News
In the early 2000s, IP VPN was the enterprise networking technology of choice for IT leaders.
MySpace was the go-to social network, we used Skype for video calls, we listened to music on our new MP3 players and the Nokia 1100 was the most popular mobile handset.
It feels like a different era entirely, yet many businesses are still running on legacy networks that were perfect for their needs back then but are now holding them back.
By today’s terms, networks were built for low levels of traffic. Cisco estimates global IP traffic levels were around 175 petabytes per month in 2001. Compare that to today’s figure, which is around 522,000 petabytes per month, or approximately 3000 times higher than 2001 levels, and you can understand why 87% of businesses in an Accenture study believe their legacy network is compromising their ability to advance on cloud, data and AI and digital transformation.
Untangling and replacing the complex web of enterprise networks built up over years is an unavoidable and costly necessity. It’s a bit like replacing the windows in your home - you know you’ll improve security, stormproof your home and cut energy costs by upgrading, but the process feels like a hassle.
Today, IT leaders aren’t just ‘replacing the windows’ by modernizing outdated networks; they’re going further and building high capacity, low latency, secure architectures designed to withstand the explosive demands of AI.
Making the move to SD WANMillions of businesses are switching from IP VPN to Software-Defined Wide Area Networks, or SD WAN. Strong market growth is forecast in SD WAN, with one market forecast anticipating SD WAN CAGR of almost 40% (38.9%) from 2023 to 2030.
This growth is being driven by multiple factors including a shift to cloud-native architectures; a change in workplace practices and rise in remote working environments; and strong demand for network architectures that can manage current and future AI-related applications and services.
SD WAN is faster, more cost effective and more secure, with built in zero trust protection. It’s purpose built for distributed users and for managing cloud, AI workloads, data flows, and SaaS traffic.
But, to be truly AI ready, IT infrastructure must be software driven, and this is where SD WAN excels: it gives your business the security, flexibility, and reliability needed to operate confidently in an AI driven future. Here are five ways switching to SD WAN will help you build an AI-ready network:
1.Built for AI-scale performanceHigh-bandwidth, low latency SD WANs are critical for the delivery of AI workloads, particularly as businesses move towards AI inference. They provide fast access to cloud services and dynamic bandwidth allocation as they monitor network conditions and reroute over the best available path.
For example, imagine a drive-through restaurant that uses an AI voice to take and relay orders or a supermarket that uses an AI model to scan shelves in its store, to detect gaps in stock, alert staff and predict which items will run out next. A high-performance, low latency network is essential here to guarantee a seamless customer experience.
SD WAN’s application-aware routing levels this up even further, prioritizing AI traffic and deprioritizing the transfer of, for example, bulk file transfers or back-ups.
2.Security that matches today’s threat landscapeThe global cyber attack surface has expanded dramatically. AI now plays a dual role, enabling more sophisticated attacks while also powering new, advanced defense capabilities. Traditional IP VPNs offer traffic encryption but lack native security features. In contrast, SD WAN is built to protect modern networks from today’s high volume, highly sophisticated cyber threats:
- Zero trust access protects users, devices and applications
- Traffic is encrypted end to end, so that all data between sites, platforms and applications is secure
- Threat prevention at the edge protects core infrastructure from threats, with features such as intrusion detection and prevention, malware scanning and DNS security
- Automated real-time security updates with threat intelligence pushed globally within minutes
3.Cloud connectivity without compromiseSD WANs provide direct, optimized access to major cloud environments, such as Microsoft Azure, AWS, and Google Cloud, by using automated secure tunnels and intelligent path selection.
This ensures cloud and AI services run with lower latency, higher performance, and more reliable connectivity. Also important to note is that SD WANs provide high levels of autonomy and automation, so it’s easy to make changes quickly and easily as businesses navigate dynamic market conditions.
4.Data insights that power automationSD WAN captures real-time data including latency, packet loss and application usage patterns – data which can be fed into AI-based network monitoring, automation and predictive maintenance management tools, so that networks become self-optimizing, self-healing and proactively secure.
5.A foundation ready for SASE and Zero TrustWhen combined with Secure Access Service Edge (SASE), SD WAN creates a single, secure, high performance network foundation that’s built to drive AI opportunities while protecting against cyber risks with integrated security solutions including zero trust, secure web gateways and cloud firewalls.
SASE is a cloud based networking and security framework that combines SD WAN with integrated security services (like Zero Trust, secure web gateways, and cloud firewalls) into a single unified architecture. It’s the gold standard of AI-ready architecture.
As enterprises accelerate toward an AI driven future, the networks that once served them well are now becoming a barrier to progress. SD WAN offers a clear path forward: a software defined, secure, high performance foundation built to handle the scale, speed and complexity of modern cloud and AI workloads.
By making the shift now, businesses can replace aging infrastructure with an agile, intelligent network that not only supports today’s demands but unlocks the full potential of tomorrow’s AI innovation.
We've ranked and reviewed the best antivirus software available.
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
London Tech Week’s focus on AI - from a £12 million investment in AI for SMEs to AI bootcamps for graduates and more - has reflected the pressure to compete in an AI-era.
