For years, the artificial intelligence industry operated under a philosophy of rapid innovation. Whilst this benefits sectors like healthcare, the initial wave of optimism surrounding generative models is giving way to a challenging reality. Numerous national security agencies and research bodies are issuing warnings regarding the potential for these models to be weaponized.

At the heart of this warning is the realization that large language models do more than process text - they democratize technical knowledge and act as decision makers rather than tools. In the wrong hands, this capability can be applied to malicious cyber operations and the subversion of critical digital infrastructure.

Historically, executing sophisticated cyberattacks required years of specialized technical expertise in exploit development and network intrusion. Today, artificial intelligence bridges the knowledge gap for individuals who lack formal training but possess malicious intent.

Recent assessments by international security bodies, such as the Organization for the Prohibition of Chemical Weapons, highlight that the emergence of data driven molecular design models means that those with limited expertise can bypass monitoring from regulatory frameworks.

New frontier AI models such as Mythos could theoretically identify alternate synthetic pathways to design toxic chemicals using ordinary laboratory reagents.

Within enterprise environments, the exposure of software supply chains and cloud infrastructure also remains an acute vulnerability. Third party applications account for a high percentage of emerging security risks, and modern enterprise operations rely on a web of digital service providers and data aggregators that were barely visible a short time ago.

Every vendor represents a potential point of entry, and a single compromised credential at a small third party service provider can grant an attacker the freedom of lateral movement within a corporate or government network.

Current public skepticism is a response to the lack of transparency in how these frontier models are trained, monitored, and integrated. Companies developing models have a responsibility to ensure that their innovations do not compromise the stability of public systems.

This requires a commitment to the responsible deployment of these tools, prioritizing national security and architectural resilience over speed to market. The industry must move away from generic statements and focus on explicit, verifiable security practices.

A new framework for technological visibility

Organizations must adopt a rigorous approach to machine visibility and network defense. Traditional perimeter focused security tools are insufficient - defensive structures must shift toward continuous internal monitoring.

This means analyzing east west traffic within an organization network to scrutinize communications between systems and understand normal data flow patterns. Anomalies must become immediately apparent so security operations teams can act before an intrusion escalates.

Response times must also collapse. The traditional multi week window that attackers enjoy gives automated threats too much leeway to cause damage. Modern network detection and response platforms shrink attacker dwell times by identifying suspicious machine behavior in real time.

Because systems prefer structured layouts and consistent schemas, defender tools must leverage network telemetry to track how these models interact with internal data stores. Security teams need to see exactly how data is being processed, ensuring that unauthorized models are not mapping corporate assets.

Governments are responding to this reality with updated legislation, such as the strengthening of national cybersecurity laws in the UK. These updates expand the scope of statutory regulations to include essential digital service providers, managed service providers, and data centers.

Tougher penalties raise the cost of non compliance, and mandatory incident reporting requires organizations to alert regulators within tight windows, often 24 hours. These legislative changes acknowledge what technical experts have warned about for years - that cybersecurity breaches on critical infrastructure are a national security threat.

Breaches and automated attempts at exploitation are inevitable. The industry must treat advanced software infrastructure with the same level of caution as critical physical assets. In a world where automated systems can orchestrate complex network intrusions, the move towards more comprehensive security measures is essential.

We've featured the best endpoint protection software.

This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

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If I'm going to watch yet another movie or TV show about a mafia-style gang in New York — because why bother in the wake of The Godfather and The Sopranos, right? — I want to come away from it having learned something new.

New MGM+ crime drama The Westies achieved this at conception, because I didn't know the first thing about the real-life Irish-American crime family of the same name. In fact, I didn't even know that they existed. But sure enough, they were known for racketeering, drug trafficking, and contract killing in Hell's Kitchen from 1960s-1980s.

I know what you're thinking: isn't Hell's Kitchen exactly where the Italian-American mob operated from in New York City. You'd be right in thinking that, and it's one of the main sources of dramatic tension across the show's eight-episode run.

Add in the fact that an FBI team has been tasked with tracking down our fictional version, led by family patriarch Eamonn Sweeney (J.K. Simmons), and you've got a proper old-school cat-and-mouse chase.

Interestingly, the biggest pro and con of The Westies is almost the same thing. While you're streaming it, you're engrossed — the storytelling itself is solid, dependable and superficially fun. But from the moment you switch it off, it will be completely erased from your mind.

Fans complained The Westies would be too tame just from the trailer — and I think they were right

After the above trailer for The Westies was released, I couldn't help but notice that the overwhelming fan response was to criticize scenes for being "too tame" compared to what mob behavior would have been like at the time.

Now that I've watched the entire season, I have to agree. Even if you don't know the story of the Westies, you're tuning into a gangster crime show expecting a severe level of violence — or even just an overarching sense of nasty brutality.

Of course, blood, guts and gore don't make a story any better objectively, but come on... we're trying to have some fun here. On top of that, it's difficult to invest in something new if you feel as though it is holding back, especially if it's aiming for a second season and beyond.

Still, the core storytelling is both engaging and well constructed. As Eamonn Sweeney's cronies face off against the local Italian-Americans, you're as engrossed in the inevitably fatal outcome as much as you are the complicated family dynamics.

The cast is stronger than its story

(Image credit: MGM+)

Bosch star Titus Welliver plays our ragged FBI lead Glenn Keenan, with an 80s "pornstache" so commanding that it might as well have had its own acting credit. When you can get past the facial accessories, you know you're in good hands... once Harry Bosch, always Harry Bosch, if you get what I mean.

If anything, I wish we had more of Simmons himself on screen. Sweeney isn't exactly the Don Corleone type, but it feels as though Simmons has somehow been a mobster boss in a former life. If you're selling him as number one on the call sheet, let's see that translated in each episode, please.

Really, I'm looking for holes when there aren't any — or at least I'm ripping tiny damaged flecks in the story's fabric into gaping tears. Because we've been so spoiled by shows such as Peaky Blinders and MobLand in recent years, we have to hold everything that comes after to an incredibly high standard.

Truthfully, The Westies just doesn't meet it. Not because there's anything wrong per se, but because the competition is so tough. It's kind of like studying really hard for an exam knowing you're going to get creamed by the kids who are naturally better at the same subject. Thems the breaks, so just enjoy the ride while it lasts.

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At most professional workstations in enterprises, you will see dual monitor setups on people’s desks.

A few years or even a decade ago, it made sense to extend the widely spread single 24-inch monitor setup, which was indeed too cramped to check your emails/notifications and work on your tasks simultaneously.

