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Woody the toy cowboy has faced a lot of frightening moments over the course of five Toy Story movies, but the actor voicing him for the last 30 years is trepidatious over the possibility that AI will supplant him. Tom Hanks told Entertainment Weekly in a new interview that the idea of AI replacing his voice is "a scary thought."

"Time is undefeated," Hanks said. "The question would be whether or not we could cobble together some version of me. Every word we have ever recorded in time in Toy Story is on digital media somewhere, so they could put together anything they would want."

Debates about AI in movies and film are raging even as the technology is deployed to reproduce the voices and complete performances of people who have passed away. Not to mention fully AI-generated films that otherwise employ human voice actors.

AI acting

Most entertainment projects with AI so far have generally involved the participation or approval of the performers themselves, but they also demonstrate how quickly the technology has matured. What once required painstaking effects work can increasingly be achieved with sophisticated machine learning models trained on years of existing material.

Hanks has himself been in AI-assisted productions, specifically in the film Here, which relied on AI to de-age him and co-star Robin Wright for part of the film rather than depending entirely on traditional visual effects.

Hanks' concerns extend beyond his own career. He has elsewhere suggested that his biggest worry is whether audiences will eventually stop caring whether a performance comes from a human being at all, not trusting that what they see isn't produced with AI. That feels like a more unsettling question than whether Woody could return without Hanks.

Future films

(Image credit: Disney Pixar)

There's a little irony in Hanks' comments. The original Toy Story was a technological revolution that some saw as a threat to traditional hand-drawn animation. Three decades later, one of the stars who helped usher in that revolution is looking at the next wave of technology with understandable caution.

Caution doesn't mean dismissal of AI, of course. Hanks is known for being part of projects using advanced tools like motion capture, digital filmmaking, and experimental visual effects throughout his career. His concern seems more about what gets lost when technology starts replacing the people audiences are connected with in the first place.

And while each individual use of AI can be justified as another filmmaking tool, there's still a larger question about where AI assistance ends, and replacement begins. The answer will probably depend on what audiences decide they value rather than purely technical capabilities. Movie stars are more than collections of facial expressions and vocal recordings, and recreating the performance that audiences associate with Woody, that's more than just "good enough," would be a tall order.

I've been scouting for Prime Day deals, but this one stopped me in my tracks. Currys is running an excellent summer sale on back-to-school and business laptops, but Amazon has absolutely crushed them on the price of the Asus Zenbook A14 for £500 (was £600) for Prime Day.

• Shop Amazon's Prime Day deals

This 14-inch OLED laptop features a Snapdragon X X1-26-100 processor that's engineered for day-to-day work and study tasks, alongside 16GB LPDDR5X memory, and a well-sized 1TB SSD. For general office and school tasks, that's pitch-perfect for the price.

Over at Currys, however, the exact same model is priced at £599 (was £999) for the Snapdragon-powered machine with 16GB RAM and - wait for it - 512GB SSD. So, you're getting twice as much SSD storage from Amazon at an even cheaper price. I wouldn't even look twice at Currys for this specific model while this Prime Day deal is live.

For more savings, I'm live-tracking all the best Prime Day home office deals.

Snapdragon X X1-26-100 | 16GB LPDDR5X | 1TB SSD

Excellent price for an efficient work laptop. This 14-inch OLED ultra-portable machine excels at battery life, and tailored for running office apps, emails, and web browsing. View Deal

Snapdragon X X1-26-100 | 16GB LPDDR5X | 512GB SSD

Only buy this if Amazon's Zenbook deal isn't available. It's a good price, but it's lacking the storage space the Prime Day deal has. View Deal

That's not to say the Currys summer sale is bad. In fact, having charted all the deals, I found it a treasure trove of well-priced laptops for work and study. You can see my article on the top 4 laptop deals at Currys here.

But considering the massive price difference, and the improved SSD size, I'd go for the Amazon deal all-day long (or while it lasts, which might not be long as Prime Day ends tomorrow).

We were impressed with the A14 when we reviewed this laptop. Scoring it 4 stars and awarding it a TechRadar Recommends badge, we found this ultra-lightweight MacBook Air-style Windows laptop possessed "brilliant design, capable all-round performance, and an impressive battery life."

As a budget-tier laptop, it's got it faults, but we loved the "fabulously thin and light" design and performance are impressive. Perfect, then, for campus and the commute.

• See all laptop deals at Amazon
• Shop all computing deals at Currys

It's been years since I last owned my own Kindle, as I ultimately do prefer physical copies to add to my collection, and only otherwise used my OG Kindle while travelling. However, whenever Amazon Prime Day rolls around, I do tend to second-guess myself when I see the meaty discounts on some of the best Kindles.

• Browse all early Prime Day deals at Amazon

In particular, I was tempted by the new Kindle Scribe Colorsoft; as an avid manga reader, I was super excited by the idea of freeing up some shelf space (and if you read manga, you'll know that comes in short supply once your collection grows) by reading some of my less-favored series digitally. However, after trying it for a couple of weeks, I'm only using it for its primary function: as an ereader.

Sure, I'm pretty impressed by this all-in-one E Ink notepad, comic and book reader, but especially right now, the price is a huge turn-off. Put it this way; the Kindle Scribe Colorsoft is currently $519 (was $679) in the US and £442 (was £569) in the UK.

Meanwhile, the Kindle Paperwhite is on sale for $124 (was $159) at Amazon US and £113 (was £159) at Amazon UK and the significantly more performant and multifunctional iPad 11-inch (A16) is $299 (was $349) at Amazon US and £309 (was £329) at Amazon UK. That's a $96 / £20 saving for an arguably better combination.

Below, I've detailed the key differences between each device.

Amazon Kindle Scribe Colorsoft

(Image credit: Future/Rami Tabari)Pros and cons

Pros
+Gets the basics right
+Color and Scribe features are well-packaged
+Large and sharp display

Cons
- Pricey
- Some features could use updating

The Kindle Scribe Colorsoft is the latest, most performant ereader from Amazon, offering a combination of three different Kindle types: the standard E ink display Kindle, the notepad-like Kindle Scribe, and the color display Kindle Colorsoft.

Each is useful in its own right; reading comics and manga on the Scribe Colorsoft is a delight, though text boxes that spread across panels can be cut off if you use the full page panel view. It's pretty well optimized for the task, though even in vivid mode, colors can be a little washed out.

The writing experience is great. The screen is super responsive, the stylus is comfortable in use and features a shortcut key as well as a functional eraser, and the addition of color to the display means you can select different pen and highlighter colors to create more detailed annotations.

It packs all the usual useful Kindle features (including Word Wise, which is great for younger readers or language learners) as well as AI features like note summary and handwriting-to-text conversion.

However, there are three major things to note when it comes to the Kindle Scribe Colorsoft.

First is that you can't actually use all of these features in tandem, meaning you can't markup comics or manga, though that's likely not a use case many people would want.

Second is that even outside of major sales events like Prime Day, you can get a Kindle, a Scribe, and a Colorsoft at almost the same price as this all-in-one device; and if you don't really need either the note-taking or the color display at the same time, you might as well do that.

Third is that while the large slate might be what you're looking for in terms of drawing, writing and graphic novel reading, it makes it a lot less portable than the standard or Paperwhite Kindle experience, which for me is the main reason I prize an ereader over a book.

Amazon Kindle Paperwhite

(Image credit: Future)Pros and cons

Pros
+7-inch display is great
+Fastest Paperwhite yet
+Excellent battery life

Cons
-Expensive for a mid-range ereader
-Ads on lock screen in some markets (unless you pay extra)

A step up from the basic Kindle, the Kindle Paperwhite offers a bright and beautiful screen for reading your favorite books. At this point, I'd very rarely recommend the standard base model for any reason beyond its low price, whereas the Kindle Paperwhite is genuinely enjoyable to read on, and that includes comics and manga.

With its E Ink Carta 1300 display, the 12th-generation Kindle Paperwhite offers great contrast for easy reading, a slightly larger screen, comfortable bezels for long hours of reading and 16GB storage (though we're not thrilled 4.5GB of that is dedicated to the operating system.)

If you've tried the 11th-generation model, there's a slim margin of upgrade with this newer, 12th-generation model, but if you're currently using any older Kindle Paperwhite or standard Kindle, you'll certainly feel the difference.

It's fast, the battery is great, and it excels at exactly what it was created for; reading. That's doubly true thanks to its slim profile, making it easy to grab and stash in your bag; at 211g, it's super lightweight to carry.

It's worth noting that, at list price, we're not 100% happy about the Kindle Paperwhite's value proposition. This goes for a lot of Amazon devices, which only feel like a good deal during major sales events, but for context, spend a little more on the Kobo Libra color which costs $219.99 / £219.99 and you can get a color ereader with a screen of the same size, double the storage, a more ergonomic design and writing capabilities.

Of course, if you're bedded into the Amazon ecosystem with access to its vast library of books through a Prime Membership, it's still a no-brainer.

Apple iPad 11-inch (A16 chip)

(Image credit: Jacob Krol/Future)Pros and cons

Pros
+A16 chip is very capable
+Now starts with 128GB of storage
+iPadOS 18 runs smoothly here

Cons
-No major changes over the previous generation

While the latest, 11th-generation iPad didn't reinvent the tablet-shaped wheel, it brought a nice refresh in the form of the A16 chipset, powering a fast, responsive iPadOS experience.

It's a great productivity machine, and especially when paired with an Apple Pencil, it offers everything you could want from a Kindle Scribe Colorsoft and more, with its app library including fantastic options for note-taking, drawing and more intensive creative functions like video editing; though you're better off with an Apple Silicon-powered tablet like the iPad Pro (M5) or iPad Air (M4) if that's your rodeo.