As this digital revolution progresses, the job economy is changing, but the mantra that AI is taking our jobs is simply not correct and potentially fueled by an undercurrent of classicism.
When the Luddites famously started to break the first machines of the industrial revolution in 1811 in England, fearing for their job as textile artisans, the “Bourgeoisie” would describe them as “ignorant workers”, with no understanding of basic economics.
More than two hundred years later, with the rise of GenAI, it is no longer the blue-collar workers who fear for their job, but the white-collar workers. This time it is the “bourgeois” who live in the anxiety of an uncertain world.
Since ChatGPT introduced AI into the everyday lexicon, it has been clear that we would experience an unprecedented revolution. The rhetoric that immediately began to dominate social discourse has been that AI tools would render most jobs insignificant.
Furthermore, whilst other technological revolutions ended up being creative destruction, ‘this time it was different’.
But is that really the case? Or are we more fearful, more concerned about destroying the status quo, because this time it’s a different ‘class’ of people being impacted? This time it’s the desk workers, not the physical laborers, who risk losing jobs, and suddenly there is alarm.
Artificial Intelligence relies on humans - and more humans than everAI is a human creation and still relies on humans to evolve. First, we have those who build the infrastructure, like data centers, which accounted for almost all of the United States’ GDP growth in the first half of 2025 (according to Harvard economist Jason Furman).
Then, we have those who train the models, which still need to be constantly retrained. Even if models are able to train themselves eventually, there is no consensus that human intervention in training will become obsolete, because human behavior and the entropy of organizations are in a constant state of flux and evolution.
And even when trained, AI constantly needs to also understand the “context” in which it is prompted to perform efficiently. AI then needs to be deployed. Managing security, defining guardrails for agents, understanding how to use AI and tracking agentic AI’s actions, all comes with inherent challenges.
The CIOs of the largest global corporations are already investing hundreds of millions of pounds to understand this. Startups based in San Francisco - a city I recently visited where 95% of out-of-home ads were about AI agents - are focused entirely on resolving these problems for large enterprises.
The fact that both Anthropic and OpenAI have launched their own consulting companies is proof that managing AI complexities in the coming years will be the biggest source of growth for all consulting and outsourcing companies of the world.
Sourcing the right human talent in the AI era is the biggest challengeSoftware engineering is a job category where GenAI - perfectly trained on open-source code and GitHub repositories - can now code better than even the most experienced developers.
Additionally, developers in AI labs - with privileged access to “tokens” on Claude Code or OpenAI Codex - now develop 100% of the time without writing a single line of code. Nonetheless, when asked about their biggest challenges, all AI startups would point to recruitment.
A report by the UK's National Foundation for Education Research showed a 50% increase in tech job adverts between 2019/20 and 2024/25, with entry-level roles particularly affected. However, we’re now seeing a surge in demand driven by Gen Z, according to Employment Hero’s March Jobs Report.
This demand for AI expertise is reflected in a new Malt Tech Trends Report, which analyzed 1.2 million searches of tech freelancers in 2025. It reveals that AI is now the second most-in-demand skill, irrespective of company size, industry, or project type. More specifically, demand for freelancers with agentic AI expertise exploded by 5,800% in just twelve months.
Observer of the AI revolution, Andrew Ng, explains that if, for example, a team of 3 developers builds 10 times faster, then they need more designers or product managers to fuel the creative process. Doing more faster, with fewer people creates more work to fuel and execute the output.
More people are echoing the same rhetoric as Ng, calling out the phenomenon of ‘AI washing’, whereby companies have justified mass redundancies with AI disruption. In reality, in many cases, they were either adapting to geopolitical and economic uncertainties or had simply employed too many in the crazy post-COVID bull market.
The AI job apocalypse is not yet here… Still, the fear is real and needs to be understoodSoftware engineering is a perfect example of a job category that has constantly evolved. Since the inception of computer science, programming has become progressively more about “natural language”. Whilst there were 50,000 developers worldwide in the 1960s, today there are almost 50 million. Undoubtedly, the eradication of barriers to entry to build software increases that number tenfold.
History, data, and observation shows us that the AI job apocalypse is not yet here. Still, the fear is real and needs to be understood. The reason every science fiction novel paints an inhospitable world and unattractive paradigm is because the human mind always fears change. We assume the worst.
AI transformation, like all transformations, will be a cultural change first. And it’s companies, not professionals, who are most at risk if they fail to adapt. If one thing will be different in this digital revolution, compared to the last (arguably comparable is the advent of the internet), it’s the rate of change.
CEOs will have to be imaginative, change org charts and processes, admit they are not omniscient, take risks, and invest in training. Schools and universities also face the challenge of teaching soft skills: how to adapt to live and work in a more uncertain world. Because we can only harness top-tier AI talent if we understand how to truly adapt to change.
Independent professionals - those who create their own roles - from freelance developer to fractional manager and strategic consultants - have already redefined work.