So businesses had increasingly adopted dual or multi-screen setups to increase the productivity of their workforce. More screen real estate, achieved easily.

Or so people thought, until the compromises started to become visible.

You see, you will have to work with twice the video cabling, twice the power cables, twice the power consumption.

If a dual-monitor setup is from different brands or models of displays, it was also not guaranteed that you will have the same resolution, same colour grading, same brightness or contrast, so it was a “stop-gap” solution to simply offer more space back then. And it worked, kind of.

In the meantime, the display market changed quite a lot. Ultrawide monitors, with a 21:9 aspect ratio, initially featured in the gaming scene for their increased immersion in games and movies, found their way into the business sector.

Even wider displays, with a 32:9 aspect ratio became more and more popular, since they can replace exactly two 16:9 usual monitors, with no bezel in between, offering a fully usable horizontal landscape.

In certain sectors, such as video editing and music production, where users work with long timelines, or in banking and commerce, where office workers use long and detailed spreadsheets, the entire workflow benefits from more horizontal real estate.

In my mind, I see five main topics why today businesses need to shift towards a single ultrawide or superwide display instead of multi-screen setups.

Bezels that distract

In a usual dual monitor setup, you set up the desk with two 16:9 displays side by side and place the chair in the middle of both displays to have an equal distance away from the screens. But this initial alignment already causes the first and biggest distraction.

In the middle of your central field of view, you will see the right bezel of the left screen, and vice versa. Your primary focus area is filled with bezels, in older displays even as thick as several centimeters.

If you want to use both monitors with a single program at once, such as a long spreadsheet or a video/audio timeline, this “bezel” issue alone breaks your focus and productivity, making following rows or timelines more difficult than a single monitor setup.

(Non-)Ergonomics that hurt

Dual setups usually mean one of two things. Either, both displays are placed side by side with a straight angle. Which means, your eyes will have more distance towards the side edges than towards the center of your field of view. Or they both are slightly angled towards the center .

In both cases, you will either keep twisting your neck left and right all day long, or you will work off axis for hours. To make matters worse, if none of the dual monitors offer an ergonomic, height-adjustable stand, with tilt and swivel capabilities, you will often try to readjust them to your posture.

A single, curved, ultrawide or superwide display simply keeps equal distance to your eyes from the sides or the center, and its curve matches the natural curvature of your eyes.

Panels that don’t match

In a dual setup, you will try to install two identical business monitors on a single desk. If that is not possible, there are even bigger issues to deal with. If one has a different resolution or size, you will lose the uniformity between extended screens. Texts may be differently scaled, and it is quite a distraction to move windows and programs between the two displays.

If we assume that “identical” units are set-up side-by-side, the fact that they are “identical” models alone cannot guarantee the same brightness, gamma, contrast and other visual features, since all panels in most manufacturers can show some kind of variation between panels, sometimes very little, sometimes more significant.

Some monitors offer features such as “Sync” or “Link” the displays to make them appear as uniform as possible. But, by definition, a single ultrawide or superwide panel, simply is uniform and eliminates these concerns completely.

Complexity of scales

With a dual monitor setup, you will need space for two stands on the desk, two power bricks on the floor, two power sockets, more video cables and more clutter, better video cards with more video outputs.

With even larger multi-screen setups, this increases linearly and can become costly, distracting and simply clutters the workspace, when it needs to be clean and minimalistic to allow users to focus on the task at hand. A single ultrawide or superwide display simply cuts the multitude of cables and all the requirements to just one connection to the workstation.

Modern business-focused 21:9 or 32:9 displays also feature KVM switches, USB-C or Thunderbolt 4 connectivity with Power Delivery, built-in USB hubs and even DisplayPort outputs thanks to the additional space on the back for these features. The USB-C or TB4 connectivity allow easy charging of connected laptops or smartphones while also extending the display, using the same cable.

Some fully-fledged docking models also include a built-in webcam with Windows Hello easy login, and/or a RJ-45 input to route the network connection to the computers plugged in with USB to the monitor.

In short, with a modern large ultrawide/superwide display you can replace even more peripherals than just a single extra monitor.

Cost of ownership

Bringing two panels to each desk directly means double the procurement, double the power consumption, double the devices the IT department needs to check, support, replace - multiplied across every desk in an enterprise. It can get costly and quickly unmanageable.

Employing “older” displays in a dual-monitor setup as a stop-gap solution becomes unsustainable in a short time with consumption figures easily doubling.

A new ultrawide or superwide display with sustainability features built-in, such as a presence sensor, or a light sensor to adjust its consumption automatically, not only offers a much more comfortable usage for the workforce but also reduces the consumption figures for years to come.

Two monitors solved yesterday's problem at twice the cost. The businesses that are at the head of the game are the ones that have realized that one great big screen has always been the right answer from the start.

We've ranked the best 5K and 8K monitors.

This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

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Choosing the most important tech product of the past 30 years is no easy task: does the iPhone deserve that accolade? The Nintendo Switch? The Apple Vision Pro? Okay, maybe not that last one. But that's the task that T3 set itself for its 30th anniversary awards — and after much deliberation it crowned the Apple iPod as the ultimate winner.

The iPod — which launched in 2001 — was deemed to be the Biggest Product in T3's Lifetime, reflecting its popularity, its longevity and, ultimately, its game-changing nature.

“The iPod was more than just a product, it was a revolution of the whole music industry, says Mat Gallagher, T3’s Editor-in-Chief.

“What started with 1,000 songs in your pocket introduced the world to iTunes and paying for digital music. Though ultimately, the iPhone made the iPod redundant, without the iPod the iPhone wouldn’t have existed.”

T3, which launched in 1996 and which is owned by TechRadar's publisher Future, also honored two giants of the past 30 years with special anniversary awards: Tim Berners-Lee, inventor of the World Wide Web, was named British Icon, while Apple's outgoing CEO Tim Cook was declared Person of the Year.

(Image credit: Future)

The awards cover 84 categories in total, across everything from kitchen tech to transport and from smartphones to smartwatches. The prestigious Product of the Year went to the Adidas Adizero Adios Pro Evo 3, while Garmin picked up Brand of the Year and the Samsung Galaxy S26 Ultra took the Readers’ Choice award.

Meanwhile, Lego Smart Play won the Tech Innovation Award and the Suri 2.0 electric toothbrush took the Sustainability Award. There was also four Design Awards winners, which were voted for by a panel of industry editors including TechRadar's own Global Editor-in-Chief Marc McLaren; the Nothing Headphone (1) and Dyson PencilVac were among those picking up honors there.

You can check out all 84 winners on T3 now, while the anniversary edition of the magazine is onsale now.