It weighs just over a pound, so it's less primed for travel, and an e-ink display offers weeks of battery life, whereas the 11th-generation iPad only stretches to roughly 10 hours with general use; that's why pairing it with a Kindle Paperwhite for your reading needs is my top recommendation.

Still, even on its own, it stands as a solid alternative to a Kindle altogether, but especially at its price, I'd wager it's a superior choice to a Kindle Scribe Colorsoft for most. After all, you can just install the Kindle app and read your favorite books, comics, and manga on the vastly superior display.

More early Prime Day deals in the US

• Amazon Devices: Fire Sticks & Echo from $18
• Amazon Haul: viral gadgets, tech & appliances from $1.99
• Apple: MacBooks, AirPods & AirTags from $29
• Beauty: 50% off toothbrushes & hair tools
• Cheap TVs: smart TVs from $69.99
• Garden: tools, mowers, planters from $24.99
• Headphones: 50% off Beats, Bose & Samsung
• Laptops: Apple, HP & Dell from $199
• Mattresses: Sealy, Serta & more from $186
• Patio: outdoor furniture, rugs & decor from $19.99
• Sports: 50% off fitness gear, treadmills & clothing
• Vacuums: Dyson, Shark & Bissell from $34

More early Prime Day deals in the UK

• Amazon Prime: sign up for a 30-day free trial
• Amazon Devices: Fire TV, Ring & Blink from £24.99
• Amazon Haul: up to 30% off
• Apple: AirPods Pro 3 for a record-low price
• Appliances: up to 45% off Ninja, Tefal & Sage
• Beauty: up to 60% off Philips & Oral-B
• Essentials: household goods from under £10
• Fashion: up to 50% off
• Father's Day: up to 50% off gifts & drinks
• Headphones: up to 50% off
• Laptops: from £149.99
• Tablets: Samsung & Lenovo from £125
• Toys: up to 25% off Lego and Tonies
• TVs: from £129.99
• Vacuums: up to 40% off Eufy & Roborock
• Wearables: Garmin & Huawei from £36.99

• Big Tech was hit with $3.5B fines over three years, Surfshark found
• Many were fined for using personal data unlawfully
• Enforceability remains a key challenge

Major tech companies have already been hit by fines totalling $3.5 billion for using vast amounts of users’ personal data to train their AI models, raising hopes that the days of AI operating in a regulatory vacuum might be coming to an end.

The figures come from Surfshark, one of the best VPNs on the market, which recently analysed 10 AI-related sanctions imposed on the usual suspects — Anthropic, Meta, Google, Clearview, Apple, Amazon, and OpenAI — between 2022 and 2026.

Disturbingly, nine out of ten fines were imposed for using users’ personal data — including biometric data, copyright-protected content, facial images, and children's voice recordings — without user consent or legal authorisation.

AI violations: which company misused our data the most?

(Image credit: Surfhsark)

According to Surfshark’s study, Clearview AI was the first, in 2022, to be fined a total of around $46 million for collecting facial images for its facial recognition database.

But the pace picked up in 2024, with five new separate fines imposed on Google, OpenAI, Meta, Clearview, and Amazon.

The size of the fines has also increased substantially, signalling a positive shift from regulatory warnings to severe financial consequences. In 2024, Meta was fined $1.4 billion for collecting users’ biometric data without consent, followed by Anthropic in 2025 with a record $1.5 billion for training its AI models using pirated books.

On a different note, the $250 million fine imposed on Apple in 2026 for AI misleading marketing practices might signal that current AI advertisement tactics might also soon become a thing of the past.

"This could be only the beginning," says Dr. Luis Costa, research lead at Surfshark. "The overarching trend suggests that accountability is catching up with innovation, and the industry must re-evaluate both how it builds AI and how it markets it."

The industry must re-evaluate both how it builds AI and how it markets it

Dr. Luis Costa, Surfshark

While regulations and authorities seem to be starting to catch up and match their punishments with Big Tech's wrongdoings, the findings continue to raise serious questions about the risks users face when using these AI platforms.

"Firstly, the scale of unauthorised data collection is unprecedented: 90 per cent of AI-related fines imposed since 2022 relate to the use of data without the necessary consent," Costa explains.

"Second, this harvesting often targets highly sensitive, unchangeable data, as seen in Meta’s $1.4 billion biometric settlement and Amazon’s fine over children’s voice recordings," he adds.

It also remains alarming that many companies fail to adequately inform the public about how their sensitive data is used, leaving consumers oblivious to the fact that their personal information is permanently baked into commercial AI models.

Better enforceability is needed

Additionally, while these fines may seem exorbitant, it is worrying that the financial impact of such punishments rarely acts as a deterrent to these large technology companies, whose market capitalisation runs into the hundreds of billions of dollars.

In its research, Proton previously found that the $7.8 billion in privacy and competition fines imposed on Big Tech in 2025 could be collectively paid by these firms in less than a month.

However, Costa argues that the issue is more complex and regulators might be working toward targeted changes. "First, regulators are escalating the financial stakes, shifting toward massive penalties like Anthropic's $1.5 billion and Meta's $1.4 billion settlements."

Additionally, a major challenge right now is actually enforceability — particularly as some companies have already been exploiting loopholes to avoid paying fines. Clearview AI, for example, managed to avoid paying $105 million in fines imposed by four different European regulatory authorities by arguing that it did not fall within European jurisdiction.

"Even if these early fines are manageable for tech giants, their real value lies in establishing the firm legal precedents that will govern how AI must operate in the future," Costa concludes.

Sorry Sony (and Bose, and AirPods) I know the best earbuds I've ever tested — and they're a Technics product called the EAH-AZ100.

I know, try to see past the immediately forgettable name, because once you get past that alphabetty spaghetti, there's a seriously good set of earbuds in a great little offer here.

Do you like my lead image? I just went out into the full glare of the sun on the hottest recorded UK day in June — for a full three minutes — to get it, to prove I'm using them right now. I also snapped the photo above because the most-asked question I get when I tell people I'm TechRadar's Audio Editor is 'What are the best earbuds with noise cancelling?'

Take note of the subtle shift in phrasing there; not the best noise cancelling earbuds — no, the best current earbuds with noise cancelling. They're quite different things actually, because one can be read as 'I just want the closest thing to actively-generated silence I can get, in a small box please', whereas this specific question above prioritises sound quality, but adds ANC because it is a desirable extra. And I love that.

Anyway, people want a definitive answer and leave the complicated reasoning to Scarrott. Obviously I'm flattered, because it means they trust my judgement (well done there. I do know my stuff). But I've already spilled the answer above: it's these Technics buds, and has been for quite some time.

They came out in January 2025, and they're built on the original May 2023-issue EAH-AZ80, which were also excellent. And both products are somehow still the only earbuds on the market able to offer multipoint to three devices simultaneously, rather than two. Think it's a small perk? Try it for two weeks, then give them back to me. You won't be able to…

Today's best Technics EAH-AZ100 deal

A new lowest-seen price! The excellent EAH-AZ80 that came before this model basically tore up the rule book on sound quality and features in wireless earbuds – and the AZ100 are even better. Released in January 2025, these little beauties are still the only earbuds to offer multipoint to three devices simultaneously, plus excellent sidetone tech for hearing your own voice in calls, as well as some of the most neutral and detailed audio in an even smaller, even more premium-feel design. Oh, and this deal is £17 cheaper than our price trackers have ever seen. Highly recommended. View Deal

Look, the Technics EAH-AZ100 are still sitting pretty at the top of my guide to the best earbuds for a reason. They're incredibly secure and comfortable to wear; Technics pioneered a 'concha fit' design (which initially looks a little deep for a top-plate, but works beautifully), and it's a trick several rivals soon adopted in a post-AirPods-stem market, whether they'd choose to admit it or not.

They also offer LDAC support, which is one of my favourite hi-res wireless codecs and a simple route to better-quality audio streaming for Samsung and Sony smartphone owners.

And did I mention the call handling? It's excellent. Technics deploys both its known Sidetone tech (to slightly amplify your own voice, so it's not muffled by the buds in your ears as you talk) plus its newer proprietary JustMyVoice technology here, which captures your speech while simultaneously suppressing background noise.

Noise cancelling is also very good, but best of all, though, is the sound. As we enthused in our Technics EAH-AZ100 review, the soundstage is neutral and natural, yet simultaneously expansive, engagingly dynamic, and energetic.

I've used the EAH-AZ100 earbuds practically every day since they launched. Before that, I'd used their older siblings every day, and let me tell you: they're the best. I say this as someone with much of the consumer earbuds oeuvre at their disposal (I'm not bragging, it's work — my job is to review earbuds and headphones), so I do know the best from the also-rans.

Yes, I typically prefer over-ears for sound quality, but when running around, earbuds are more portable — especially in a UK heatwave where those ear cups can get a little hot. And in an in-ear design, I love the sonic performance of these buds, especially when the Prime Day deal is this good.

Did you struggle to sleep in the heat last night? What you need is a super-quiet fan, and you're in the right place to find one in the Amazon Prime Day sales. We test dozens of fans here at TechRadar, and I've put together this collection based on brands and models we know are dependable and effective.

• Check out all Amazon's Prime Day fan deals

When choosing a quiet fan for your bedroom, take a minute to think about the space. Will you be keeping the fan on your bedside table? If so, a fan with a rechargeable battery might be the best option, letting you run it all night while leaving plug sockets free for phone chargers. If you want to blow a blanket of air over your bed, consider an adjustable-height fan that you can direct at your duvet.

Some of the best fans have been selling out extremely quickly in the Prime Day sale, for obvious reasons, but all these deals are still in stock at the time of writing so grab one before they blow away on their own.

