reliance, in some situations, on using a computer screen when scanning. An example is when using the scanner wirelessly, and the display provides a live scan preview; you can also use it to adjust the exposure and zoom.

Additional hardware settings can also be accessed through the touchscreen, including Wi-Fi hotspot information, display brightness, screen rotation, language, prompt sounds and sound alerts. I also liked the fact that I could access the onboard user guide.

(Image credit: Alastair Jennings)

Not all aspects of the user interface are as polished as the hardware itself. The start and pause controls, exposure adjustment, and zoom interface use a slightly dated visual style, with gradient effects that feel more like enthusiast equipment than professional; still, the actual functionality is there.

As I’ve seen with many of these scanners, it arrives in a hard carrying case which is identical in design to the one that arrived with one of the Creality scanners recently; the only difference is the logo on the front and the equipment inside.

Inside, the scanner is neatly laid out, with the scanner, batteries, calibration board, USB cable, tripod, and reflective markers. In contrast to some other scanners, the cables are kept to a minimum, with power and data handled through the same USB connection when using wired.

• Design: 4/5

ELEGOO M1 Ultra: Features

(Image credit: Alastair Jennings)Specs

(Image credit: Alastair Jennings)

Dimensions: 191 × 50 × 76mm

Weight: 511g (including battery)

Scanning Accuracy: Up to 0.02mm (blue laser)

Scanning Modes: Five, including blue laser and infrared

Scanning Speed: Up to 100fps (USB), 60fps (Wi-Fi)

Scanning Resolution: 0.05–2mm (blue laser)

Scanning Volume: 5 × 5 × 5mm to 4,000 × 4,000 × 4,000mm

Display: 3-inch HD touchscreen

Connectivity: USB-C 3.1 and Wi-Fi 6

Battery: 4,800mAh removable

The M1 Ultra features five scanning modes designed to enable you to scan different materials, object sizes, and most importantly, levels of detail.

A quick run-through, and you have the 34-line crossed blue laser, which is designed for fast scanning of medium-to-large objects. The seven-line parallel mode is better suited to smaller parts and more detailed areas. The single-line configuration lets the scanner capture recessed features, deep holes, and narrow gaps.

Alongside these are infrared structured light mode, designed for larger objects, faces, and bodies, and the marker-free blue laser option for situations where reflective markers can't be applied, such as when scanning valuable museum artefacts.

Within each mode, there are a variety of options that you can configure through the Elegoo Scan software, which offers adjustments to tracking, field of view, capture resolution, as well as the main scan quality settings.

This does take some time to get your head around, and depending on the mode, you can select marker-assisted or marker-free tracking, standard or wide-angle fields of view, global marker workflows and different laser patterns. This sounds complex, but Elegoo have created guides for each type and practice is definitely needed in order to fully understand what type and size of object needs what type of scan and settings.

The software does go some way to make things easy, with an example being the infrared scanning mode that offers dedicated presets for normal objects, faces, and bodies, plus geometry-based and texture-based tracking options.

Although the number of settings is considerable, the software is generally well organised. If you are new to 3D scanning, there’s also plenty of guides and visual prompts in the software to explain how the different options work.

• Features: 4.5/5

ELEGOO M1 Ultra: Performance

(Image credit: Alastair Jennings)

Getting started, the first step is the hardware setup. After installing Elegoo Scan on my MacBook Pro, connecting the scanner through USB and selecting the connection option, it was almost ready to go aside from a quick initial firmware update.

Before the scanning process could begin, I needed to run through the calibration process, and this was all surprisingly easy with the calibration chart sitting on the table and the software directing me through a series of manoeuvres with the on-screen guide. This style of calibration used to take me ages; however, here I found the process pretty quick and straightforward.

I started the test using the wired connection, but to switch to wireless there’s a small switch on top of the scanner that enables the change from USB to WLAN. As the switch is moved, the system restarts, and then you can select the scanner’s hotspot from the computer’s Wi-Fi connections, enter the on-screen password, and again it’s ready to go.

The process is easy enough, though wireless operation means the scanner creates its own Wi-Fi hotspot, which the computer must connect directly to. That meant disconnecting from the workshop Wi-Fi, and there was no option to keep both connections active at once.