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"I just can't watch it... I don't want them to ruin what's already been" is a direct quote from my 60-year-old mother when I told her that Netflix was set to re-adapt the Western family drama classic, Little House on the Prairie.

The tales of Laura Ingalls Wilder's real-life childhood have always held a distinct sense of importance in my household. As a child, my mum raced through the original book series — and encouraged me to do the same when I was old enough — and voraciously watched all nine seasons of the 1974 TV show when she was 12.

As with any classic story that's being readapted for the umpteenth time without much in the way of explanation as to why, there was always going to be a valid sense of trepidation around bringing the Ingalls family back to life. But as an initial skeptic, my mind has been changed after watching all eight episodes.

Sure, it resembles the Hallmark series When Calls the Heart a little too much for my liking (and has a lot of underlying issues surrounding how it looks, but more on that later). But watching Laura Ingalls (Alice Halsey) navigate moving to a new town reminded me how important it is to be brought back to the core things that matter in life.

We so often get lost in overhyped marketing, complicated lore, and visual effects that the core components of storytelling no longer have merit on their own. There's no big dramatic narrative in Little House on the Prairie, just family, feelings, and a strained sense of love.

TV is stripped as far back as the Ingalls' bare wooden house, and I think 2026 viewers will really benefit from the show's no-frills style of storytelling. That being said, there's a lot left to be desired in the bigger picture.

Little House on the Prairie still serves purpose in 2026 — even if nothing really happens

Interestingly, Little House on the Prairie neither feels like gripping, unforgettable television, nor does it feel like placid, put-on-in-the-background streaming. Your mind can go blissfully numb while watching, but subconsciously, you're being recalibrated.

It's not perfect, but empathy, understanding, and a childlike sense of wonder are bursting from the seams here. Seeing life through Laura's eyes automatically realigns us to what's important in life — respect, understanding and a willingness to grow. Halsey is a knockout in the role, and you want to strive to be a better person just by watching her open heart expand even further.

Frankly, our child actors are running rings around the adult cast in general. Together, they carry the weight and heart of the show and have more chemistry between them than any of the parental figures, including dad Charles (Luke Bracey) and mum Caroline (Crosby Fitzgerald).

Youngest Osage member Good Eagle (Wren Zhawenim Gotts) is another standout and a testament to the suitable level of sensitivity when it comes to navigating Native American history. This could have so easily backfired or been grossly overlooked, but instead feels evenly tempered.

You couldn't pay me $1000 to pick Little House on the Prairie episodes out of a Netflix lineup

(Image credit: Netflix)

I'm honestly sick of complaining about this, but the biggest drawback of Little House on the Prairie is undoubtedly its look. This means that episodes look exactly like any other period drama or Western content that Netflix has ever made. But who is surprised?

Once again, this takes me back to my ongoing argument that the streamer uses the same lighting, visual style, and effects to mold its content into one, homogenised, cookie-cutter preset. Why? I still haven't figured that out. But if it's to brand Netflix content into a signature style, the result falls flat.

Netflix likens the new series to pre-existing hits such as Virgin River and Ransom Canyon, and if you took away the bonnets, you'd have a difficult time knowing which show was which. I yearn for a sense of individual creativity when it comes to this aspect of the streamer's creations, and it looks like I won't be stopping anytime soon.

This is also the closest Netflix has come to straying into Hallmark territory in its original content. What I mean by this is that the drama is often so twee that you'd expect someone to randomly burst into song like it's a production of Oklahoma!

It can be grating, but if you look past the form, the content is meaningful. Season 2 has already been renewed, and unexpectedly, I'm already looking forward to it.

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For the last few years, most AI infrastructure conversations revolved around the massive scale of AI training.

The AI training factories that leading AI companies have been building to develop frontier models and lead the AI race are nothing short of impressive: hundreds of thousands of GPUs, power consumption comparable to a medium city, and tens of petabits per second to scale training across multiple campuses.

But, as AI adoption accelerates and its applications expand, a larger infrastructure challenge is set to grab the spotlight. The new, real, and sustained pressure on networks is coming from the demand side of AI: inference.

Inference is what happens every time someone asks a chatbot a question, drops a file into a productivity tool for analysis, or relies on an AI-generated summary inside their inbox or search results. On a per-query basis, the traffic generated is lightweight, nothing comparable with a massive training run.

Now multiply that by the number of people interacting with AI across the globe – and consider that each time more it involves video, images, and supporting files – and you can see where the next major network demand driver is emerging.

With inference, the growth curve is steeper, global, and widely distributed, and it is now reshaping how data center connectivity is designed and the broader network ecosystem that connects cloud regions, metros and continents.

The inference inflection point

Even more powerful than users actively embracing AI faster than any technology before is the compound effect of AI features being injected into platforms that already serve billions.

Just take a look at your technology ecosystem and no doubt you’ve got AI capabilities now embedded in your search engine, email, office software, maps, social feeds and your smartphone. Embedding AI into those products is ensuring instant, global access and inevitable overwhelming usage.

The result is staggering growth in inference volumes. Take Google, for example, which reported the number of AI tokens it processes monthly increased 50 times year over year in early 2025… and then doubled it again just two months later and continues to grow at breathtaking pace, as seen on the 60 percent quarter-over-quarter token growth announced on April 2026.

Efficiency gains at the hardware and algorithmic level help attenuate the demand for additional resources, but nowhere near all of it. Delivering this increased inference volume requires the accelerated deployment of new GPU capacity and in a quickly growing number of inference data centers distributed across more geographies.

That geographic distribution is the first reason inference is not just a compute story but, at its heart, a networking story.

From text to video: multimodal models’ impact on the network

Until recently, AI's contribution to overall internet traffic has been limited. A text prompt and a text response amount to a few kilobytes — negligible next to a single minute of video streaming.

That’s changing quickly.

Multimodal models analyze and generate images, audio, video and 3D content. A user uploading a short HD video clip for analysis or editing pushes several megabytes upstream in seconds.

Researchers, students, and workers are increasingly pumping collections of documents into models to summarize key findings and generate detailed reports. Cloud-based video analytics that process camera feeds to provide insights and alerts are finding their way into viable business models.

Multiply those interactions by hundreds of millions to billions of users and inference traffic becomes a major driver of distributed and pervasive traffic flows.

Reasoning models add a second stressor. Rather than producing an instant response, they break problems into multiple internal steps, often pulling in supporting information in real time. A single user-visible answer can sit on top of dozens of background retrievals, sending megabytes of data between models, storage systems and external sources, much of it crossing data center boundaries.