Amazon Prime Day quiet fan deals

Levoit makes some of the best value fans we've tested here at TechRadar, and this is an exceptional deal for one you can control with either a remote or a smartphone app. It's hit a record-low price for Prime Day 2026.View Deal

Another super quiet fan from Levoit, this model is specially designed for night time, with adjustable height to direct airflow at your bed. At under £80 it's one of the cheapest fans from a reputable brand this Prime Day.View Deal

Dreo's air fans and air circulators have been selling out fast during the current heatwave, but you can still grab a great deal on this oscillating standing fan, which can drop as low as 20dB at night and includes a useful timer.View Deal

I'm a big fan of SwitchBot's smart home tech and this near-silent desk fan will play nicely with all your other smart devices. It's rechargeable so you can keep it on your bedside table even if there's no plug socket available.View Deal

I'm relying on a Dimplex fan to keep me cool at night, and this versatile desk/standing fan should do the job for you as well. At under £100 it's a great Prime Day deal, and will serve you well for many heatwaves to come.View Deal

Be prepared

The current heatwave might have broken by the time your new fan arrives, but it's still a good idea to grab one during the Prime Day sales. As we've seen, the weather forecast can change within the space of a week, so it's never a bad idea to have one handy and ready to go next time the mercury rises.

Buying a fan now also means you won't be in such a rush. If you're in a hurry, it can be tempting to grab anything that has a good review, but not all fans are suitable for all rooms, so it pays to take some time now and make sure you're making the right choice.

The latest fans can move a large volume of air much more easily than older models, and are more energy efficient as well, which will keep you cooler and reduce your energy bills in the long term. That's not necessarily something you have time to think about if you're rushing to pick up a fan — any fan — in a sweat-soaked panic.

More Prime Day deals in the UK

• Amazon Prime: sign up for a 30-day free trial
• Amazon Devices: Fire TV, Ring & Blink from £24.99
• Amazon Haul: up to 30% off
• Apple: AirPods Pro 3 for a record-low price
• Appliances: up to 45% off Ninja, Tefal & Sage
• Beauty: up to 60% off Philips & Oral-B
• Essentials: household goods from under £10
• Fashion: up to 50% off
• Father's Day: up to 50% off gifts & drinks
• Headphones: up to 50% off
• Laptops: from £149.99
• Tablets: Samsung & Lenovo from £125
• Toys: up to 25% off Lego and Tonies
• TVs: from £129.99
• Vacuums: up to 40% off Eufy & Roborock
• Wearables: Garmin & Huawei from £36.99

• Sony is going all out for GTA 6 marketing
• The PS5 homepage, PS Store, and PS App have been updated with a GTA 6 theme
• Pre-orders have officially begun

Sony has gone full Grand Theft Auto 6 marketing mode as pre-orders for the most anticipated game of all time officially begin.

The wait is finally over, GTA 6 pre-orders are now live, and in anticipation of the game's release later this year, Sony is showing that it definitely has a favorite by updating the PlayStation 5 homepage, PS Store, and PS App with a new GTA 6 theme.

Now, when players boot up their PS5, they're greeted by a full-screen animation of the game's logo, before it fades into an ad for the game on the console's welcome hub.

When navigating to the PS Store, the background now features co-protagonists Jason and Lucia, and the "Must See" UI has been updated with purple boxes that provide details on the Ultimate Edition, trailers, the Vintage Vice City and GTA+ pre-order bonuses, and a way to pre-order.

GTA 6 is now the first thing you see when you boot up your PS5, they made an entirely new UI for this, insane. pic.twitter.com/xmz8h6RLzIJune 24, 2026

As spotted by Shinobi602, Sony has also updated the PS App logo with GTA 6 branding. Instead of the blue icon, it's been replaced by the game's sunset theme and palm trees.

It's clear that Sony is going all out to maximize the GTA 6 marketing, and it's not even a first-party exclusive.

It also shared in a post yesterday that "thanks to a close partnership" with the studio, "GTA 6 will play best on PS5" and take advantage of PS5’s features "to deliver a deeply engaging single-player experience."

@techradar

♬ original sound - TechRadar

GTA 6 officially launches on November 19 for PS5 and Xbox Series X and Series S, and will cost $79.99 / AU$129.95 / £69.99 for the Standard Edition and $99.99 / AU$159.95 / £89.99 for the Ultimate Edition. Pre-loads begin on November 12.

It's also confirmed that physical copies won't have a disc and only include a digital download code in the box.

As both a hardcore gamer and an audio geek, I used to spend a lot of time agonizing over whether to invest more money on a gaming headset or whether I could spend more on a great pair of headphones to cover both my hobbies. If you find yourself in the same boat, it's your lucky day: I'm here to help you make that decision and, with some of the great deals available this Prime Day, I can help save you some cash to boot.

• View the full Amazon Prime Day sale

I've been reviewing audio gadgets for many years now and have reviewed a bunch of gaming headsets in my time at TechRadar. What I've found is that headphones absolutely can do double duty as an alternative to a dedicated gaming headset, but you really need to consider what kind of features are the biggest priority for you personally.

Gaming headsets vs headphones: which should you buy?

When it comes to gaming headsets, there are a few kinds of features you can expect. Low-latency connectivity will often set these apart from wireless headphones, nixing any lag and ensuring you can respond to gunshots and monster cries quickly.

I've always found specific gaming sonic profiles super useful as well — headsets that can boost footsteps are fantastic for FPSes, for example, making it harder for people to sneak up on you. Pick up the Turtle Beach Stealth Pro for $167.94 at Amazon (was $329.99) and you can experience both of these features in spades.

Gaming headsets have historically been way ahead of the curve in terms of battery life. That's partly because not all of them offer ANC and some wireless headphone brands have really caught up in this area. For example, you can get the Sennheiser Momentum 4 for $179.55 at Amazon (was $299.99) and they offer up to 60 hours with ANC on, which is seriously competitive.

But I wouldn't say headsets get the upper hand on every front, with some areas being more of dead heat. I've not always found gaming headset's boom mics to be higher quality than the built-in call mics on higher-end headphones. But some offer fold-to-mute functionality that makes it easier to mute yourself when you want some privacy, for example the Corsair HS55 Surround v2, which you can pick up for $39.99 from Amazon (was $59.99).

Meanwhile, while many headsets these days offer spatial audio, so do a good proportion of high-end headphones — honestly, both camps contain great examples with deeply immersive audio and yet there are also plenty of headsets and headphones that promise spatial effects that sound pretty mono-directional. The absolute undisputed champ here is also on offer right now: you can buy the Apple AirPods Max 2 for $399 at Amazon (was $549).

For me, traditional headphones get the edge over a gaming headset in a couple of key areas. Headphones tend to offer superior music playback, as they've been engineered with that in mind — I know, I know: 'thanks Captain Obvious' — so they tend to handle soundtracks and your fave tunes better.

On top of this, they can also come crammed with innovative features. For example, the Sony WH-1000XM6 offer nice touches like speak-to-chat for automatic transparency mode during conversations and head gestures for accepting and rejecting calls. If you're keen to try out some of these cutting-edge advances, you can currently grab the Sony WH-1000XM6 for $378 at Amazon (was $459.99).

Ultimately, whether you need a dedicated headset or you can get away with using the same pair of headphones for listening to tunes and gaming will depend on the features you most rely on. Fortunately, there are so many great Prime Day deals available on each right now that no matter which choice you make, you can be sure you'll get it for a bargain price.

Headsets for gaming

HyperX Cloud III S Wireless

Corsair HS55 Surround v2

SteelSeries Arctis Nova Pro

Pros

• Excellent sound quality
• Very detailed audio
• Long battery life
• Extremely versatile with multiple connectivity

Cons

• Eye-watering price tag
• ANC isn’t the best
• Non-intuitive physical controls

Razer BlackShark V2 Pro — PlayStation Version

Pros

• Battery life for days, literally
• Incredibly clear mic audio
• Beautiful stitching and finish
• Great sound reproduction
• Multi-device compatibility
• Comfortable and adjustable

Cons

• Physical chat mix control only on Xbox version
• No wired operation on consoles
• Synapse software required to get the best out of the mic

Beyerdynamic Tygr 300 R

Pros

• Best-in-class audio quality
• Comfortable as heck
• Robust cable
• Open back design great for single player

Cons

• Expensive
• No replaceable cable
• No built-in mic

Turtle Beach Stealth Pro

Pros

• Incredible audio quality
• Flawless active noise canceling
• Excellent build quality and comfort
• Versatile connectivity options

Cons

• Average sounding microphone
• Expensive

Headphones for gaming

Sony WH-1000XM6

Pros

• Class-leading noise cancellation
• Excellent audio performance
• Super lightweight and comfortable
• Highly intuitive touch controls
• They're foldable again!

Cons

• Price increase over previous model
• Battery life is nothing special
• Still not waterproof
• Some may find them to be a tad bulky

Apple AirPods Max 2

Pros

• Even better active noise cancellation
• Live Translation that's easier to use than on Apple's earbuds
• Adaptive Audio means meatier, punchier sound than the originals
• Even head-tracked Spatial Audio feels more accurate and crisp

Cons

• Battery life hasn't been improved
• That flimsy 'headphone bra' case remains
• Still very iOS-only (Android owners need not apply)
• No wireless hi-res codec support still

Sennheiser HD 599 SE

Bose QuietComfort Ultra Headphones (2nd Gen)

Pros

• Predictably brilliant noise cancellation
• As comfortable as these things ever get
• Balanced, energetic sound

Cons

• Not quite the perceived value of some rivals
• Humdrum control app

Nothing Headphone (a)

Pros

• Great sound that's a big upgrade over Headphone (1)
• Fantastic on-ear control options and app
• Gigantic battery life

Cons

• Still heavy, with a strong clamping force
• Some rivals offer better sonic detail
• No auto-pause feature or case

Sennheiser Momentum 4 Wireless

Pros

• Neutral, crisp, detailed sound
• Excellent ANC and transparency
• Incredible battery life even with ANC deployed

Cons

• A little plain aesthetically
• Design doesn't fold up into the headband

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Operational performance is becoming just as important as investment performance in private credit.