On average, freelancers spend 4 hours a week on upskilling and keeping up with the job market and already have the habit of switching from one client project to another. They were the first to adapt to AI and realize that a job is more than just a bundle of tasks.
As Jensen Huang, CEO of Nvidia, recently said, if someone were to observe him at work, we would conclude that his day consists of tasks like making hundreds of calls and sending emails. AI will replace, augment, and improve these tasks. But it will not take Jensen’s job.
We've featured the best AI chatbot for business.
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
As enterprise AI systems evolve, the limiting factor is shifting. Model quality still matters, but it’s no longer the main issue holding systems back. Increasingly, what constrains performance, scalability, and cost is context.
Large language models are now expected to support long conversations, multi step reasoning, and complex workflows that span time, users, and systems.
Every one of those interactions generates tokens, and those tokens produce key value (KV) cache — the working memory that allows models to reason efficiently without constantly recomputing prior steps.
Most AI architectures still treat this context as temporary. KV cache typically lives in GPU memory, is tied to a single inference process, and is discarded as soon as resources are exhausted.
That approach might be acceptable for small scale experimentation, but it quickly breaks down in enterprise environments where context lengths grow, concurrency increases, and recomputation becomes expensive.
Inference context has quietly become one of the largest bottlenecks in enterprise AI.
KV cache as AI native dataTo understand why this matters, it helps to stop thinking about KV cache as “just a cache.”
Enterprises have spent decades building strategies around structured data and unstructured data, but AI introduces a third class that deserves just as much attention: AI native data. This is data generated by model execution itself, and KV cache is one of its most important forms.
KV cache directly determines inference latency, throughput, energy consumption, and cost. As context windows get longer and reasoning chains become deeper, the volume and importance of this data grow faster than token counts alone. When KV cache is constantly thrown away, systems pay for it through rising latency, lower GPU utilization, lost reasoning context, and higher inference costs.
At scale, this inefficiency becomes structural rather than incidental.
Why existing infrastructure assumptions don’t holdKV cache also exposes a mismatch with traditional infrastructure design.
GPU memory delivers exceptional performance, but it is scarce and local to a single server. CPU memory extends capacity but remains volatile. Local NVMe storage adds scale yet keeps context trapped at the node level. Traditional shared storage provides durability and resilience, but it wasn’t designed for highly dynamic, inference time state.
This leaves enterprises with a fragmented memory hierarchy where context is either fast but fragile, or persistent but difficult to access efficiently. No amount of tuning can fully resolve this, because the problem isn’t optimization — it’s architecture.
What enterprise AI needs is a way to treat inference context as system memory rather than disposable state.
Introducing an inference context memory layerThat shift is what we describe as an inference context memory layer.
Instead of forcing all KV cache to live and die inside GPU memory, this approach allows context to be created close to the GPU for low latency, then managed across a hierarchy of memory and storage tiers designed explicitly for inference workloads. Inactive context can move out of high cost memory without being discarded, while relevant context can be restored on demand without recomputation.
This changes the behavior of inference systems in a fundamental way. Inference is no longer a series of isolated executions that start from scratch each time. It becomes a continuous, stateful process where knowledge accumulates, moves, and is reused across sessions, agents, and nodes.
When storage becomes part of AI memoryMaking this work places new demands on storage.
Inference context is large, mostly immutable, and technically recomputable — but regenerating it at scale is costly and inefficient. A storage architecture for inference context must preserve locality when performance matters, enable sharing without manual replication, and provide resilience so context isn’t lost when hardware fails.
When storage is designed this way, it stops being just a place to store data and becomes an extension of AI memory itself. That shift has real economic consequences: faster time to first token, higher GPU utilization, support for much longer sessions, and dramatically lower cost per query.
For enterprise workloads like tax advisory, legal analysis, healthcare reasoning, financial planning, and customer support, this is critical. These systems depend on preserving reasoning history and conversational context, not repeatedly rebuilding it from scratch.
Context is now infrastructureEnterprise AI is entering a new phase.
Models will continue to advance, but the systems that scale successfully will be defined by how well they manage the intelligence those models produce. Tokens are no longer fleeting artifacts, and context is no longer something enterprises can afford to lose.
KV cache is AI native data. It represents system state. And increasingly, it must be treated as infrastructure.
The architectural principle is simple: generate context once, manage it intelligently, and reuse it wherever possible. That shift is foundational to making enterprise AI reliable, efficient, and scalable — and it’s why storage once again plays a central role in the future of computing.
Use the best business cloud storage to manage your data.
This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.
The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit
- Early listings for the Pixel 11 series were spotted on Amazon
- These include renders of the phones in various shades
- Some of the listed specs would be a downgrade
We’ve just seen perhaps the biggest Google Pixel 11 series leak yet, as listings for the Pixel 11, Pixel 11 Pro, Pixel 11 Pro XL, and Pixel 11 Pro Fold have all appeared on Amazon.
These were spotted by 9to5Google and — while they’ve now been removed — the site claims that they appear to be part of the ‘Google Store’ seller, which suggests they might be official listings, albeit a bit early.