And more pressure on the network comes from context window expansion. Frontier models can now ingest enormous prompts: think entire document sets, conversation histories, retrieved knowledge bases and more. Retrieval-augmented generation has become a widely adopted technique for many enterprise AI applications, and it involves injecting contextual knowledge into the model prompt on every query.

All told, these trends mean inference is no longer a lightweight workload from a network perspective. It is becoming a dominant driver of traffic growth, both between data centers and between users and the AI infrastructure.

How the DCI focus needs to shift

AI models are now distributed across regions, and usage signals and reinforced learning feedback must flow back to the centralized intelligence.

Multi-step and disaggregated inference workflows are increasingly spanning sites with complementary capabilities; think one for prefill focused on high-compute, large context processing, another for decode centered around low-latency token generation and memory and cache efficiency.

And sovereign AI requirements are pushing workloads into specific jurisdictions, multiplying the number of facilities that need to be tied together with high capacity and reliability.

Typical inference DCI links already operate at multiple terabits per second per route. The number of routes is growing alongside the capacity of each one, driven by more resilient and diversified interconnect topologies combined with a surge in the volume and geographic distributions of emerging inference-driven AI data centers.

Interconnecting inference data centers is just one side of the equation. The other involves connecting users, agents, things, and organizations to run their inference workloads across this meshed infrastructure.

Multicloud onramps are evolving to enable the movement of large enterprise datasets across AI platforms. More symmetric broadband access and scalable aggregation will be needed support widespread cameras to upload video for analysis on the AI cloud. The entire networking ecosystem needs to adapt.

So how do network operators keep up with demand and service providers take advantage of these trends?

Connecting the Dots – or Tokens

Network operators are already responding with planning centered on scalability, flexibility, efficiency, and security. To maximize capacity of every fiber pair—a resource that has never been more valuable and sought-after—they are adopting coherent optical platforms and systems capable of 1.6 Tb/s per wavelength.

Lumen Technologies, for example, is one such network provider that is building for tomorrow. It’s expanding its network at incredible speed, and to do so is leveraging a high-bandwidth 1.6 Tb/s coherent transceiver.

Additionally, the variable and diversified nature of inference traffic patterns make static networks less than ideal. Many operators are thus turning to AI-assisted multilayer network control to shift capacity and optimize performance in near real time.

Again, Lumen is a prime example of this; by leveraging a rich control suite the provider is gaining comprehensive visibility and maximizing usage and performance of its fiber assets from one point of control.

And to tie it all off, as inference traffic often includes sensitive data, network operators are baking in encryption at the optical layer within any new DCI deployment.

Inference workloads are evolving faster than any forecasting model can keep up. The networks best positioned for the next five years are the ones designed to scale in capacity, reach and intelligence without requiring major upgrades each time the workload spikes.

Training defined AI's first wave of infrastructure buildout. Inference is shaping its second – one much more globally distributed and intricate that will transform the networking landscape.

Use the best business cloud storage to manage your data.

This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

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Fan technology has made huge leaps in recent years, with more powerful and quieter motors, misting attachments, and AI-powered person-tracking all promising to keep you extra cool when the weather warms up. But which fans actually deliver, and actually keep you feeling refreshed on sticky summer days?

We test dozens of new fans every year on TechRadar, and to help you pick the best one for you, I've rounded up the five that have really impressed me over the first half of this year, from brands including Shark, Dyson, and Dreo.

Dyson HushJet Mini Cool

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Release date: April 2026

Score: 5/5

It's a lot pricier than your average handheld fan, but the Dyson HushJet Mini Cool is also a lot more powerful, and unlike flimsy plastic devices, it's built to keep you cool for many summers to come. Despite its small size, the HushJet Mini really packs a punch, even on its lowest setting, and the highest options feel like a cold hairdryer blowing in your face. It's comfortable to hold, can stand on its end for use as a desk fan, and comes with a strap that lets you wear it around your neck. You can twist the angled nozzle to aim the airflow directly at your face and neck for quick relief on sweaty days.

Dyson claims battery life of up to six hours, but in my tests it continued running for almost exactly six and a half, which is impressive for such a compact device that shifts a lot of air even on its lowest setting. It's not quite as quiet as the Shark ChillPill below, despite Dyson's HushJet nozzle, but that's understandable considering it's basically a portable tornado.

Read our full review

Shark ChillPill

Future / Becca Caddy

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Release date: March 2026

Score: 4.5/5

Another excellent handheld fan, the Shark ChillPill has a unique twisting design that lets you place it on a desk and angle the airflow at your face, plus three different cooling attachments: a regular fan, a misting fan (with a small reservoir for water), and a metal cooling plate that you can press against pulse points. The misting feature is my personal favorite, with continual and intermittent options — the spray is fine enough to evaporate on contact so it won't make your hair and clothes wet.

It loses half a star compared to the Dyson fan due to its higher price tag and less powerful motor — the ChillPill can reach up to 25,000rpm, while the HushJet Mini Cool can reach 65,000rpm — but the Shark is quieter. During my tests it ranged from 46dB on its lowest setting through to 67dB on the highest, making it a more discreet option in public.

Read our full review

MeacoFan Sefte Pro 10in Table Air Circulator

Future / Becca Caddy

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Release date: May 2026

Score: 4.5/5

Air circulators are designed to move a large volume of air around a room rather than direct a focused stream in your direction, and the 10-inch version of the MecoFan Sefte Pro does this extremely well. You can run it directly from the mains, or from its rechargeable battery, so you can carry it around the house with you. This works particularly well when paired with the Sefte Pro's Eco mode, which adjusts the air circulator's power depending on the temperature.

I used the MeacoFan Sefte Pro during the last heatwave, and it was a real life-saver at night. Its sleep mode is almost silent, and its remote control means you don't need to get out of bed to activate it, and it's also available as a pedestal fan if you prefer. The biggest drawback is that it's not currently available outside Europe.

Read our full review

Dreo Smart Misting Fan 516S

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Released April 2026

Score: 4/5

The Dreo Smart Misting Fan 516S is another fan that keeps you extra cool with a super-fine spray of water, and our reviewer Harry Padoan said that "it added a nice degree of coolness without making any mess or feeling too intense". The 1.3-liter tank is large enough to keep misting for hours on end, and it's easy to switch to fan-only mode once you've had enough.

It's very reasonably priced too, coming in at $99.99 / £99.99 (about AU$140). That's not bad at all for a misting fan with app controls, and compatibility with both Amazon Alexa and Google Home, so you can operate it using voice commands.

Its lowest mode is quiet enough to avoid disturbing your sleep, though Harry found the turbo option loud enough to break his concentration, so it's best reserved for exceptionally sticky days when you want to just slump on a chair and do nothing.