As fundraising slows and investor expectations increase, firms are facing growing pressure to modernize the IT infrastructure supporting their portfolios.

In fact, transparency and faster reporting are becoming top priorities.

Without such capabilities, funds can’t clearly see across their own portfolio, amplifying stress when markets are less forgiving.

Especially as private credit scales and operational diligence become more central to allocation decisions, such back-office issues become something more structural.

Fortunately, managers that properly invest in their operational foundations now, will be better equipped to manage the increasing demands facing the private credit industry moving forward.

Analyzing Operational Pressures

Private credit is operationally intensive. And many firms never built systems to match the increasing complexity of their portfolios as they grew and evolved. Instead, operations are often spread across legacy servicing platforms, spreadsheets, email-driven workflows, and disconnected internal tools, leaving firms without a single real-time view of portfolio data.

Most loan servicing operates on cycles such as monthly reconciliations, quarterly reporting, and batch-based payment processing. This model reflects the constraints of legacy systems and manual workflows. Data must be collected, validated, and processed in stages. Consequently, funds often view their portfolios through periodic snapshots rather than in real-time.

Many funds also maintain parallel spreadsheets to verify their servicer's calculations. Known as shadow booking, this redundancy has no other purpose than to increase control. Ultimately though, it’s a sign of mistrust in the data provided, and the underlying calculations are often difficult to inspect. When discrepancies arise, they are discovered after the fact and require manual investigation, often across multiple systems.

These realities of the private credit industry are now colliding with a more competitive fundraising environment. Even if their underlying deals aren't catastrophic, private credit funds begin to look fragile if they cannot perform operationally well under increasing pressure.

Not surprisingly, many private credit firms are looking to AI to address these issues. But automation software alone cannot repair broken operational foundations. The critical question becomes whether their infrastructure is actually prepared to support the AI model they choose to use.

AI Alone Is Not the Answer

AI agents can execute operational work reliably while platforms can provide real-time visibility and full auditability. The pieces are in place. But there’s a pattern in how AI projects fail in the finance industry that's worth naming and it's almost never the model that's the problem.

What’s often missing is the infrastructure surrounding the model - the systems, workflows, data access, permissions, and controls that allow AI to operate reliably inside real financial processes. Otherwise known as the harness. Generic AI tools don’t know what a rate notice is.

They don't know that a prepayment request triggers a multi-step workflow across every syndicated entity on a facility. They don't know the difference between a funded tranche and a committed-but-undisbursed revolver, or why that distinction matters for how a payoff figure should be calculated.

This lack of operational context is also one of the biggest reasons AI hallucinations occur in finance. The majority of hallucinations aren't random malfunctions, they're a context problem. The AI model wants to give an appropriate answer. When it doesn't have access to the specific data it needs, it reasons from what it does know and produces something plausible.

Private credit portfolio data isn't embedded in any public language model. If the harness doesn't provide it, through tools, memory or real-time data access, the model will fill the gap with something that sounds right. Which, in a financial operations context, is a real problem.

The fix isn’t a better model. It’s a harness that gives the agent access to the right data, at the right moment, with the right tools and controls to retrieve it.

The firms that focus on building operational systems that provide context, transparency, audibility and human oversight will receive the greatest value from its AI investments. In private credit, the long-term advantage may not come from adopting AI faster than competitors, but from building the infrastructure, or the harness, capable of supporting it responsibly and at scale.

Establishing New Competitive Differentiators

As these operational systems mature and advance, they will also reshape what excellence actually looks like inside private credit firms. Responsiveness won't be a differentiator. It will be assumed. Real-time and instant delivery will be the new baseline.

This is because most routine interactions will no longer require human involvement. With real-time systems, shared data layers, and automated workflows, information will be directly accessible and continuously updated. What previously required a request and response cycle will be resolved at the source.

As a result, the role of the servicer shifts. They are no longer measured by how quickly they process or reply, but by how well they handle what cannot be automated - exceptions, edge cases, and judgment calls.

This is why the next generation of private credit leaders may look fundamentally different from the firms that defined the industry’s earlier growth period. Capital access and underwriting expertise will remain essential, but operational execution is becoming increasingly strategic.

Most funds are using general-purpose AI for ad-hoc analysis or are in a holding pattern. A small number are starting to build their own and discovering how much harder it is than first expected. The funds that move first on specialized operational infrastructure will have an advantage that compounds. Not because they picked the right model (the model will keep getting better and cheaper regardless), but because they built or adopted the right harness, trained it on the right context, and gave it the controls that make it trustworthy at scale.

In many ways, private credit firms are evolving into operational organizations as much as financial organizations. The ability to manage workflows, data, oversight, and execution will become a defining part of a firm’s competitive performance.

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Data governance is unglamorous work. It is also the reason most AI strategies stall before they scale.

Spending on models, platforms and use cases keeps growing. But the disciplines that make those investments effective – data quality, ownership and governance – often receive far less attention.

Part of the challenge is that data governance is neither “fun” nor “sexy.” It lacks the excitement of new technologies and the appeal of quick wins, so it is consistently deprioritized.

Yet as organizations scale their AI ambitions, governance is increasingly the factor that determines whether those efforts succeed or stall.

The imbalance in attention is now starting to show. While AI adoption continues to grow, many organizations still struggle to move beyond pilot stages into enterprise-scale deployment. The gap between ambition and execution is widening, and weak data governance is often at the center of it.

The issue is not awareness. Most business leaders recognize that governance matters. The challenge is that governance demands structural decisions, cultural alignment and sustained discipline – the hard parts of the job. And, unlike a new platform or tool, its value often only becomes fully apparent when it is missing.

When governance is absent, problems don’t stay small

Weak governance rarely fails loudly at first. The problems accumulate.

Early AI initiatives often prioritize delivery, with dashboards, models and applications taking precedence over governance. Silos form, data definitions diverge and access controls become inconsistent. A common pattern: two teams – one in marketing, one in data science – train separate models against different definitions of the same metric.

Both definitions look correct in isolation. In production, the predictions conflict, neither team can explain why, and the investigation takes weeks longer than building either model did. Quality issues are patched rather than fixed, and new projects begin to rely on shaky assumptions.

As complexity grows over time, confidence in the data declines.

Data dictionaries and permission frameworks are not administrative overhead – they are what makes scalable AI possible. Building them early demands investment before visible returns but postponing that effort is far costlier.

Left unchecked, governance gaps eventually land hard, resulting in delayed projects, compliance failures and decisions made on unreliable data. At that point, organizations are forced into reactive fixes – or even total rebuilds – that are far more expensive and disruptive than addressing governance from the start.

Governance is not just compliance – it enables innovation

Regulators are placing increasing importance on accountability in how data is used. The UK’s Information Commissioner’s Office (ICO) has made it clear that organizations must be able to demonstrate control over data use, particularly as AI systems become more prevalent. Scotland’s new National AI Strategy also highlights that organizations must follow best practice in responsible AI governance aligned with OECD principles.

This has reinforced the perception that governance is primarily a compliance exercise – something important but not necessarily prioritized at the prototype stage. Effective governance is far more than that: it shapes how data flows through an organization, how decisions are made and how confidently teams can act. It defines accountability and sets the standards needed to maintain consistency at scale.

In that sense, governance is a design choice, and businesses need to make the right one to effectively scale their innovation ambitions.

Define ownership before you decide the model

Governance is not one-size-fits-all - nor it is purely a technical problem to be addressed through tools or platforms alone. In fact, the harder initial challenge is often a people and accountability one. Before designing a governance model, organizations need to define the who as much as the how. Who owns the data? Who is responsible for its quality and who decides how it should be used?

In many organizations, these responsibilities are unclear. Management is shared, and ownership is (often wrongly) assumed rather than defined. But it is only once those questions have been answered – in practice as well as on paper – that businesses can turn their attention to developing a governance model that fits their structure.

Some take a centralized approach to this, with control sitting in a single function. This can provide consistency and clarity, but the model may struggle to scale across complex organizations with diverse needs.

Others adopt a federated model, combining central standards with local ownership. This can be more flexible and scalable, but only if the business is committed to those shared standards and has defined clear roles and accountability. Without them, federated models risk furthering data fragmentation.

The key is alignment. Governance models should match how teams actually use data and AI, not how they’re assumed to operate.

A practical test: ask three different teams how they define a key business metric – revenue, active users, or customer churn. If the answers differ, the governance problem already exists. The operating model question is not how to prevent that divergence in future; it is who has the authority to resolve it now.

Governance doesn’t show up in a demo

Governance is rarely the most visible part of an AI strategy. It’s detailed, structural work that often goes overlooked, but that is precisely why it matters.

For business leaders, the challenge is to move beyond acknowledging its importance and begin making early, deliberate decisions about how it is implemented. That means defining data ownership, aligning operating models and investing in the capabilities that support long-term success.

Technology choices are reversible. Data ownership decisions compound. The governance model you design – or neglect – in the next twelve months will shape what your AI strategy can actually deliver in three years.

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• The second season of Netflix crime drama Dept Q begins production in Edinburgh, Scotland
• Core cast set to return alongside nine new faces
• No word yet on release date or the number of episodes

Netflix has confirmed that the second season of the hit crime drama Dept Q. is now in production, filming in Edinburgh, Scotland.

Our core cast is set to return, including:

• Matthew Goode as DCI Carl Morck
• Alexej Manvelov as Akram Salim
• Jamie Sives as DS James Hardy
• Leah Byrne as DC Rose Dickson
• Mark Bonnar as Stephen Burns,
• Kate Dickie as Moira Jacobson
• Aaron McVeigh as Jasper
• Sanjeev Kohli as Martin Flemming

Nine new cast members will also be seen in new episodes. While we don't know exactly what their roles will be, we do have names:

• Aisling Franciosi as Kimmie
• Greg Wise as Derek Powell
• Nicholas Rowe as Thomas Fulton
• Tony Curran as Winnie Calderwood
• Hamish Clark as Christopher Herron
• Alex Ferns as Phil Allenbeck
• Ross Anderson as Ricky Daddario
• Rebecca Root as June Lovesay
• Isla Johnston as Agnes

Currently, there's no word on exactly when Dept Q. season 2 will be released, nor how many episodes will make up the series.