In any case, you can see some images taken from the listings below, with the Pixel 11 itself being shown in Midnight (black), Fuchsia (pink), and Moss (green) shades. The Pro and Pro XL meanwhile appear in Dune (a pale pink), Sterling (a grayish lavender), Pine (green), and Light Fog (a pale blue), and the Pixel 11 Pro Fold is listed just in Midnight and Pine.
There’s a mix of bright and understated shades here, and reactions to the images — particularly the brighter ones — seems quite positive so far. Over on Reddit, comments include “those non-pro colors are incredible if true. That’s green and pink are just perfect,” “in pink omg,” and “Dune is pretty nice.”
That said, some reactions to the Pro shades are a bit less positive, including “Why can't the pro like get some fun colors too?,” and “imagine seeing the popularity of the bold orange iPhone Pro color and STILL choosing to offer the same boring muted colors for the Pro.”
Leaked images showing the Pixel 11 and Pixel 11 Pro9to5Google / AmazonLeaked images showing the Pixel 11 Pro Fold9to5Google / AmazonAnd when it comes to the other details in these listings, reactions are more universally negative. According to the listings, the standard Pixel 11 will have a 6.3-inch 1080 x 2424 screen, a 4,985mAh battery, 256GB of storage, and 12GB of RAM for $899 (probably £899 / AU$1,149 based on Google Pixel 10 pricing in these regions).
That’s the same price as the 256GB Pixel 10 launched at, though that’s also available in a cheaper 128GB version, and it’s unclear whether there will be a 128GB model this time. The listed specs are also identical, except the battery which is 15mAh higher capacity this time.
Less RAM and smaller batteriesAs for the Pixel 11 Pro, that’s listed with 12GB of RAM, down from 16GB in the Pixel 10 Pro, and 9to5Google also mentions a 5,115mAh battery in the Pixel 11 Pro XL (down from 5,200mAh in the Pixel 10 Pro XL), and a 4,750mAh one in the Pixel 11 Pro Fold (down from 5,015mAh in the Pixel 10 Pro Fold).
So these incomplete specs lists point to a mix of similar specs and downgrades, with Reddit responses including “people already thought the 10 Pro was a small upgrade,” and “iPhone 17 is such a better value.”
Still, while these early listings seem like they might be the real deal, there are some red flags, with 9to5Google highlighting that Android 16 is mentioned on them, when these phones are certain to run Android 17.
So there’s a chance these aren’t in fact official listings, and even if they are, that error means other details could be wrong too. We should find out for sure on August 12, as that’s when Google is unveiling these phones.
- Microsoft CEO Satya Nadella has warned AI companies are training their models on the business secrets of their customers
- These secrets are then used to train new, more powerful models, that are sold to their customer's competitors
- But, Nadella says there is a way to remain competitive without being locked in to one AI vendor
Microsoft CEO Satya Nadella has warned the big players in the AI industry are using their proprietary models to learn the business secrets of their customers, which they can then use to train and deploy more advanced AI models.
The crux of the issue, Nadella said in a blog post, is that, “You essentially pay for intelligence twice, once with money, and again with something even more valuable: the proprietary knowledge you must reveal to make that intelligence useful. The better you want the model to perform, the more of that knowledge you have to feed it!”
What Nadella is saying in essence, is that AI companies are harvesting sensitive business data from their customers, using it to make training their models cheaper, and then launching these models for use by their own customer’s competition.
“The kind of knowledge a competitor could never buy”“Models learn from ‘exhaust,’ the prompts people write, the tools agents use, and especially the corrections people make when the model is wrong. Every correction is distilled into institutional know-how,” Nadella explained.
Nadella also criticized how AI companies are increasingly complaining about how their models are being distilled by their own competition. For example, Anthropic accused retailer and e-commerce company Alibaba for using thousands of Claude prompts to distill their own models. By figuring out how a proprietary model works, you don’t have to spend the enormous amount of capital needed to source training data and create your own AI model.
This, for Nadella, is a major contradiction in how AI companies work. “While the great innovation that comes from model providers having fair use rights to train models on public data is needed, I find it ironic that the status quo is to then turn around and impose restrictive terms on distillation,” he said.
It is also therefore hypocritical for AI companies to accuse other companies of distilling their own product, and then include within their AI usage contracts clauses that allow AI companies to “reserve the right to learn from customer usage and interaction data.”
“In consuming intelligence, you are creating intelligence. And what you create should belong to you,” Nadella added.
On-prem is back in fashionNadella’s fix for this growing problem? It’s time to move back to on-prem. Nadella encourages businesses to “retain ownership” of the data they feed AI models by switching to the use of “proprietary learning environments” built on the cloud.
The added benefit of moving to these environments is that they allow businesses to switch between different AI models provided by different companies using “orchestration layers” and AI gateways.
There is also a growing trend of businesses switching to using open source technologies, which goes hand in hand with businesses operating in the cloud. Businesses can train open source AI models using their data that is already available in cloud environments to do much of what the proprietary models do, for far cheaper — and without handing over that same sensitive data to be used by AI companies to train their own models.