Read our full review

Dyson Find+Follow Purifier Cool

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Release date: June 2026:

Score: 4.5/5

As you can guess from the name, this fan's key selling point is its ability to detect motion and follow you around the room, so you're never beyond range of its refreshing jet of air, even when you're doing chores, working out, or pottering about the kitchen — all of which are usually extremely unpleasant in hot weather. Paired with its extra-wide range of motion, this could make it the only fan you need.

It has Dyson's signature bladeless design, and our reviewer John McCann said it "delivers smooth air flow that feels like a natural breeze moving through your home, rather than the harsh buffeting you get from some other propeller and tower fans." It's extremely quiet at night (dropping to as low as 20dB), but delivers real cooling power as well.

It's the most expensive fan in this roundup (indeed, it's one of the priciest fan/air purifier combos on the market) but it's hard to argue with its sheer performance. If you've got the budget to spare, it's packed with premium features that really work. I only wish it offered vertical oscillation as well as horizontal.

Read our full review

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Businesses do not lose time on agreements - or any other business process - because they lack AI tools. They lose it because the steps involved, like contract intake, review and approvals, still move through disconnected systems, inboxes and document versions.

There is an opportunity to embed AI where work actually happens so that talent spends less time on routine admin in favor of work that requires judgment and negotiation - and offers growth and interest.

Most organizations are looking for AI gains in the wrong place. The deeper issue isn’t a lack of access to intelligent tools, but poorly designed workflows that often go unnoticed. In agreement processes, for example, the cost shows up in slower revenue, more dull manual review, weaker visibility around important changes or areas of risk, and unnecessary pressure on legal, procurement and HR.

AI becomes useful when it is built into those workflows to automate repeatable tasks, apply consistent policy checks and help teams move faster without losing control.

AI projects underperform when they're bolted onto broken processes. Instead, redesign existing processes, or reimagine them completely. Many users treat AI as a layer when deeper results come from reworking how tasks move across teams and how people spend their time interacting with each other.

Contract management - better called ‘agreement work’ - is a good example because though it touches revenue, supplier management, hiring and compliance, it often still runs through fragmented handoffs and manual reviews.

Deloitte research calls this the “agreement trap”, with poor agreement management costing businesses significant time and value - nearly $2 trillion in lost global economic value.

That multi-trillion-dollar figure is the sum of thousands of small frictions inside every organization. Teams lose time on intake, triage, chasing status, checking standard clauses and routing approvals.

Highly skilled people are pulled into repetitive work that does not require their full expertise. Then, deep insights on key people, mechanisms, and alliances sit locked up in static documents, not being used within the knowledge base of new intelligent solutions used to set corporate strategy.

Workflow matters more than innovation hype

Tasks and processes are the challenge that technology offers a solution for, and they outlast whatever technology solution is applied. Within agreement management for example, legal teams are there to review and remove risk, yes, but they also act as traffic controllers for broken processes, ensuring the task is moved onward to completion.

Procurement and HR face similar issues when requests arrive inconsistently and progress can be hard to track.

Early lessons in AI implementation have shown leaders that AI is most effective when the underlying workflow is structured. If the process is unclear then AI can accelerate confusion at scale.

Those with tech expertise and skill in workflow creation design can standardize rules and responsibilities such that AI will support the consistency and speed in a well-designed system.

So, a strong first question isn’t “where can we deploy AI?” It’s “where do existing workflows force skilled people to do routine and less valuable work?”

In agreements, that includes comparing terms against policy, flagging deviations, chasing approvals, and surfacing the subsequent step for the following decision-maker. AI works well here because the task is repeatable and the human still owns judgment.

With AI embedded in the workflow of this example, routine review is automated so standard clauses and known risks are checked quickly. Teams work from shared playbooks, making reviews more consistent.

Then progress becomes visible across the process, with fewer requests disappearing into email chains, sitting with absent people, or in a game of pingpong.

An AI-assisted review compares contracts against pre-approved playbooks, suggests redlines inside the workflow, centralizes intake, review and approvals, prompting the person, rather than the other way around.

The need for speed (with control)

Faster does not have to mean riskier when control of the workflow has been tightly defined. In any business managing a workflow, whether agreements and contracts or anything else, the best use of AI is to make business applications more consistent, with human experts able to spend significantly more time on areas like exceptions, negotiation and complex risk.

Used well, AI allows experts to focus on the areas where nuance matters most - just when it’s most needed.

Agreements cut across every major business function. Poor agreement workflows affect deal velocity, supplier onboarding, compliance and employee processes at different points in the workflow. That makes agreement management part of the whole digital workplace conversation, not a legal-contractual-sales-back-office issue.

More recent Deloitte research found that companies with advanced agreement management are more likely to outperform financially, and that 85% of organizations with advanced agreement management say it contributes to strategic goals.

It’s proof that the market is shifting towards structured agreement management solutions for areas of risk reduction and revenue acceleration. Leaders are building AI into structured workflows around intake, review and approvals because that is where their users feel the friction most acutely. It’s been that way since the first complex contract between two organizations was signed.

The next AI gains will come from everyday work

This example from agreement management shows that the next phase of enterprise AI can be less about eye-catching claims and more about fixing the everyday workflows that shape how humans do real business.

Agreements are one example, but they make the lesson clear: AI delivers the most value when it helps people do real work fast, consistently, and visibly. But more than that, it shows how by rethinking the invisible we reassess what is possible, making business work better.

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It’s no secret that the data centers that form the hidden engine of today’s AI boom can consume huge amounts of water, mostly for cooling purposes, and dealing with this issue is critical for any organisation in the technology sector.

Worldwide, the International Energy Agency (IEA) estimates that the data center sector consumes 560 billion liters of water per year today, and projections suggest this figure could soar over the coming years, reaching as much as 1,2 trillion liters per year by 2030, according to a recent government report on data center water use.

Taking measures today can help to mitigate this.

It’s very possible for data centers to reduce the drain on local freshwater resources, while also curbing their energy use, and all without reducing performance.

Here are five key issues which are driving water consumption in data centers today, and steps that data center operators can take to mitigate them.

1 Open-loop evaporative cooling is a problem

Today, many data centers still rely on ‘open-loop’ evaporative cooling systems, where hot water is sprayed onto pads to be cooled. This older form of cooling architecture means that data centers consume significant volumes of water, which has to be continuously replenished as it evaporates.

But more modern sealed liquid cooling systems offer a way to mitigate this source of water loss, by ensuring water is reused efficiently, while not impacting performance.