However, we do have a brief idea of what the plot will involve thanks to the synopsis below.

Dept Q. season 2 set to explore a brand-new case

As per Netflix, Dept Q. season 2 follows "DCI Carl Morck heading up the maverick Dept. Q from the basement of an Edinburgh police station, charged with cases previously deemed unsolvable.

"This darkly humorous, propulsive show delivers all the pleasures of a procedural but takes us into the complex mysteries not just of the cases but of the detectives themselves."

Unsurprisingly, this is all very vague at this point in development. However, Rob Bullock, Executive Producer, Left Bank Pictures, added in a statement, “This season, Carl and his band of misfits tackle a terrible crime hidden in the highest echelons of Scottish society. It is a story for our times: rich and powerful people who believe they are above the law."

Executive Manda Levin agreed, "The story of season 2 is as darkly delicious as you’d expect, and Carl and his glorious gang will have their work cut out pinning down the perpetrators as we launch back in for more!”

What we know for sure is that we will continue to see an adaptation of Jussi Adler-Olsen’s original novels — but how faithful the show will be remains to be seen.

Two years ago, Netflix dramatically let me down. As a massive anime fan, I tuned into the first season of their live-action Avatar: The Last Airbender remake and was horrifically disappointed within minutes. In fact, the most positive critique you could give it is that it was better than the live-action movies, which are widely considered to be garbage.

Why? The action was all there, but the heart of Aang's story wasn't. Spectacular VFX tried to cover up the hollow, mundane narrative underneath. In fact, to quote a fantastic jaw-dropping writer called Jasmine Valentine: "There’s little room to learn, with life-changing realizations made in a ridiculously short amount of time. If a tale can’t be paid its due diligence in a certain remit, should we even bother at all?"

In 2026, my excitement for Avatar: The Last Airbender season 2 is non-existent. I've approached its seven-episode run with complete trepidation, honestly wondering if there is anything better that I could be covering this week. However — while a long way from being a masterpiece — the hit Netflix show has clearly been listening.

Now that all of the exhausting worldbuilding is out of the way (for the most part), fans can finally focus on the character relationships that they want to invest in. There's a lot of tenderness and vulnerability on display, which is the most fulfilling part of our cast having grown up so much between seasons.

But there's still something obvious that's really bothering me... and it comes back to Netflix's "cookie-cutter" mold that none of its programs can escape.

Avatar: The Last Airbender season 2 has finally learned its lesson about the importance of heart

Read it and weep (for joy), kids — Avatar: The Last Airbender season 2 actually has heart. If we're being honest, nobody had to put any effort into achieving this, with the mere fact that the lore of the Four Nations is fully established meaning there's now room for bigger, better things.

A mature Aang (Gordon Cormier) now straddles his inner struggles of legacy and constant imposter syndrome even more effectively, with the likes of Katara (Kiawentiio), Sokka (Ian Ousley), and Suki (Maria Zhang) now all settled into their selves, wants and needs.

If anything, Zuko (Dallas Liu) is going through it the most. After deserting his family and retreating into hiding at the end of season 1, we've got a lot more sympathy with him this time around as he grapples with his supposed destiny of capturing Aang for the Fire Nation's glory. Unlike Lord Ozai (Daniel Dae Kim), he's no longer a villain, but a victim.

The standout character of season 2 is easily Toph (Miya Cech), who has finally been introduced after not appearing in season 2. Coming from a complicated family background that routinely dismisses her Earthbending, she comes into her own sassy self after teaming up with Aang to teach him the next element.

Collectively, the team is now firing on all cylinders, and it's nothing short of a joy to watch. Now we understand who they are and what the bigger picture looks like; intimacy, fun, and genuinely satisfying friendships are now flourishing. The jokes land, the serious moments stab you in the heart, and whimsy is flying around like Appa the sky bison.

Netflix makes season 2 look exactly like The Witcher — just with different lore

(Image credit: Netflix)

Everything else in Avatar: The Last Airbender season 2 feels like more of the same — and that's a huge problem when it comes to the visuals. Broadly speaking, the Four Nations are jaw-droppingly gorgeous, and the detail that the creative team has packed into the landscapes is nothing short of impressive.

The immediate VFX, such as the bending that our characters use, leave a lot to be desired. It's obviously not a usual thing for people to have fire and water shooting out of their hands, so we're suspending a great deal of belief anyway... but being in the moment doesn't help when seeing it happen looks so fake.

This lumps season 2 into the same visually poor category as The Witcher, which is another comparison I made during season 1's debut. Cover the faces of the actors, stick them in the woods for a combat scene, and you'd be hard-pressed to tell the shows apart. Netflix is determined to make all of its genre programs look exactly like one another, and I'm baffled as to why.

Then there's the ultimate ending, which we already know without including spoilers. Much like other long-running anime series like One Piece (with its Netflix adaptation also guilty of this), we've known about the final endgame from its first five minutes. Here, it's for Aang to learn his bending skills, become all-powerful, and defeat Lord Ozai and the Fire Nation.

With a third series already confirmed, this is being drawn out for as long as humanly possible. It was obvious that none of the above was going to be achieved by the time season 2 wrapped up, so we've made little substantial progress from when Aang's goal was first introduced.

For me, the constant theme of "Oh no! Danger is on the horizon, and the Fire Nation must be stopped" is going to wear thin quickly. I'd really like to see season 3 mix things up, but I'm guessing that it won't.

Did I enjoy seeing Aang and the gang in 2026 more than in 2024? Absolutely. Has it renewed my interest in seeing them again at the end of 2027 (season 3's assumed release window)? Far from it.

Spoilers for Avatar: The Last Airbender season 2 ahead.

Even before Avatar: The Last Airbender season 2 dropped on Netflix, we knew exactly where it was heading: the Fire Nation taking over all of the Four Nations.

In the latest batch of seven episodes, the target is the hidden city of Ba Sing Se — and as of season 2 episode 6, it's been captured.

With Avatar Aang (Gordon Cormier) the only person who can save the day, the pressure is on to stop Fire Lord Ozai (Daniel Dae Kim) from doing any more damage.

Unluckily, Princess Azula (Elizabeth Yu) is taking her dad's wishes into her own hands. But can our favorite gang cope with her fiendish plans?

Here's everything you need to know about the Avatar: The Last Airbender season 2 ending... and what it might mean for the already confirmed season 3.

Appa, Sokka, Zuko and Katara are all captured by the Dai Li — which is now controlled by Azula

(Image credit: Netflix)

We kick off Avatar: The Last Airbender season 2 episode 8 with a flashback of baby Aang meeting Appa the sky bison for the first time. Aang feeds Appa an apple (trying to say that three times fast), and they embrace.

Cut to the present day, where Appa has been kidnapped by the Dai Li — Ba Sing Se's secret police force — which is now being controlled by Princess Azula. Trust me, you will cry seeing him in chains.

In a meeting with the city's Grand Secretariat, Long Feng (Chin Han), Azula kills all of Ba Sing Se's highest-ranking men in the force when they question why the Fire Nation wants to control the city. Long Feng, however, begrudgingly but fearfully complies with Azula's plan: to raise Ba Sing Se's drawbridge and let the Fire Nation troops roll in, taking out anything they want in the process.

Remember, this is all coming from Lord Ozai's orders, despite Azula being a more than willing vehicle for them. But Appa isn't the only Aang ally the Dai Li has captured on her orders, with Sokka (Ian Ousley) and Katara (Kiawentiio) also in separate cells.

Sokka reunites with inventor Sai (Danny Pudi) in his cell, with the inventor already being captured before his arrival. Together, they try to figure out how to use the prison's underground structure to break free.

Katara has been put in a cell with Zuko (Dallas Liu), who was caught by the Dai Li after "doing a good act." This marks the biggest pinnacle in Zuko's personal struggle between good and evil so far, and Azula has no idea that he's jailed.

Meanwhile, Toph (Miya Cech) returns home to her mother, complaining that Aang and co. "don't understand her" after their huge falling out in episode 6. While initially seeming on board with how great Toph's earthbending powers are, her mother poisons Toph's tea in order to try and control her urge to leave home forever.

Aang and Iroh plan an escape mission

(Image credit: Netflix )

So where is Aang in this? Right behind his pals, having already figured out where Appa is underground just by sensing him. When the Azula-controlled Dai Li parade through the center of Ba Sing Se, he's hidden by allies made in season 2, episode 1.

When he attempts to approach the Dai Li's underground jail, he's spotted by Iroh (Paul Sun-Hyung Lee) and is immediately suspicious. Iroh reveals that he's also on a mission to break Zuko out of jail, thinking that the pair should team up for maximum effect.

Iroh tells Aang about a secret door that Avatar Kyoshi once installed to lead into the underground caves, but it needs all four elements bent at once to be able to open it. Aang is missing his firebending powers at this stage, so he needs Iroh just as much as Iroh needs Aang.

Together, the pair locate and open the door, and set off on their rescue mission.

Zuko tries to bond with Katara

(Image credit: Netflix)

While Sokka and Sai try to be proactive, Katara learns who Zuko really is. Immediately, she goes on the defensive, telling him how all of her family — and the entire Waterbending tribe — were wiped out thanks to the hostile Fire Nation invasion.

Zuko definitely feels empathy for Katara, but still has a chip on his shoulder. He tells her that the Fire Nation also stripped him of his family, with his mother dying at the hands of Lord Ozai.