This isn’t an issue during scanning, especially since the software works offline, but it becomes a bit annoying when switching between scanning and anything that I needed to do online.

When everything was set and ready, I was able to start the scanning process, starting with the 34-line cross blue laser options, which proved to scan objects at speed. Once a scan was captured, it was then possible to clean up the point cloud, as well as easily align multiple scans, and move through mesh wrapping and optimisation before exporting the finished model.

The M1 Ultra and the software effectively give you an easy scan-to-model process, and when finished, you just click export.

For testing, I scanned a variety of objects, ranging from household and office ornaments to mechanical components and structural parts that I needed to reproduce or work around when creating brackets and replacement pieces.

These included objects made from tarnished metal, matte ceramic, plastic, and wood, and the scanner performed exceptionally well across these materials. As with other 3D scanners I’ve tested, good results come down to preparation. While marker-free scanning sounds appealing, I have found that reflective markers remain the most reliable approach.

My usual setup includes a rotating platform, custom 3D-printed marker blocks positioned around the object, and adhesive reflective markers attached directly to the object wherever practical. I also use acrylic blocks to raise the object above the surface. This helps separate the subject from the surrounding environment, especially the platform it sits on, and makes the captured data easier to cut out and process.

The whole preparation process generally takes around five minutes, but it makes an enormous difference to the ease and reliability of scanning. Through the setup process, I aim to keep at least five reflective markers visible to the scanner at any one time, and this generally meant that tracking was straightforward. Scanning objects without markers proved less reliable, even with the scanner’s marker-free configuration.

Once I had properly prepared the subject, most objects took around five to ten minutes to scan from each orientation. Where possible, I tried to capture the object in just two orientations, as this made alignment quicker and generally produced better results.

The scanning process itself was fast, and it was good to see the preview build up the model. When scanning, I started off with the crossed blue laser pattern as this tended to provide the best overall coverage, and then switched to the seven-line mode when scanning more complex objects. For recessed features and deeper holes, switching to the single-line laser again helped to fill in some of the gaps.

After scanning, each model is previewed on the screen, and then you can go through the various processing modes. One point to make here is that the initial scanning is surprisingly fast and the initial point-cloud preview can look a little rough, giving little indication of the level of detail that has actually been captured. However, after you finish the scan and move through the first refinement stage, the model's detail suddenly snaps into place, and it’s impressive.

The M1 Ultra reproduced fine surface features and dimensional accuracy extremely well. One example of the accuracy came when I scanned the car's EV charger, with the model generated being imported into CAD software as a template for a wall-mounted holder. The finished product, while needing some refinement, fitted the EV charger perfectly.

The software is able to export OBJ files that can then be used in applications such as Blender for further editing. The range of available export formats also makes it relatively straightforward to move finished models into other design and manufacturing workflows, with 3MF and STL alongside OBJ.

Not every object's surface was easy to capture, and as ever, while tarnished metal, wood, ceramic and plastic surfaces generally scanned very well, glossy black plastic gained mixed results.

Essentially, any surface that reflects or absorbs the scanning light causes a bit of an issue, and you can get matte scanning sprays to help with the scanning of this type of object.

Infrared scanning also produced ok results, and making sure you work in a well-lit, soft-light environment definitely helps. Again, as with any scanning mode, practice and skill often play a large part in the scanning success.

(Image credit: Alastair Jennings)

One of the main skills when scanning is alignment, essentially when you take a couple of scans of an object from different angles and then align them into one. The alignment option worked well and was surprisingly fast to process between scans, provided the reflective markers' position was maintained. This works by completing the first scan; then the object could be repositioned to capture another side without moving any of the base markers, and the resulting scans could then be selected and aligned within Elegoo Scan.

The important point here is that the markers used as reference points must remain in the correct positions. If you move markers on the platform between scans, alignment will be much harder, and in most cases it's easier to start again.

Mesh processing generally took a couple of minutes per scan, though the time varied considerably with the model's size and complexity. There is still a need to remove unwanted surfaces and sections of the surrounding environment manually, but the software proved effective. Throughout testing, Elegoo Scan remained solid, with no crashes, freezes, or other problems that I have come across in the past with scan software.