Today’s closed-loop systems reuse the same water over and over again, using liquid-to-air heat exchangers for cooling, rather than evaporating water. These warm-water cooling systems are sealed, so that after the system is filled in the first place, water loss is extremely low under normal operating conditions.

Instead, the systems recirculate the same water inside a sealed environment, so no water is consumed at all during normal operations. Water is not discharged from the system, and it never evaporates: instead, it absorbs heat directly from high-performance components and transfers it out of the system.

Closed-loop systems are designed not to be consumption-driven infrastructure but instead are recirculating, self-contained systems. This technology will be vital to reducing the water demands of data centers worldwide.

2 Data centers still attempt to cool the room

In too many data centers, cooling is highly inefficient, meaning that up to a third of the data center's total energy use can be 'spent' on keeping components cool, with fans working to keep the data center's temperature low as well as cooling individual machines. Modern technologies such as direct-to-node and direct-to-chip cooling are offering a new way to curb this inefficient energy and water use.

In direct-to-chip cooling, cold plates are attached to heat-generating components such as GPUS, with coolant liquid flowing through the plates to absorb heat and transfer it out to a heat exchanger. Liquid cooling techniques such as direct-to-node cooling can remove up to 98% of heat from servers, operating on a closed-loop system which means water is not wasted.

By capturing heat directly at the source, at the processor level, rather than attempting to cool entire rooms full of hot air, data center operators can reduce energy demand and also place less strain on local water systems. This also produces higher-temperature outputs which are easier to reuse.

3 Generative AI is driving an increase in compute density

One key reason for the increasing water use of data centers is simply that the AI boom is driving more demand for cooling. Generative AI is powered by Graphics Processing Units (GPUs), which can consume between five and 10 times more energy than Central Processing Units (CPUs). But we are also seeing an increase in compute density, as more and more of these components are packed into smaller areas, using techniques such as 3D silicon stacking.

The demands of AI workloads mean that warm water closed-loop cooling is coming into its own as a low-energy solution. Even at high rack densities, warm water systems (which can use inputs at much higher temperatures) enable high performance while also curbing water use and removing evaporative cooling.

To take one example, DreamWorks Animation adopted warm-water cooling systems for high performance computing (HPC) and recorded a 20% performance increase alongside reduced cooling requirements.

4 Projects to reuse data center heat are still too rare

In data centers, almost all of the electricity used is ultimately converted into heat, and today that is a resource that is underused. In fact, the heat has been traditionally treated as an unwelcome byproduct to be removed and then discarded. But this can be transformed into a usable resource, which can deliver heat for residential communities, commercial buildings and even district heating.

This reuse is still too rare, but pioneering projects across Europe are already showing the potential of the idea for reducing reliance on fossil fuels, cutting energy costs, and boosting resilience. Projects in Ireland and Scandinavia are already reusing heat to warm homes and businesses.

Older evaporative cooling systems are wasteful, and shifting towards closed-loop systems where water is reused, heat harvested and given to the wider community are a prime example of how waste can be turned into wealth.

5 Data centers are still in the wrong locations

At present, too little thought is given to the location of data centers, meaning that the facilities can be located in areas where there is already strain on local freshwater supplies.

Going forward, organizations will take this factor into account in order to deliver more sustainable data centers which ‘fit in’ to their local environment: research found that 45% of IT professionals believe current data center design does not support sustainability goals.

In the future, data centers will be put in carefully chosen locations to optimize renewable energy use, and also to ensure their water demands are not at odds with their local environment. This could include data centers built into urban areas with a goal to reusing waste heat to warm local homes - or even to offer spa-like experiences to local people.

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• Productivity and AI-induced cost reductions are actually dropping
• Most businesses plan to continue spending on AI regardless
• Only 35% have full visibility into costs, reporting lower ROI

Despite ongoing deployment, many organizations are apparently still struggling to achieve ROI from AI, with new KPMG data revealing growing accountability, governance and workforce pressures.

The report found productivity gains actually fell from 42% to 35%, with decision making speed also dropping from 41% to 36%. Even costs were challenged, with cost reductions slightly falling from 31% to 29%.

But planned AI spending data indicates a near-identical value compared with the quarter before, implying companies could be investing blindly without detailed strategies spelling out where they would get the most returns.

AI ROI is still a challenge, years later

Backing that optimism, four in five (79%) say AI would remain a top investment priority even if a recession occurred, with a similar number (78%) confident they can future-proof their AI strategies accordingly.

Costs are clearly being scrutinized, though, with 22% now factoring in lower-cost AI models (compared with 15% previously). Nearly half (49%) have even delayed, paused or shrunk their AI strategies over cost concerns.

"AI is now as much a financial management priority as it is a technology one," Global Head of Advisory Rob Fisher summarized.

Clearly, model capabilities are no longer driving AI investments as companies start to look more closely at how much they're paying for services and the promised returns. And with only one in three (35%) having full visibility into AI operating costs currently, much work needs to be done here.

The report even argues that those with full AI cost visibility are 5x more likely to report ROI. "We’re seeing a clear divide between organizations with leadership accountability at the top and those without," Global Head of AI and Digital Innovation Steve Chase commented.

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It’s no longer a question of if – only when. The promise of humanoid robotics is finally crystallizing into a commercial reality.

This new era will create a sector with the heft to rival megaliths like automotive and computing.

But we’re not there yet, and though large and well-known manufacturers are investing billions in development, with some clear leaders, the robots themselves remain in adolescent stage.

My advice? Treat them like any other adolescents and don’t rush them into adulthood before they’re ready. Take a crawl walk run approach to innovation, build capability layer by layer, and let maturity emerge from momentum. This is the fastest way to win the race to commercial deployment and value.

Development teams are making progress by the day, stimulated and inspired by the obvious appeal of a robot shaped like a human, operating deftly and effectively in any environment designed for people, using existing tools and infrastructure. But we’re clear on the obstacles, and equally clear with business leaders on the need to understand the technical, practical, regulatory and social factors that stand between them and the market.

That said, there’s no doubt in my mind that humanoid robotics represents not just a new way to win – but a way to win big. Companies that are first to crack the challenges I’m about to describe will seize powerful advantages. They’ll define industry standards, accumulate proprietary data and build customer relationships that late entrants can’t hope to replicate.

Early deployment – even for tasks like packing boxes – generates real-world learning that accelerates improvement.

The human-shaped challenge

The formidable gap between impressive (if carefully pre-choreographed) demonstration videos and actual deployment is marked with several key technical challenges, not least the physics of the human form. Balance and locomotion are among the hardest problems in robotics. We walk with a complex, energy-efficient gait that takes years to learn. Replicating for a robot requires real-time processing of sensor data, continuous adjustment to shifting weight and the ability to recover from unexpected disturbances.