The on-prem solution also has additional benefits. AI models operated on-site within manufacturing plants, stores, and other premises are far cheaper and require less specialized hardware. Businesses that operate using a centralized cloud are increasingly encountering issues with data egress fees, storage bloat, and idle specialized hardware.
Google Cloud recently released a report about these very issues, and also encouraged businesses to move towards using AI gateways and on-prem models to reduce latency, improve resilience, and cut per-token costs by switching to local, highly optimized models.
Via TechCrunch
- Future Games Show will return for Gamescom 2026
- The main showcase will begin on August 26, followed by the FGS Live, and the FGS Best Of Gamescom will air on August 30
- Future Games Show at Gamescom will feature world premieres, new trailers, and more
The Future Games Show will officially return next month for Gamescom 2026 with three digital showcases.
Future Games Show at Gamescom will air the same day the industry event kicks off, on August 26, and feature new announcements from "some of the industry’s most creative studios," including world premieres, exclusive trailers, developer deep dives, and brand-new game demos.
The recent Future Game Show Summer Showcase in June included 40+ games and 11 world premieres, and reached over 17.8 million live and launch-weekend views, so viewers should expect some more exciting game reveals.
FGS Live From Gamescom will immediately follow the main showcase on August 26, be hosted by the FGS editorial team, and feature more world premieres and exclusive trailers, as well as news and interviews from the Gamescom show floor.
To round out the event, the FGS Best Of Gamescom broadcast will kick off on August 30 and take viewers to the show floor to wrap up the best games of the event. Those tuning in can also expect exclusive booth tours, developer interviews, and a recap of Gamescom’s most exciting announcements.
All three digital shows can be watched on Future Games Shows' Twitch, YouTube, X, TikTok, Facebook, and GamesRadar+.
"The Future Games Show is the best place to discover new games, from indie gems like acclaimed-puzzler Blue Prince to AAA blockbusters such as sci-fi RPG Exodus," said Daniel Dawkins, Content Director of Future Games Show at Future. "Our Summer Showcase delivered 3.72 wishlists per live viewer, comfortably outperforming industry averages, thanks to our super-engaged viewers.
"Since launching in 2020, we have been proud to showcase the industry's most exciting titles alongside premier hosts like Troy Baker, Alix Wilton Regan and Ben Starr. This Gamescom, we are delivering three massive digital showcases packed with the latest news and world premieres for PC and consoles. Don’t miss it!”
Shokz is a big name in running and fitness headphones. And if you've been intrigued by its bone conduction headphones but put off by the cost, there's now a chance to bag the Shokz OpenRun Pro at Amazon for $109.95 (was $124.95) — that's a record-low price.
Yes, these may be the older first-generation model, but they remain an excellent pair of headphones to this day. They boast excellent audio quality, a slim and comfortable design, and solid battery life of up to 10 hours.
While the OpenRun Pro 2 do offer better sound, a slightly larger battery, and more convenient charging options, I'd say these upgrades are not super-important to more casual users — and certainly aren't worth paying up to $70 more for.
Shokz OpenRun Pro — record-low priceIf you've never tried bone conduction headphones before, maybe this record-low price for the Shokz OpenRun Pro is what finally encourages you to pick up a pair. This may be the older model, but you still get excellent audio quality, a comfortable and slim fit, and good battery life of up to 10 hours. If you're a runner or fitness enthusiast who wants to avoid in-ear options or be aware of your surroundings, these are a great budget buy.View Deal
When we originally reviewed the Shokz OpenRun Pro, we called them "the best bone conduction headphones you can buy.' New models have been released now that improve the unique tech and add quality-of-life features, such as USB-C charging and longer battery life, but these are still a good buy at this low price.
If you are set on the tech but would prefer a newer model, though, do check out our guide to all of the best bone conduction headphones for several other options from top brands including Shokz, H2O, and Nank.
- Marvel is reportedly making a Nova movie with the aid of Loki's showrunner
- The cosmic hero was originally going to star in a Disney+ TV show
- If true, the film will need to address three big questions about the MCU
Marvel is turning its attentions to the stars again as it begins work on a movie starring fan-favorite character Nova.
Per Deadline, the comic-book titan has pivoted away from telling a story about the cosmic hero on Disney+ to give him the full big-screen treatment. Furthermore, Michael Waldron, who was Loki's showrunner and rewrote parts of the Doctor Strange and the Multiverse of Madness script, is leading development on the untitled Nova project.
According to Deadline's sources, the Marvel Cinematic Universe (MCU) flick is still in the early planning stages. Nonetheless, I've already got four big questions that Marvel and Waldron need to shed light on regarding their next sci-fi project…
1. Who will play Nova?Tenative rumors have circulated online that Powell could play Nova in the MCU (Image credit: Hulu)Chief among the answers I seek is which actor will portray the eponymous character.
With Waldron also the creator-in-chief on acclaimed sports comedy Chad Powers, a Hulu TV Original that starred Glen Powell, it's little surprise to see that the aforementioned actor has been linked with the titular role. Add in the fact that Marvel has prioritized casting A-listers in its movie and TV productions recently, and the charismatic Powell would fit the bill as a big name who could draw a crowd, too.