For a first-generation Elegoo scanner, and with software at such an early stage of development, this level of reliability is excellent.

At the start of the test, I stuck to a wired connection, mainly due to having to check guides, etc., but over the weeks of the test I switched to the wireless option. There are some sacrifices that you make as you switch over to the wireless connection, most notably that the scanner has a lower quoted maximum frame rate; however, I didn’t notice much of a difference.

The real improvement going wireless was the ergonomic feel of scanning alongside the obvious effect of no longer having trailing wires. The main benefit is that instead of looking back at the laptop monitor to check scan progress, the wireless connection let me monitor the preview directly on the handheld scanner’s touchscreen. This made scanning far more natural, especially when moving around larger or awkwardly positioned objects.

Through the test, I found that the battery runtime was about 60 minutes, shorter than Elegoo's advertised maximum of 90 minutes, but still enough for several typical scans, and I also discovered I could hot-swap the battery with the second battery that was included. I experimented with swapping the battery while USB power was connected, which appeared to work, though this wasn't officially covered in the material I had.

• Performance: 4 / 5

ELEGOO M1 Ultra: Final verdict

(Image credit: Alastair Jennings)

The Elegoo M1 Ultra shows the direction that the company is moving, and this is an impressive start for them in the 3D scanning market. The arrival in the hard case, with the premium build and design, is far removed from their hobbyist machines, and it all has a decidedly higher-quality feel.

The overall ergonomics and build are excellent, and this quality of design comes across in use, with it being easy to handle and with the ability to switch between wired and wireless scanning.

As ever, there are the usual issues with the time taken to prepare the scan, but this is part of the course for all 3D scanners and the more time you put in, the better the scan you get. However, the speed of the scans that the M1 enables is impressive, and more importantly, the quality of those scans was exceptionally detailed.

The Elegoo Scan software is also well thought out, although I do feel there needs to be a little more thought on the design of both the scanning software and the touchscreen interface. The old Elegoo is still apparent in both, giving that hobbyist rather than slick professional aesthetic.

Wireless scanning is another point, and while this works exceptionally well, it does lock your computer out of the normal Wi-Fi network. There are then the usual points about scanning highly reflective or glossy surfaces, which will require scanning spray.

While good results can be achieved with what's in the box, I would, as always, highly recommend the following: turntable, reflective markers, marker blocks, acrylic supports, and scanning spray; these are all relatively inexpensive but will save you hours.

Should you buy the Elegoo M1 Ultra?

Value:

Exceptional first-generation scanner at a very reasonable price considering the alternatives.

4.5

Design:

Premium build and ergonomics highlight Elegoos investment in design.

4

Features:

Packed with scanning modes and plenty of options to refine your scanning

4.5

Performance:

Fast and very capable with one of the easiest workflows yet

4

Total:

Excellent scanner for everyone from enthusiasts to professionals.

4.5

Buy it if...

You need detailed scans.

If you regularly design replacement components, custom brackets, or work with existing physical objects, the M1 Ultra delivers excellent scan quality that you can update in CAD.

You want wireless flexibility.

The integrated touchscreen, direct Wi-Fi connection, and removable batteries make the M1 Ultra much easier to manoeuvre around objects than scanners that rely on wired connections.

Don't buy it if...

You expect instant results.

Despite the ease of use, successful 3D scanning still requires preparation, reflective markers and practice. If you expect to point the scanner at an object and instantly produce a perfect model, you’ll be disappointed.

You scan difficult surfaces.

Highly reflective, transparent or glossy black objects remain difficult to scan. While the M1 Ultra is more versatile than some alternatives, you may will need additional scanning spray and lighting to get good results.

For more crafting essentials, I've also tested out the best 3D printers and best laser engravers

If you celebrate Halloween, you'll no doubt be on the lookout for some things to entertain you this weekend. With this in mind, I checked out three of the biggest new horror releases in October to see if they're any good.

Scream or Skip

Scream or Skip, that is the question. With so much horror out there to watch and play, our senior entertainment writer, Lucy Buglass, is here to help you decide what's worth your time (or worthy of a Scream) and what's not (so you might want to Skip). Her goal is to help you spend less time scrolling and more time enjoying some great TV shows, movies, and games. Read the full series here.