The more the two talk, the more they realize that they have a lot in common. It's the closest we've even seen Zuko come to his "good" side, and it seems as though he's finally going to stay that way for good.

Looking at the burn mark around his left eye, Katara offers to try and heal Zuko using the waterbending potion in the locket around her neck. Just as she's about to apply it, Aang and Iroh storm in, having found and released Sokka and Sai first.

Aang goes to fight Zuko, but Iroh stops him, claiming that he's seen huge changes for the better in his nephew. Not quite believing that Zuko has defected from the Fire Nation, the gang sets off in search of the exit.

Aang's escape plan is thwarted

(Image credit: Netflix)

With the Dai Li everywhere, the gang splits up. Aang goes to find Appa after Long Feng brings him up to speed with Azula's plans, earthbending a hole through the ceiling so that Appa can fly to safety.

But as he tries to rejoin the others, he passes another prisoner who was originally being psychologically tortured by a Dai Li officer earlier on. Aang offers to bring her with them, but instead of accepting his offer, she shouts that "the Avatar is here," alerting the guards.

From there, it's fighting on all fronts. In pairs, the group makes light work of the Dai Li roaming the hallways, especially when Toph joins suits, revealing that she has invented "metalbending."

In fact, metalbending is how she ended up there in the first place. When she wakes up after her poisoning, Toph awakes in a metal box riding inside her mother's horse and carriage. Coming to the conclusion that Aang really does understand her, where her family doesn't, she bends the box and flies out of the carriage, making her way to safety.

An all-out battle with Azula changes Zuko's allegiance

(Image credit: Netflix)

With the fight raging on, Azula soon joins the mix, learning that her brother is among the escapees. Honing her focus on him, she tries to convince him, once again, to rejoin her side.

At first, Zuko remains hesitant, more confident in his newfound ability to do good things. But when Azula brings up the death of their mother, he changes his mind.

Where Zuko has always held a grudge against Azula for how she acted when their mother died, Azula reveals that she was only acting on her mother's orders. Their mom wanted the siblings to stay together through the trauma, breaking an emotional trigger point inside Zuko when he hears this.

By the time the rest of the gang reach a large clearing in the underground caves, Azula and Zuko emerge to fight them all as a team. This shocks Katara, who had genuinely believed that Zuko was coming around to being on their side.

After a lot of intense bending and fighting, it looks as though Azula has Aang right where she wants him — after all, the entire point of kidnapping his friends was to lure Aang to Ba Sing Se.

But in his hour of need, Aang taps into what can best be described as an "Avatar portal," seeing physical forms of all the Avatars that came before him in his mind's eye. More clearly, it's what causes Aang's eyes and head arrow to turn a shining blue, as he's essentially channelling their collective power through his body.

Aang is left unconscious

(Image credit: Netflix)

At this point, we see Aang's best bending to date, turning the tables on Azula and leaving her (and the Dai Li guards who join her) powerless.

But just as he's about to deliver the final blow, Aang loses his inner vision, effectively shutting his power off. He collapses to the floor, but Katara, Sokka and Toph are able to get him to safety thanks to Appa having waited outside.

With Ba Sing Se still under Azula's control, our final scene shows the gang flying away on Appa's back. Kata uses the potion she initially offered to Zuko on Aang, aiming to heal him and bring him back to full health.

However, nothing happens after she gives it to him, with the final shot showing Aang completely unconscious and unresponsive.

Season 3 predictions

(Image credit: Netflix)

Obviously, finding out if Aang has actually survived the battle is a top priority for season 3. But the mere fact that season 3 has already been greenlit basically confirms that we'll be seeing Aang again anyway.

In a nutshell, we can expect to see Aang learning to firebend, infiltrating the Fire Nation, and preparing for his climactic showdown with Fire Lord Ozai before Sozin's Comet arrives. Not too much, then.

We also know that Zuko will eventually team up with Aang and the gang to make this happen, so we can expect to see some more emotional upheaval from him.

We're hoping to see season 3 episodes next summer.

Getting AI-ready while building your data infrastructure is like learning to drive a manual transmission on the wrong side of the road.

It’s complicated and requires potentially dangerous multitasking.

Organizations with immature data-handling processes that are adopting AI are trying to solve multiple technology problems at once, and risk stalling out.

Unsurprisingly, 48% of enterprises cited data-related issues as their top challenge to AI adoption in NVIDIA's 2026 State of AI report.

Most enterprise AI programs don't fail because of the model or solution selected. They fail because underlying data is fragmented, inconsistent and poorly governed.

Get Your Data Foundation in Order

Enterprise data is messy in layers. It’s scattered across many systems, making it hard to pull together into a coherent picture. Even when you can consolidate it, you often will run into granularity or identifier mismatches. One application may store account numbers as plain digits, while another adds “ACCT” as a prefix. That small inconsistency creates an extra reconciliation step every time you join those data sets.

Data governance compounds the problem. Without a system intentionally designed to control who accesses data, where it moves and what protections are in place, gaps emerge fast. PII exposure is the most obvious risk: an email address that ends up in the wrong hands can trigger a serious breach. Raw, unstructured data also yields mediocre AI outputs and is more expensive to process.

Clean, structured data yields better results at lower cost. A third gap, explainability, is quickly becoming a legal requirement. Many countries and several U.S. states now require organizations to demonstrate how AI-driven decisions were reached. Cut corners on the data foundation and you may not be able to show that chain of reasoning.

At that point, you’re either in compliance violation territory or your model is producing outputs you can’t defend.

Three Steps to Get Your Data AI-Ready

Define governance before you deploy. Classify your data: what is it, where did it come from and who can touch it. Separate the roles of technical decision-making and compliance oversight. Keeping those responsibilities with different people prevents a compromising situation where the same person sets the rules and monitors compliance.

Run cross-functional AI governance as a standing function. Assign a representative from every department and meet monthly to discuss what teams are working on, what concerns have surfaced and what support they need from one another.

Approach larger AI-readiness initiatives like any other business project: assign a project manager, designate an executive owner, set a weekly cadence, build a task list and work through it.

Collect behavioral data even before you need it. The outcomes you get from AI vary enormously depending on how skilled the operator is, ranging from using it as an expensive search engine to developing autonomous workflows. Without visibility, you might be pouring money into AI licenses and getting Google-level output in return.

You don’t know who needs training, whether they have the right tool in front of them or what outcomes they’re achieving. The risk is that you make the wrong strategic call as a result—abandoning a rollout, for example, when the real fix was better training or a different tool.

Further considerations

Here’s another layer to consider. When an experienced worker completes a task, with AI assistance, they leave more skilled than when they started. The output and the learning happen together. That's what behavioral data should demonstrate over time – not just task completion, but upward skill trajectories.

When someone at the beginning of the learning curve accepts whatever AI produces without critically engaging with it, you get the output but not the growth. Behavioral data is how you catch that gap early, before it becomes a long-term cost you can't unwind.

Stay curious and look for the easy wins. Focus your data readiness efforts on the workflows where work actually happens, and prioritize tools that let you get at that data.

A recent example illustrates the payoff. A product manager ran an AI-powered analysis of quarterly bug patterns using data from the department’s most commonly used tools. The results were unexpected. One team carried a disproportionate share of incoming tickets, most of them requests for manual workarounds to a missing product feature.

While other teams split their time roughly 75% on new work and 25% on incoming bugs, that team was closer to 50-50. By not building a single feature, the organization was effectively operating 1.5 people below capacity.

The entire analysis took about 45 minutes. None of it would have been possible without data that was organized, tagged by team, connected to individual contributors, accessible via existing AI connectors and protected by role-based access controls.

The organizations that get the most from AI are the ones that empower their people to ask "I wonder if there's something here" — and have data to diagnose in an afternoon. That only happens when the foundation is already in place.

Make your data safe with the best backup 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

Recent court developments in Germany have put an important issue into the robotics spotlight.

A German court in Hamburg has issued a preliminary injunction against Elite Robots Germany in a copyright infringement case involving copying of Universal Robots software.

As a result, the company is not allowed to offer or distribute the products covered by the decision in Germany while the case continues.

At first, this may sound like technical legal news only relevant for the German market.

But it highlights broader questions that matter to every company investing in automation – especially when choosing a collaborative robot that will operate close to people and become part of daily production.

Here are five reasons why.

1. Copying creates real risk for customers

When protected robot software or design is copied without permission, the impact extends well beyond the supplier and exposes all parties in the value chain to significant legal risk.

It can affect end-customers directly as using an infringing product for commercial purposes, such as a robot with infringing software in a production line, can itself constitute a legal violation.

This not only creates a risk of court-ordered remedies, including preliminary or permanent injunctions requiring the immediate shutdown and removal of the affected robots, but also exposes customers to costly and disruptive litigation and potential business interruption.

Automation systems are long‑term investments meant to run for years. Legal uncertainty at supplier level can turn into a real business risk on the factory floor.

2. “Similar” does not mean safe

Collaborative industrial robots are often described as safe, but safety is not automatic. It depends on how a robot is designed, tested, and used in real applications.

A robot that looks or behaves like another system does not share its safety profile. Safety comes from reliable hardware, validated software, certified functions, clear limits, and proper documentation. These cannot be copied by appearance alone.

Superficial similarity creates a dangerous false sense of security, which may result in serious physical injury to operators and bystanders.

3. Lower price can mean higher cost later

The purchase price of a robot is easy to compare. The long‑term cost is not.

If your robot vendor ends up in a legal battle, besides the question of even being able to use it legally, you also face uncertainty about product availability, software updates and service support.

Unexpected downtime, lack of updates or compliance challenges can quickly outweigh any initial savings. This has never been more relevant as modern robots are software‑driven machines. Motion control, force limits, diagnostics, and safety logic all depend on software.

If customers do not know where the software comes from, who owns it, or how it is maintained, they introduce uncertainty into production. Original, well‑understood software is essential for reliable and predictable operation over time.