That said, Powell is far from the only star that Waldron has worked with before. Additionally, Marvel President Kevin Feige has occasionally stated his belief that the comic giant needs to reduce the costs of its films and TV series, which includes the salaries of those who appear in said screen projects. Powell's hiring, then, is certainly not a foregone conclusion.
2. Which version of the superhero will we see — Richard Rider, Sam Alexander, or Frankie Raye?It's unclear which version of Nova we'll see in this Marvel production (Image credit: Marvel Comics)Like the Green Lantern Corps that exist in DC Comics, there are hundreds of individuals who have held the rank of 'Nova' in Marvel Comics.
There are three particular human characters who are part of the insterstellar cop agency known as the Nova Corps, though — those being the aforementioned Rider, Alexander, and Raye.
Of that trio, Rider is the most famous, so it would make sense if Marvel decided to center Nova around this well-known individual. However, should Marvel want to go down the route of introducing a younger Nova to audiences, Alexander would be the way to go. Furthermore, if Marvel isn't worried about the fan backlash that could come from casting a female lead in this film and/or taking creative liberties with Raye's comic-book origins, it could turn heads by selecting the least likely member of this group to star in it.
For what it's worth, I think Marvel will play it safe and go for Rider — but that's just my view. Vote in the poll below to let me know which character you'd like to see!
3. Will Nova show us the off-screen destruction of Xandar at Thanos' hands?Thanos brought wrath and ruin to Xandar prior to the events of 2018's Avengers: Infinity War (Image credit: Marvel)Think you've heard the word 'Nova' before in the MCU? You'd be right. We were actually introduced to the Nova Corps in 2014's Guardians of the Galaxy Vol. 1, which saw the titular ragtag group travel to — and then save — Xandar, aka the capital city of the Nova Empire and, by proxy, the space cop agency's headquarters.
At the end of that film, the Nova Corps was entrusted with the Power Stone, aka one of the Infinity Stones. Unfortunately, as part of his genocidal plan to destroy half of all life in the universe, the Mad Titan known as Thanos soon came calling for said cosmic gem. Long story short: he acquired the Power Stone and, as punishment for Xandar's role in trying to stop him obtaining it, decimated the planet.
So, will we witness Xandar's destruction in a flashback sequence as part of Nova's story? If it had been developed and released by now, I believe we already would have. However, Nova won't arrive before the Marvel Multiverse Saga comes to an end with Avengers: Doomsday and Avengers: Secret Wars. And, with that Marvel Phase 6 duology set to reboot the MCU, I think it's incredibly unlikely that Xandar's annihilation at Thanos' hands will be depicted in Nova.
4. Can Waldron win over the MCU sceptics?Waldron is something of a divisive figure among Marvel fans (Image credit: Alberto E. Rodriguez)There's no denying that Waldron's apparent involvement in Nova has caused something of a ruckus online. Indeed, following the publication of Deadline's article, fans have taken to various Reddits, the ResetEra forums, and other social platforms to criticize or defend Waldron's hiring.
There are valid arguments on both sides of the debate, too. As Loki's head writer, Waldron proved he had the necessary writing chops to tell a sci-fi story that was focused on a beloved Marvel character. In sharp contrast to the praise he received for his work on that show, though, Waldron is often 'credited' with not only turning Doctor Strange 2 into a narrative mess, but also with undoing all of the growth that Wanda Maximoff/Scarlet Witch underwent in WandaVision and positioning her as a one-dimensional villain in Multiverse of Madness.
Of course, Loki and Doctor Strange 2 aren't the only screenwriting credits on Waldron's resume, but they're the ones that MCU diehards will know him from. In that sense, he's one for two in the 'great MCU project' department. The jury is still out, then, on whether it'll be one or two for three before Nova's arrival.
Heading off on a vacation? It's easy to forget about boring things like charging solutions, but when you're away from home, keeping your devices juiced up is both more important than usual, and more difficult than usual. I speak from experience — I've found myself in one too many foreign city after a long day of exploring, trying to memorize Google Maps directions to a hotel while my phone battery dwindles alarmingly into the red.
This year, though, I've decided to get myself prepared, and avoid all that stress by arming myself with the right travel gadgets. Luckily, at TechRadar our reviews team members have tested dozens of charging gadgets of all kinds, and below I've rounded up our top recommendations for travel.
I've included a mix of options here. There are plug-in charging stations that will let me juice up multiple gadgets at once if I end up in a hotel room with limited power outlets (or it's a foreign socket and I've only brought one plug adaptor). There are also plug-in or MagSafe power packs that I can keep in my bag for charging when out and about. I've also thrown in a couple more specialized options: a foldable pad that can juice up three different Apple devices at once, and a 6-port beast that can handle charging power-hungry laptops and tablets — ideal while working while on the go.
I've included a handy specs comparison table at the bottom of the page, and if you want to dig into more options, we have separate, dedicated guides to the best wireless chargers and the best power banks. Bon voyage!