Reinforcement learning and improved actuators have produced robots that can walk, run, and even perform parkour in controlled settings. But real-world environments are a chaotic mess of uneven floors, unexpected obstacles and slippery surfaces – and current systems still struggle here.

Dexterity and manipulation are equally daunting. Human hands have 27 degrees of freedom and extraordinary tactile sensitivity. Once learned, we can thread a needle, crack an egg, or catch a ball without conscious thought. Robotic hands have improved substantially, but fine motor control, delicate force application and adaptive grip remain limited. Tasks that seem trivial to us are extraordinarily difficult for machines.

Our research notes the promise of perfecting fine manipulation as physical AI teams progresses from lab proof-of-concept to stable pick-and-place cycles with real hardware. It’s tough, because it’s all about building new capabilities from scratch. But with a growing confidence in areas like fine manipulation, human-robot interaction and whole-body control, we’re moving ever closer to significant breakthroughs.

A new way to look at perception

Perception and decision-making represent further technical hurdles. Robots must interpret cluttered, dynamic environments in real time, distinguishing between a crumpled napkin and a spilled hazard, recognizing when a human is about to cross their path, and making split-second decisions about how to respond. Current AI can handle many of these tasks in isolation, but integrating them into a coherent, reliable whole is a work in progress.

As these technical problems are solved, economic viability will come increasingly into focus. While some humanoids are advertised with a cost of a few thousand dollars, these are essentially expensive toys rather than effective workers. Top-of-the-range humanoid robots cost hundreds of thousands of dollars, far more than what most businesses can justify for tasks that humans perform adequately.

Manufacturing at scale could bring prices down, but the path to a $20,000 or $30,000 unit that could potentially result in productivity and cost efficiency gains remains uncertain. Robot-as-a-Service financing models will enable early up-take but the underlying cost challenge will remain a blocker to mass adoption.

Getting closer to real-world usefulness

Personally, I’m optimistic about overcoming the remaining challenges. There is work to be done on operational reliability (we’re not yet there with machines that operate autonomously for extended periods without much intervention); legal frameworks; physical safety (regulatory guidelines are in their infancy); and even public perception (resistance to automation has derailed past initiatives.)

The key is to stay focused on the end game. With the remaining hurdles diminishing, the direction of travel is irresistible. Every small breakthrough – like that box packing example I mentioned earlier – brings us closer to real-world usefulness and every early deployment teaches us something we can’t learn in the lab. Build steadily, crawl-walk-run, and the rewards await the ambitious first movers.

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Genki Attack Vector: Review

The Attack Vector is a basic set of covers and grips for your Switch 2 and Joy-Cons, designed to protect your console and improve ergonomics in handheld mode.

The plastic covers for the console and both Joy-Cons are quite plain, with a totally black finish and no extra flourishes. They’re reasonably thick and durable, but also light.

(Image credit: Future)

The back cover for the console is easy enough to snap on. It should offer sufficient protection from scratches and the like, and I appreciated the fact that the inside has a small patch of rubber, which makes the fit more snug.

Like the best Nintendo Switch 2 accessories, the Attack Vector doesn’t interfere with the console’s stand, ports or buttons, thanks to the various cutaways. They’re still quite easy to use, although the deep recess that’s created around the power and volume buttons means you may have to press these more with your fingernail than your fingertip. What’s more, the Switch 2 still fits in the dock with the cover attached; in fact, the fit is actually better, since it prevents it from wobbling at all.

(Image credit: Future)

Snapping on the Joy-Con covers is a little trickier, but it’s easier if you hold the detach button on each Joy-Con as you slide them on. These also have a small rubber backing on the inside for a more secure fit.

The Attack Vector comes with three sets of grips to attach to the back of these covers, of varying shapes and sizes. These have a solid build quality and a nice finish, with a rubber texture that feels comfortable, grippy, and hardwearing.

(Image credit: Future)

Attaching these grips is a little difficult at first. You have to line up the grooves and slide them on blindly, which can result in numerous failed attempts. However, I soon got the technique down and managed to attach them without issue thereafter. Once attached, they’re very stable; at no point did they come loose while I used them.

The two larger grip sets are called the Anchor and Balance. I found the latter set very comfortable, as the sides of the grips fitted the center of my palms naturally as I played.

(Image credit: Future)

The Anchor grips are shorter and feature ergonomic indentations at the bottom. I didn’t find these as comfortable or as secure, since only my last two fingers fit in these indentations. I suspect they’re designed for smaller hands than mine. Ultimately, though, both grips make handheld mode more comfortable and secure, especially when holding the Switch 2 upright, as you have something more substantial to hold on to.

There is a problem with these grips, though. Their weight and leverage mean that the Joy-Cons can rock back and forth slightly in the console, which is a little disconcerting. This rocking is minimal under normal use, and it never resulted in the Joy-Cons disconnecting from my Switch 2 during testing, but I do worry that eventually their hold in the console might loosen.

(Image credit: Future)

No such issue is created by the Feather grips, though. These are the smallest set and only cover the middle section of each Joy-Con. Unlike the other grips, they barely protrude outwards, offering a much more subtle feel. But given the stock Joy-Cons’ absence of a grippy surface or an ergonomic shape, I was still pleased with the limited support they provided. What’s more, I found them ideal when the Joy-Cons were detached from the console, since, unlike the other sets, they offer enough bulk to get a secure grip without impeding the reach of my thumbs to the controls.

At £40, the Attack Vector isn’t exactly cheap. However, the covers provide a good fit and basic protection for your console and Joy-Cons. Meanwhile, the comfortable grips for all types of hands are great if you play in handheld mode often, especially in a more upright position.

(Image credit: Future)

Genki Attack Vector review: Price & availability

The Genki Attack Vector costs £39.99 and is available now in black only. This isn’t particularly cheap for a case and grip combination. But the quality of the product, as well as the inclusion of three different types of grips, may be worth it to those who take their handheld gaming seriously.

Should I buy the Genki Attack Vector?

Buy it if…

You’ll be using handheld mode a lot
The grips offer a secure and satisfying way to use your Switch 2 in handheld mode, and the three different kinds should ensure you’ll get the right fit.

You want to keep the covers and grips on at all times
The console cover is designed to fit in Switch 2’s dock, and it actually prevents it from wobbling around in there, too.

Don't buy it if…

You want to improve the Switch 2’s looks
The utilitarian nature of the Attack Vector means if offers no flair to help personalize the style of your console.