There have been some real highs and lows this month, and I found myself especially disappointed by one movie in particular. Thankfully, there's a great TV show and game to keep you occupied, so it's not all bad.

So, what do I recommend checking out this spooky weekend? Scroll down to find out.

TV — Crystal Lake

Where to watch: Peacock (US); Sky (UK); Stan (AU)
Lucy's verdict: Scream

Crystal Lake is the anticipated Friday the 13th prequel, and it's a great choice if you want a binge-worthy series to watch over the Halloween weekend. With all eight episodes streaming at once, how could you resist?

I did have my reservations about this series, but it is an excellent entry into the horror franchise. In my full Crystal Lake review, I noted there's a clear love for the original movies here, and that it expands upon the lore by focusing on Pamela Voorhees, an under-explored character in the Friday the 13th universe. Played excellently by Linda Cardellini, it's very worth your time.

Movie — Other Mommy

Where to watch: Theaters worldwide
Lucy's verdict: Skip

As someone who loved the book Incidents Around the House and was genuinely freaked out by it, I was excited to hear it was getting a movie adaptation. I was even more excited to hear that Jessica Chastain would star in a dual role as a woman and an entity that emulates her, known as "Other Mommy".

Unfortunately, the movie ended up being a massive letdown. Not only does it suffer from the cliché of tired and overused jump scares, but it also deviates from the book to the point that it loses the psychological dread and tension that had me looking over my shoulder. Other Mommy does very little to stand out from similar supernatural movies like it

Game — Clive Barker's Hellraiser: Revival

Where to play: PlayStation 5, Xbox Series X/S, Nintendo Switch 2, and PC
Lucy's verdict: Scream

Hellraiser has been everywhere recently, from its haunted house at Universal's Halloween Horror Nights to a new video game. I was very impressed with Clive Barker's Hellraiser: Revival and would highly recommend it this Halloween weekend.

It's clear it's been made by people who have a genuine appreciation for Hellraiser, as the atmosphere and the willingness to stick to canon are excellent. Iconic character Pinhead returns too, and the result is a gripping game with puzzles and heart-pounding moments.

• OpenAI CEO Sam Altman would rather have RAM put into data centers
• Altman says it's 'quite terrible' that RAM is sitting in individual PCs
• The comments haven't gone down well with consumers online

The increasing demands from data centers powering AI engines has plunged us into a global RAM shortage crisis, and the CEO of one of the companies responsible thinks the memory that is available should be in data centers rather than individual PCs.

Offering up an opinion that's unlikely to add to his popularity among the general public, OpenAI boss Sam Altman told the Cheeky Pint podcast (via IGN) that "from a global allocation perspective, actually, it's quite terrible to have everybody have a bunch of the world's limited supply of DRAM sitting in their own computer."

Individual PCs rarely make full use of their RAM, was Altman's larger point, whereas data centers often do. "You want maximum utilization in the cloud if you're trying to deal with this very supply constrained environment," the OpenAI CEO continued. "And somehow many people's intuition is the opposite of that."

The PC owners Altman was referring to have had to deal with rising prices, job insecurity, and data center pollution thanks to the rise of AI chatbots like OpenAI's ChatGPT, so the opinion he's shared is unlikely to be supported by the masses.

Not a popular opinionOpenAI CEO Sam Altman Thinks It's 'Terrible' for You to Have RAM in Your Gaming PC from r/technology

As you would expect, consumers aren't particularly pleased with what Altman has had to say. A Reddit thread discussing the comments is packed with pushback against AI, data centers, and the RAM shortage.

"It's only 64GB but he can pry it from my cold, dead hands," writes one commenter in the thread, while another is of the opinion that "[tech company executives] will destroy the planet by continuing with this mentality and then they'll promptly blame everyone else for the downfall".

The out-of-touch mentality of AI company bosses gets several mentions — as do their ethics, with bots like ChatGPT having built up their training data on vast amounts of information, often copyrighted, without paying for it. It's fair to say Altman's comments haven't gone down well.

Most analysts expect RAM to be in short supply for years to come, which is going to mean prices for consumer gadgetry continue to rise, and anyone thinking about building their own PC will have to pay top dollar for its components.