In automation, shortcuts often appear affordable at first but expensive later. And as with all things in life: if it seems too good to be true, it probably is.

4. Buying copycat tech shapes the future of automation

Every automation investment sends a signal about what the market rewards. Choosing original, lawfully developed technology encourages long‑term engineering, robust safety practices, and continued product improvement. Choosing copycat technology does the opposite: it normalizes shortcuts, weakens incentives to invest in research and compliance, and shifts competition away from quality and reliability.

Over time, widespread tolerance of intellectual property infringement affects the entire robotics ecosystem, from suppliers and integrators to suppliers and regulators. It increases uncertainty and ultimately makes it harder for manufacturers to rely on stable platforms that will be supported and improved for years to come.

Protecting original technology is not about limiting choice or slowing competition. It is about ensuring that competition is based on real innovation, verified safety, and accountability – and that customers can invest in automation with confidence, knowing the technology they rely on is built to last.

5. Trust in the original

In summary, choosing a robot is not only about specifications and price. It is about trust.

Buyers need confidence that a robot is legally sound, properly certified, and supported by people who truly understand the technology. Trust comes from transparency, responsibility, and deep technical knowledge – not from claims or visual similarity.

Automation is becoming increasingly central to modern manufacturing and as it does, questions of originality, safety, and integrity become part of responsible decision‑making.

So, no matter if you’re purchasing your first robots or expanding your fleet, before asking what a robot can do, it is worth asking a simple question:

Do you trust where it comes from?

I tried 70+ best AI tools.

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

Although the technology powering them has evolved in performance and efficiency, the core principle of data centers hasn’t changed much in the past two decades.

Every new generation of infrastructure has been designed to shorten the distance to users, reducing latency and increasing reliability. However AI is putting serious strain on that model, and unprecedented demand for data centers is making companies think outside the box.

Terrestrial projects now face challenges from all directions, including land availability, cooling, power and water consumption, and local opposition.

Step in orbital data centers. Some pioneers are now looking to rocket data centers up into space, and the model keeps shifting further from concept and closer to reality.

While enormous technical hurdles remain, advocates argue orbital data centers could eventually complement terrestrial campuses by shifting some of the most energy-intensive AI workloads away from land-based constraints.

Networking is what will define good orbital compute

Some of the benefits include virtually unlimited space to expand, uninterrupted access to green solar energy and cooler environments that don’t require so much cooling.

But while sending compute into space tackles some of the problems we face today, it reverses one of the biggest fixes we’ve spent years improving – latency.

In today’s instant economy, a data center has no use if it can’t exchange information quickly and reliably. Terrestrial networks lean heavily on fiber networks and physical connections, but orbital data centers would need to improve wireless transmission across hundreds of miles.

As work on this progresses, Internet exchange operator DE-CIX CEO Ivo Ivanov says orbital compute should be viewed as another layer in our increasingly distributed digital ecosystem – not an outright replacement for terrestrial compute.

To better understand whether orbital data centers are just another ambitious experiment or whether they could be the next evolution of digital infrastructure, I spoke with Ivanov about the industry’s biggest challenges.

• You noted that SpaceX's IPO has brought the idea of AI data centers in space into the mainstream. Setting the hype aside, how close is this to real, and what's actually driving the biggest companies in the world to look at space?

The idea of placing data centers in orbit is the kind of thing that immediately captures people's imagination. It belongs in the same category of technological ambition as reusable rockets, commercial spaceflight, or landing on the Moon.

For decades it felt like something that belonged in science fiction. Today, for the first time, it's being discussed as a serious infrastructure proposition. But I don’t think the real story here is about space – it’s about AI, and how it’s altering our global trajectory.

Over the last few years, we've seen an extraordinary increase in demand for compute capacity. AI training clusters are growing larger, power requirements are rising, and in many regions the availability of energy, land, and cooling has become a genuine constraint.

These constraints are what drive innovation, and that’s what we’re seeing play out here.

In theory, space offers access to continuous solar energy and room to scale without the physical limitations we experience here on Earth. Having said that, we're still at a very early stage.

I don't think we're talking about replacing terrestrial infrastructure anytime soon. What we're seeing today is the beginning of a serious exploration into how orbital resources could complement the digital infrastructure ecosystem that already exists.

There is still work to be done, particularly around networking – putting an AI data center into orbit would be a milestone achievement, but it won’t count for much if we have to truck hard drives into space to do any training. For now, all anybody can say with confidence is that it's becoming part of a broader conversation about how society will support the next generation of AI workloads.

• What problems could orbital data centers potentially solve that terrestrial infrastructure struggles with today?

I think the broader answer is that orbital infrastructure has the potential to ease some of the physical constraints that have shaped and limited digital infrastructure for decades. We can’t simply keep building more data centers – they need access to land, power, cooling, transport links, and of course, connectivity.

As AI continues to grow, some of those resources will become harder to secure, especially at the pace the industry wants to move.

That's why the industry is starting to look at non-terrestrial alternatives. Suddenly, you're talking about access to potentially unlimited solar energy, plenty of space, and the opportunity to scale at a pace that matches our ambitions for AI.

But putting data centers into orbit, as impressive as it would be, is only the first step. Google’s Project Suncatcher is already exploring how power might be harvested from the sun, while the European Space Agency’s OFELIAS project is exploring how optical feeder links between Earth and orbit can be optimized to reduce latency and disruption. There are lots of moving parts.

• From a networking perspective, what challenges will emerge once data centers move into orbit?

The moment you put a data center into orbit, networking becomes the make-or-break factor. A data center on Earth can usually rely on a dense ecosystem of fiber routes, Internet Exchanges, cloud on-ramps, and interconnection facilities. In orbit, that ecosystem doesn't exist yet.

Every workload, every application, and every AI model depends on data moving between different locations, and suddenly those journeys become much more complex.

A lot of the discussion I’m hearing focuses on bandwidth or speed, but I think predictability is the more interesting challenge. AI systems need data to arrive quickly, but they also need it to arrive consistently.

Optical and laser-based communications have enormous potential, but they also introduce new variables like cloud cover, atmospheric turbulence, satellite handovers, and changing orbital positions that can all affect how data moves between Earth and space.

That's why I believe the real challenge isn't simply connecting an orbital data center to the ground, but creating an interconnection layer that makes orbital, terrestrial, cloud, and edge infrastructure behave as though they're part of the same ecosystem.

That's a much bigger networking challenge than people realize.

• Elon Musk said orbital infrastructure is "only a few milliseconds away." How much could those milliseconds matter, and is latency the biggest challenge?

Those milliseconds absolutely matter. AI systems are fundamentally data-driven, and every additional moment spent moving information between users, applications, models, and infrastructure affects performance and productivity.

That's one of the reasons the industry is investing so heavily in edge computing – the closer you can bring compute resources to the data, applications, and users they serve, the better the experience tends to be.

Certainly, low-Earth orbit is only milliseconds away, but for latency-sensitive use cases, the 20-40 ms it takes to reach the stratosphere will provide a significant challenge for some AI inference use cases. So not all applications can possibly be served from hundreds of kilometers above the ground.

Having said that, performance isn't just a question of latency. A network that consistently delivers twenty-five milliseconds of latency is often more valuable for many enterprise use-cases than one that fluctuates between twenty and a hundred.

Physics determines how quickly data can travel, but factors such as atmospheric conditions, satellite handovers, routing decisions, and network architecture all influence how predictable that experience is.

• If a data center is in orbit and the AI workloads it serves are on Earth, what actually has to happen for those two worlds to behave as one network?

The way I like to think about it is that users shouldn't have to think about where a workload is running. Whether an application is being served from a terrestrial data center, an edge location, a cloud region, or one day an orbital platform, the experience should feel seamless.

Achieving that is much harder than it sounds, because data has to move continuously between different environments, and those environments need to behave as though they're part of the same network, even when they're separated by hundreds or thousands of miles and, increasingly, by the boundary between Earth and space.

That's one of the reasons projects like the ESA's OFELIAS initiative, which I mentioned earlier, are so important. As part of that initiative, DE-CIX is working alongside partners including the German Aerospace Center to explore how optical feeder links between satellites and the ground can become more stable, efficient, and predictable.

Rather than simply building more connections, we need to create an infrastructure foundation that allows terrestrial, satellite, and orbital resources to work together as a single ecosystem.

We've spent decades building that kind of seamless interconnection on Earth, and now we need to take what we’ve learned and combine it with new technologies to bring non-terrestrial infrastructure into the picture.

• Where does this leave terrestrial data centers and interconnection? Will orbital compute compete with what exists on the ground, or depend on it?

I don't see this as a competition at all. Digital infrastructure has a long history of adding new layers rather than replacing existing ones. Cloud computing didn't eliminate enterprise data centers, edge computing hasn't eliminated centralized clouds, and satellite connectivity hasn't replaced terrestrial networks.

Instead, each technology tends to find the role it's best suited to, and the overall ecosystem becomes more capable as a result.

I think orbital compute will follow a similar path. Some AI workloads may benefit from being processed closer to abundant energy sources in orbit, while others will remain in terrestrial edge data centers because they require ultra-low latency inference, regulatory compliance, or proximity to users and applications.

It’s not about choosing one over the other, but creating an architecture where workloads can be placed wherever they make the most sense and where data can move seamlessly between them.

• What should the industry be doing now to prepare networks for orbital compute?

I think the first step is recognizing that orbital compute is more than a compute challenge. It's a networking one. The industry has spent decades building highly interconnected ecosystems on Earth, where data can move efficiently between enterprises, cloud providers, networks, content platforms, and users.

If compute begins expanding into orbit, we'll need to ensure the same level of interconnection exists between terrestrial, satellite, and orbital environments. Advances in satellite communications, laser-based networking, and distributed infrastructure are creating new possibilities that didn't exist a decade ago.