You want ultimate Joy-Con stability
The larger grips tend to cause the Joy-Cons to wobble slightly, which might lead to problems for more animated players.

Genki Attack Vector review: Also consider

Genki Dual Wield Nintendo Switch 2 Charging Station
The Dual Wield actually makes a good companion to the Attack Vector, since you can attach the Joy-Cons to the Dual Wield grip while keeping the Attack Vector’s grips in place. What’s more, this improves the ergonomics of the Dual Wield, which was one of the main weaknesses I identified when I reviewed it. And when your session is over, you can simply dock your Joy-Cons in the charging station. There are two sets of grips for two sets of Joy-Cons and two positions on the charging station. Read our full Genki Dual Wield Nintendo Switch 2 Charging Station review.

(Image credit: Future)

How I tested the Genki Attack Vector

I used the Genki Attack Vector for several days, playing a variety of games in handheld mode, including Super Mario Bros. Wonder and The Legend of Zelda: Tears of the Kingdom. I made sure to try out all three grip types. I also tested the grips with the Joy-Cons detached from the console.

I've been gaming for decades, and have used a variety of systems and controllers in that time, including various handheld systems. I've also reviewed other Switch 2 accessories and controllers before.

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Snakebyte Ergo Grip S2 review

The Snakebyte Ergo Grip 2 is a basic grip for the Switch 2’s Joy-Cons, although it has a few tricks up its sleeve.

Its design is very much a case of function over form. There’s no RGB lighting, and the all-black colorway leaves no room for levity. At least it's simple and unfussy, consisting merely of a central bar and two grip handles on either side. These handles are reasonably long but quite thin compared to more traditional controllers.

(Image credit: Future)

The build quality isn’t particularly great, it has to be said. There’s quite a bit of flex to the whole unit, although it's solid enough and the plastic feels smooth in the hand. But it’s certainly not going to challenge the best Nintendo Switch 2 controllers on this front.

There’s a small switch underneath the Ergo Grip 2 to release the central bar from the bottom of the pad, allowing it to pivot upwards and out of the way of the grip handles so you can insert the Joy-Cons. This seems a little gimmicky, and what’s more, it’s not strictly necessary: by inserting my Joy-Cons at an angle, I managed to get around the handles while the center was locked down.

I think it would’ve been simpler to engineer a solution where the handles didn’t get in the way at all, rather than have a rotating mechanism. I’m also mildly concerned about the button that locks it down. I noticed a small amount of play while it’s locked down, which could spell failure further down the line.

(Image credit: Future)

Happily, the fit for the Joy-Cons is more secure. They slot into the Ergo Grip 2 just as well as they do into the Switch 2 itself. The hold feels strong, and the handles effectively partially cover their outsides, which prevents them from being prised out easily.

In action, it’s quite comfortable. The Joy-Cons sit fairly close together, but not so close as to cause issues. However, the grip handles took me a little while to get used to. At first, I had to slide my hands upwards to reach the Joy-Cons' bumpers when playing games such as Super Mario Bros. Wonder. However, I discovered that I could slot my last two fingers into the handles’ small indents for better purchase, which helped alleviate this problem somewhat.

But there are a few more ergonomic issues with the Ergo Grip 2. The bottom parts of the grips aren’t particularly long, and what’s more, they’re completely vertical, rather than angling outwards. This meant that they didn’t sit in the palms of my hands as well as more traditional gamepads, leading to a less secure feeling of grip.

(Image credit: Future)

This verticality extends to the orientation of the Joy-Cons. They don’t angle outwards at the bottom, which is part of the reason why reaching the bumpers can be a struggle. Other grips, such as the Genki Dual Wield, create such an angle, which feels like a more natural way to use the Joy-Cons.

The Ergo Grip 2 features a USB-C port for charging while you play. There are LEDs on top to indicate charging status, although these are basic, merely lighting up red while charging and green once complete.

At 200cm, the included USB-C cable is quite long, but it's made from rubber. This contrasts with the best Nintendo Switch 2 accessories, including other controllers and grips, that come with braided cables for better flexibility. Thankfully, the cable is quite light, so I didn’t feel much resistance while playing, and I wasn’t worried about the cable disconnecting. However, it’s quite hard to unbunch, meaning it fails to maximize its entire length.

At less than £20, though, such shortcomings are easier to swallow. If all you’re after is a cheap way to securely hold your Joy-Con 2 controllers and want to play and charge at the same time, you could do worse than the Ergo Grip 2.

Snakebyte Ergo Grip S2 review: Price and availability

(Image credit: Future)

The Ergo Grip 2 can be ordered from Snakebyte’s website for €19.99, which is about £17. However, we have seen it for less than this at other retailers. This is a fair price for a Joy-Con 2 grip, especially one that features charge-and-play.

However, there are Switch 2 accessories that are arguably better value for money, including others from Snakebyte. Its Starter Kit S2, for instance, includes Joy-Con 2 grips, a case, wired earbuds, joystick caps, and a screen protector — all for about the same price as the Ergo Grip 2.

Should I buy the Snakebyte Ergo Grip S2?

Buy it if…

You want your Joy-Cons secured
The design of the Ergo Grip 2 means that your Joy-Cons are locked in place with nowhere to go.

You want to play and charge at the same time
Thanks to the USB-C port and cable, you can charge the Ergo Grip 2 as you play.

Don't buy it if…

You want formidable build quality
The release button for the pivot mechanism doesn’t feel particularly solid, which is a slight concern.

You want the best ergonomics
The upright nature of the Ergo Grip 2 means you don’t get the same ergonomics of typical gamepads.

Snakebyte Ergo Grip S2 review: Also consider

Genki Dual Wield Nintendo Switch 2 charging station
This accessory features two grips for two sets of Joy-Con 2s, as well as a charging station for them. The triangular shape of the grips creates a more natural playing angle for your Joy-Cons, although the completely flat surface of the grip and its small central hole hamper ergonomics somewhat. Still, for the price, the Dual Wield is a decent value.

Read our full review Genki Dual Wield Nintendo Switch 2 charging station review

How I tested the Snakebyte Ergo Grip S2

(Image credit: Future)

I tested the Ergo Grip 2 for several days. I played various games with it attached to my Joy-Cons, including Super Mario Bros. Wonder and Super Mario 3D All-Stars. I attached and detached my Joy-Cons several times to test the fit and pivot mechanism of the grip.

I’ve been gaming for decades and have used many systems and controllers in that time. I’ve also reviewed other Switch 2 grips, as well as numerous controllers for the Switch, PC, Xbox, and mobile.

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