Top travel chargers UGreen Uno 100W USB-C ChargerWhy's it good for travel? This is our very favorite charger overall, and it's very well-suited for travel. Charging is super-speedy and there's a good number of ports (four in total) for juicing up multiple gadgets at once. The mini robot styling, complete with changing facial expressions, isn't strictly necessary, but who doesn't want a bit of extra friendly company when they're away from home?
Pros- Super-fast charging
- Fun display and emojis
- Four ports including USB-A and USB-C
- Not the cheapest charger on the market
- Display could be a touch brighter
Why's it good for travel? We called this "the ultimate on-the-go charging solution". There's a wireless charging pad, a speedy USB-C port, and an integrated USB-C cable, and it's compact, high-quality and charges fast. If you can stretch to the higher price, it'd make a superb travel buddy.
Pros- Reliable performance
- Great build quality
- Integrated cable and USB-C port add flexibility
- Can get a little hot
- Price may be a turn-off
Why's it good for travel? An integrated, retractible USB-C cable means you don't have to worry about remembering to bring an extra cable or remember where you've put it. It's a generous length, which is helpful if your power outlet isn't optimally placed. In our tests, charging was impressively speedy, too.
Pros- Convenient retractable cable
- Strong overall performance
- Compact build
- Multi-port power distribution won’t suit all
- In-built cable doesn’t support Samsung Super Charge 2.0 45W
- Non-foldable prongs on UK model
Why's it good for travel? This palm-sized, fold-up, wireless charger is perfect for traveling Apple fans. It unfolds to offer up charging modules for an iPhone and AirPods, plus a certified Apple Watch fast-charging module. It also turns into a landscape stand for your iPhone.
Pros- Light-weight and travel-sized
- Good iPhone and Apple Watch charging speeds
- Can charge Apple Watches with loop bands
- Turns into a landscape stand for iPhone
- Tricky to take phone off charge one-handed
- Moves on surfaces easily
- It’s pretty pricey
Why's it good for travel? This compact power bank has an integrated, retractable charge cable — ultra-helpful if you're traveling about and don't want to have to remember a separate one — and a handy cord to clip on a backpack or belt loop.
Pros- Convenient retractable cable
- Useful display
- Solid overall performance
- Not enough wattage for more power-hungry devices
- Could recharge a little faster
- Thermal throttling can prevent peak performance
Why's it good for travel? If you have a MagSafe device you want to keep powered up, this slimline Anker power bank is a great choice. It's well-built, the charging is speedy, and the grip is strong enough that you won't have to worry about it dropping off.
Pros- Charges fast
- Strong magnetic grip
- Slim for a 10K battery
- Heavier than expected
- On the pricey side
Why's it good for travel? It's overkill for casual travelers just looking to juice up their phone and earbuds, but if you're working on the go, this charge station is an excellent choice. It has the most power-out ports of any featured in this list (four USB-C ports and two more USB-A) and packs a hefty output of 200W, making it suitable for power-hungry devices like laptops.
Pros- Six speedy charging ports
- High build quality
- Great value
- No Anker app compatibility
- Lacks any kind of display
Why's it good for travel? This Qi2 charger is light in weight, compact in size and has a reinforced power cable that won't mind being shoved into your luggage. The magnetic grip is secure and it's perfectly possible to keep using your phone while it's charging. If you just have one MagSafe device to charge, it's a great choice.
Pros- Easy to hold
- Robust power cable
- Reassuringly secure magnet
- Integrated power cable
- Slides around on surfaces
- Not as comfortable to hold as some alternatives
I'm always keeping my eye out this time of year for the ultimate 'back to school' laptop deals for our readers. Today, I think I've spotted a listing that could actually lay claim to that title.
It's the brand new Dell XPS 13, which is currently on sale for just $599 if you're a student. This new model has just been released at $699, but it looks like Dell is doing a particularly aggressive intro deal for prospective students right now.
To be honest, even at $699, I'd say this Dell XPS 13 is a strong contender. We haven't reviewed it yet here at TechRadar, but this iteration looks like a very compelling alternative to the likes of the new MacBook Neo, which is also $699.
It's surely no coincidence that the new XPS 13 is priced to compete with the MacBook Neo, as both offer a premium, lightweight laptop at a rock bottom price. The XPS 13 is obviously a Windows 11 machine, however, so it's the one to go for if you prefer Windows over MacOS.
Get the new Dell XPS 13 for just $599 todayProcessor: Intel Core 5-320
RAM: 8GB
Storage: 512GB
In a time where laptop prices are spiralling out of control, Dell's latest XPS 13 looks like a rare deal on a premium model. OK, so this is the baseline model with only 8GB of RAM, but the XPS 13 is a great laptop with a fantastic 120Hz display and excellent build quality. Considering that Dell are also offering students an impressive $100 discount at launch, this XPS 13 looks like a very competitive alternative to the likes of the MacBook Neo.View Deal
While we haven't reviewed this model yet, our sister-site Windows Central managed to check it out in-person earlier this year. Initial reports are exceedingly positive, with the price, display, and overall build quality being particular highlights.