What I'd like to see now is greater collaboration between network operators, cloud providers, infrastructure companies, and space organizations.

The technologies themselves are advancing rapidly, but the challenge is ensuring they evolve as part of a coherent ecosystem rather than a collection of isolated systems.

• Looking ten years ahead, what does a fully interconnected ecosystem spanning terrestrial, edge, cloud, satellite, and orbital infrastructure actually look like? What technologies will make it work?

The most interesting thing about the future is that people probably won't think about infrastructure at all. Today, we spend a lot of time talking about whether something runs in a cloud region, an edge location, a data center, or on a particular network.

Ten years from now, if we succeed with orbital infrastructure, workloads will simply move to wherever they can be processed most efficiently, and data will flow across terrestrial, satellite, and orbital environments as naturally as it moves across continents today.

When we look back at the great infrastructure achievements of the past, whether it's railways, electricity grids, undersea cables, or the Internet itself, their success wasn't measured by the technology, but by how completely they disappeared into everyday life.

People stopped thinking about the infrastructure and started focusing on what it enabled. I think we'll see something similar here. The future of digital infrastructure will be defined by our ability to connect every layer of the ecosystem into something that feels seamless.

That's when we'll know we've succeeded.

When you’re shopping for a new pair of headphones, you naturally want them to sound good, but how often do you actually think about how they look?

As someone who lives and breathes headphones, I think I’m experienced enough to claim that most pairs look the same. A simple, minimalist set of cans, usually available in black or white, and maybe with some chrome or coloured accents.

Pretty boring, right?

That’s certainly not the case with the Nothing Headphone (a) which, along with the flagship Nothing Headphone (1), completely reinvent headphone design for the better — and the former has now received a huge 36% discount at Amazon in the run up to Prime Day 2026 in Australia.

Not only do the Headphone (a) offer a distinctive design, but they’re also crammed with features that make them an utter joy to use. Sound quality is superb too, making these attractive over-ears a genuinely viable alternative to the more established names.View Deal

These are Nothing’s second over-ear headphone attempt, and they earned a glowing 4.5-star rating in our Nothing Headphone (a) review. We claimed them to be the “dream tech version 2.0” over the flagship Headphone (1), thanks to improved, more spacious sound, while retaining the same fantastic set of controls to adjust playback.

And then there’s how they look. The Headphone (a) are unmistakably a Nothing product, but the design has been softened a little compared to the flagship pair. The cassette tape look has been subbed out for a solid colour, available in white, pink or yellow. The pink colourway has received the biggest discount of 36%.

The Headphone (1) are still a fantastic pair of cans in their own right. They also come with the bold claim of being tuned by esteemed hi-fi brand KEF. As we said in our Nothing Headphone (1) review, the sound is “reasonably refined, well-balanced, and broadly enjoyable”.

The Headphone (1) boasts a wealth of features including effective ANC, Hi-Res audio in wired mode and head-tracked spatial audio. Pair them with a Nothing phone and you'll unlock even more. The sound profile is a little flat in comparison to the Headphone (a), but at this price, they're easy to recommend.View Deal

The slight downside is that the Headphone (1) sound a little compressed — I’ve used these headphones and can vouch for that comment. I personally don’t think it’s a huge deal breaker, though, and the amount of personalisation on offer via the companion app more than makes up for it. Plus, as our tester noted, “if they get a price drop, these could be great headphones”, and here it is.

With both pairs now costing similar money, your buying decision could well just come down to aesthetics. Regardless, you’ll be catching looks wherever you go.

I've been using the Nintendo Switch 2 since its launch week, playing practically every title released for the platform either as part of my work covering games here at TechRadar Gaming or my own personal enjoyment.

I've spent hours in everything from big new entries in first-party franchises like Mario Tennis Fever and Mario Kart World to groundbreaking ports such as Cyberpunk 2077 Ultimate Edition. I'm not just playing the big hitters either, and have invested loads of time in getting to grips with underrated gems including Kunitsu-Gami: Path of the Goddess and Raidou Remastered: The Mystery of the Soulless Army.

• View all of Amazon's current prices and deals on Nintendo Switch 2 games this Prime Day

While many of these games will be discounted over the course of the ongoing Amazon Prime Day deals, every title that I've included is well worth your time and attention regardless of its price.

Amazon Prime Day game deals

• PS5 games: God of War Ragnarok for just $32 and more
• Xbox games: loads of deals, including NBA 2K26 for just $10
• Nintendo Switch 2 games: Save $12 on the likes of Cyberpunk 2077 Ultimate Edition

Amazon Prime Day – the best Nintendo Switch 2 games I'd buy right now

Sonic X Shadow Generations

Yakuza 0: Director’s Cut

Star Wars Outlaws - Gold Edition

Fatal Frame 2: Crimson Butterfly Remake

Xbox Fallout 4 Anniversary Edition (Code in Box)

Cyberpunk 2077: Ultimate Edition

Street Fighter 6 Year 1-2 Fighters Edition

Mario Tennis Fever

Donkey Kong Bananza

Mario Kart World

Resident Evil Generation Pack (Requiem, Village, and 7)

Pragmata

More Prime Day deals in the US

• Amazon Devices: Fire Sticks & Echo from $18
• Amazon Haul: viral gadgets, tech & appliances from $1.99
• Apple: MacBooks, AirPods & AirTags from $29
• Beauty: 50% off toothbrushes & hair tools
• Cheap TVs: smart TVs from $69.99
• Garden: tools, mowers, planters from $24.99
• Headphones: 50% off Beats, Bose & Samsung
• Laptops: Apple, HP & Dell from $199
• Mattresses: Sealy, Serta & more from $186
• Patio: outdoor furniture, rugs & decor from $19.99
• Sports: 50% off fitness gear, treadmills & clothing
• Vacuums: Dyson, Shark & Bissell from $34

We already know watchOS 27 is coming and not all Apple Watches will support it. So if you’ve been holding off on upgrading an older Apple Watch or you’ve been thinking about getting your first one, then you don’t need to wait until Amazon Prime Day 2026 to score a great deal because the mainline Apple Watch Series 11 has just hit its all-time low price in Australia.

That’s right, Prime Day in Australia is still a little over a week away and Amazon is already discounting the wearable by 32% to just AU$447 for the 42mm GPS model.

While we’ve always recommended the more affordable Apple Watch SE 3 as the best for most people, we reckon this discount for the Series 11 is currently the better buy, especially if you value battery life, screen brightness, a slimmer chassis and more health monitoring.

This price is the lowest we’ve seen in Australia, though it only applies to the Jet Black and Rose Gold colours. If you have larger wrists, the 46mm is also discounted by 25% to AU$549, down from AU$729. The cheaper Apple Watch SE 3 has a smaller 13% discount, which isn’t as good a deal in comparison.View Deal

Our Apple Watch Series 11 review called it the most capable and best-looking mainline Apple Watch yet, praising the brighter, more efficient and more scratch-resistant Always-On Retina LTPO3 OLED display compared to its predecessor, as well as the larger battery capacity.

Battery capacity increased 9% for the 42mm and 11% for the 46mm model, with Apple rating both for 24 hours of typical use and up to 38 hours in Low Power Model. Our reviewer found the claim to be realistic, getting a full day and a half of battery life with light use.

On the software side, health tracking is more comprehensive with heart-rate alerts, ECG, wrist temperature, respiratory rate and cycle tracking, with blood pressure monitoring and hearing health as new additions. A Sleep Score feature has also been added (across all Apple Watches) to provide more easily digestible sleep tracking data.

Admittedly, the Apple Watch Series 11 won’t be much of an upgrade over the Series 10 as it’s very similar hardware, but upgrading from the Series 8 or older models, or even the Watch SE and SE 2, the performance jump will be a substantial boost.

And while we’re at it, marathon season is still in full swing in Australia, so this deal is worth a look as it can keep up with even the best running watches from the likes of Garmin.

While you might think Prime Day is all about deals on vacuums, iPads, and air fryers, it's also one of the best opportunities to score a rare discount on a popular streaming service.

Case in point: Amazon has a Prime Day Apple TV deal that lets you add an Apple TV subscription for only $5.99 a month for two months. It's normally $12.99 per month, which means you're getting a massive 54% off.

Apple TV lets you to watch popular shows like Your Friends and Neighbors, Shrinking, Widow's Bay, and my personal favorite and the reason I want to resubscribe, The Morning Show, which is coming back for a fifth season.

Something to keep in mind is that discounts from streaming services like Apple TV rarely happen, and today's Prime Day offer ends on June 26. Also remember, you'll need to subscribe through Prime Video and be an Amazon Prime member to score. If you aren't already a member, you can sign up today for a free 30-day trial.

Today's best Prime Day Apple TV deal

Apple TV (Prime Video add-on): was $12.98 now $5.99 per month for two months two months
Apple TV doesn't run promotional offers often, making this limited-time deal to get more than 50% of the usual monthly price of $12.99 one of the cheapest ways to sign up to the service right now. You'll be able to lock in a new low price of $5.99 a month for two months with this offer, but be quick because it ends on 26 June. View Deal

Shop more of today's best Prime Day deals

• Amazon Devices: Fire Sticks & Echo from $18
• Amazon Haul: viral gadgets, tech & appliances from $1.99
• Apple: MacBooks, AirPods & AirTags from $29
• Beauty: 50% off toothbrushes & hair tools
• Cheap TVs: smart TVs from $69.99
• Garden: tools, mowers, planters from $24.99
• Headphones: 50% off Beats, Bose & Samsung
• Laptops: Apple, HP & Dell from $199
• Mattresses: Sealy, Serta & more from $186
• Patio: outdoor furniture, rugs & decor from $19.99
• Sports: 50% off fitness gear, treadmills & clothing
• Vacuums: Dyson, Shark & Bissell from $34