Interestingly, Dell had MacBook Neos on display next to the New XPS 13, so journalists could directly compare the to models. According to Windows Central, the XPS 13 had better build quality, a better display, and it was lighter. Of course, they do love Windows laptops over on that site, so your preference may vary.
We still rate the MacBook Neo here at TechRadar with its eye-catching colors and incredible battery life.
With that said, if I were choosing between the two, I'd definitely be tempted by the XPS 13. Generally, I prefer Windows laptops, and the XPS 13's Thunderbolt 4 ports are more useful to me than the Neo's standard USB-C ports. I'm also partial to the XPS 13's display, which I think it is a little more modern-looking than the Neo's, with its thick-bezels.
- Microsoft is improving Windows 11 search in multiple ways
- That includes a calmer search panel, the ability to turn off web results, a better way of prioritizing returned results, and a more stable search overall
- This is in testing for now, and the main worry is how long it might take for Microsoft to usher all this through to release
If you're fed up with the way Windows 11's search functionality works – and you wouldn't be alone – some incoming changes are set to greatly improve this experience.
Microsoft revealed the tweaks to the search box in a blog post, explaining that they're being delivered via a gradual rollout to testers in the Experimental channel for Windows 11 preview builds.
The first major change is simply to make search a calmer place, so when the panel appears, it only contains a list of your recent searches (allowing you to easily fire up one of those again if you wish). The current clutter to the right of that list, including recommendations – some of which are outright adverts – along with trending searches has all been banished.
And the second important piece of work here is that Microsoft is finally giving Windows 11 users the ability to get rid of web results in search. Currently, when searching for a file in the operating system you get not just local results (for files on your drives), but also some web results which can get in the way.
In this new scheme of things, you'll be able to switch off all web results in Settings, and also ditch Microsoft Store suggestions too.
If you keep these results on, Microsoft notes that they won't be prioritized, although this is something the company had already started to address (it used to be the case that web content could appear at the top of the returned results in a truly baffling fashion). Web results have also been stripped of any 'promotional content' so you'll only get the most relevant answers if these results are enabled.
Microsoft has also bolstered the handling of results for Windows 11 settings so that more relevant options are flagged up higher in the pecking order, and Microsoft says further fine-tuning is planned on this front.
The search box will also be able to handle typos, with an improved ability to guess what you really meant ('Chrome' rather than 'Chome' for example), and it'll start to surface possible results after typing just two characters (another enhancement we've already heard about).
While this is mostly all about streamlining, Microsoft is going the other way in one notable respect — adding a bit more detail in for the files returned in the results. Search will now provide more info about files (such as when they were last opened) and a more in-depth preview in the right-hand panel, so you can more readily tell what you'll be opening if you click on that result.
Finally, Microsoft is making search more reliable, which involves "reducing [the] likelihood of crashing and loading issues" which is obviously a welcome move.
Analysis: the rollout fly in the soothing search ointment(Image credit: Microsoft)Windows 11 search has always been a somewhat painful affair for me, thanks mainly to the clutter of the thinly veiled (or not even veiled at all) ads, and the irrelevant results which were surfaced with a baffling level of priority, as noted. Windows 10 isn't a lot better, frankly, but at any rate, I'm very happy to see the fresh direction Microsoft has taken here.
The calmer search results are a major boon, with Microsoft following in the same vein as the streamlining it recently announced for the widgets panel, which was made a quieter place. (All this follows a broader early promise to rein in the upselling with Windows 11 and generally make the interface a more chilled place).
I was hoping that the option to turn off web results would be brought in, and this is the most important addition for me personally. I'm not alone, and the reaction to these various changes has been very positive, with the only real sticking point being impatience around when these new features will be rolled out. That's both in terms of testers wanting to try the revamped search box now, and the general computing public wondering when they will eventually get their hands on all this.
As this tester posts on Reddit: "We love this... except gradual rollouts. We don't like when things are inconsistent from PC to PC despite running identical [test] builds [of Windows 11]. It's really obnoxious and breaks muscle memory. But the changes seem great and I look forward to trying them."
As Microsoft points out in its blog post, it's worth remembering that there are now feature flags that can be enabled if you're really keen to try out something in a preview build, and it's not on your PC yet.
However, as for those asking: 'For those of us on release, when might this arrive?'
Well, that's a very different kettle of fish, as it could take quite some time for this work to progress through testing. Mainly because there are a lot of changes involved, and it's not something Microsoft will want to rush (especially given the drive to make search more reliable and stable).
And when these search improvements are eventually released outside of testing, it'll be on a controlled rollout that you won't be able to jump the queue with. However, there's a reason for that – Microsoft will need to observe the changes going live in a gradual manner to ensure no unexpected gremlins are crawling around in the works.
So, you will have to be patient, and there's some frustration around the length of time it can take for controlled rollouts to proceed these days (the Start menu overhaul from last year being a key example here – some folks still don't have it even now). But the good news is that these changes are coming, and they promise to revamp search in Windows 11 to a considerable extent. I can't wait (but I'll have to).