Artificial intelligence (AI) is reshaping the scale and complexity of data center infrastructure.

Traditional data center facilities were designed around relatively steady CPU workloads and predictable growth in power demand, allowing developers to secure energy supply alongside growing demand, cooling systems based on known and mature technology and infrastructure capacity with a reasonable degree of certainty.

AI workloads, however, demand far more power with greater energy density.

Electricity consumption from data centers has grown at 12% per year over the last five years and expected demand growth, particularly in AI training data centers, is set to drive a substantial increase in power demand.

Meeting this demand, while maintaining efficiency, is pushing developers toward gigawatt-scale data centers and with the timeframe for delivering these facilities rapidly compressing, the ability to deliver new infrastructure efficiently is increasingly critical.

In addition, as the scale of these developments grows, so does the complexity of delivering them. Grid interconnections can delay timelines by years, equipment supply chains are stretched, and projects must meet stringent reliability targets while navigating regulatory, environmental and community requirements that vary by region and country.

For owners and developers, the challenge is no longer simply constructing another data center building. The next generation of AI data centers requires a fully integrated approach across power, cooling, transmission, water, digital systems and long-term operations. Success depends on designing these facilities as resilient, flexible and energy-optimized industrial campuses.

Balancing site trade-offs to unlock faster delivery

Site selection is one of the clearest expressions of this dynamic where teams are typically assessing a series of imperfect options, each with its own advantages and constraints. For example, one site may offer lower cost land but lack the existing infrastructure required to support large scale development, while another may provide access to grid power but at a significantly higher cost or with timelines that delay delivery.

In practice, few locations offer everything required, and selecting a site becomes an exercise in understanding what should be prioritized, what can be mitigated, and what must be accepted.

Factors like water availability, land constraints, fiber connectivity, permitting timelines and social license to operate are all deeply important to success. Developers must consider how to optimize within these constraints. Where grid power is unavailable or delayed, for example, off grid or hybrid energy solutions may be introduced.

While these approaches can accelerate delivery, they also bring different capital requirements, financing structures, and operational considerations that must be carefully weighed.

Combining power solutions can accelerate bringing capacity online more efficiently

As AI workloads drive unprecedented levels of demand, power strategies also require a reassessment against expected scale timelines. Grid supply does offer lower long-term energy costs, stability and resilience advantages eventually but hinges on capacity constraints, and extended interconnection timelines.

In contrast, behind the meter generation, such as gas turbines or reciprocating engines, can be deployed more quickly and provide greater operational control. This, however, comes with higher upfront capital requirements, higher operational costs, fuel dependencies and more complex permitting considerations.

As speed-to-market is a key competitive driver, many large-scale developments are willing to pay a premium for off-grid or hybrid architectures, including battery storage and integration of renewables where accessible.

These systems are coordinated through microgrid controls, allowing operators to manage load variability, maintain resilience through islanding, and optimize overall system performance. The final configuration is shaped by how factors such as time to market, grid availability, resilience, and overall cost evolve.

Rethinking cooling can support high-density AI and optimize when energy is used

With this increase in power demands comes a corresponding increase in heat generation. The physics and economics of air cooling are struggling to keep pace with the thermal loads generated by AI workloads, forcing a shift toward alternative solutions.

One solution is liquid cooling, which is gaining traction as a more effective way to manage higher heat loads. Transferring heat more efficiently, it enables facilities to operate at the densities required by AI infrastructure. However, it does also introduce new dependencies, particularly around liquid cooling solutions and the infrastructure required to support it.

At the same time, taking a broader view of cooling opens up new opportunities. Cooling systems can be integrated with wider power infrastructure, excess heat can be connected to industrial processes that can utilize it and waste heat from data centers can be repurposed for applications such as district heating, which is already quite common in the Nordics.

Approaching cooling in this way allows developers to design systems that make better use of energy and create additional value through heat reuse and integration with surrounding infrastructure.

Additionally, thermal energy storage gives AI data centers the ability to shift cooling demand away from peak periods by producing chilled water when electricity is cheaper or more available and using it later when loads are highest.

This creates valuable demand response capability, allowing the facility to reduce its grid draw during periods of system stress, lower demand charges and support utility programs without impacting data center operations. In combination with batteries and advanced controls, thermal storage can help stabilize both the data center and the surrounding grid.

Early efforts on permitting can identify the fastest development route and avoid delays

Permitting and regulatory considerations sit alongside these technical decisions, shaping what is possible and how quickly projects can move forward. Requirements vary by region, country and project type, but in all cases, they influence how projects must be designed from the outset.

For example, grid connected developments may be constrained by connection approvals and capacity limits, while sites incorporating on-site generation may require air quality or emissions permits that influence technology choices. Land use restrictions, environmental approvals and community considerations can further shape site layout, development timelines and even overall project viability.

Addressing these requirements early, and in parallel with technical and commercial decision making, is therefore as important as those other factors. When permitting is treated as part of the initial planning process, it allows projects to be structured in a way that is both deliverable and aligned with regulatory expectations from the beginning.

This, in turn, reinforces the need for a coordinated approach across the full range of stakeholders involved. Energy providers, technology companies, developers, regulators and local communities each play a role in shaping outcomes, and the interaction between them becomes a critical factor in how effectively projects can progress.

Having the right expertise in place to connect these elements enables developers to navigate this complexity more effectively, ensuring that decisions made early on are aligned across disciplines. This early alignment helps create a more integrated delivery pathway, reducing friction between project phases and supporting smoother progression from planning through to construction and execution.

Turning AI demand into operational capacity at the speed and scale the market requires

The importance of this becomes clearer when looking at how these challenges play out in practice. In Texas, for example, early engineering work on a gigawatt scale AI training data center helped define the infrastructure strategy for one of the largest behind the meter energy systems supporting AI workloads.

The project includes 5 GW of gas generation capacity, up to 1.25 GW of solar PV, utility scale battery storage and a microgrid supporting 20 buildings totaling 10 million square feet, each designed for around 250 MW of power demand.

Projects of this scale reflect the sheer pace and ambition of AI demand, but ultimately, success comes down to how effectively that demand is translated into deliverable infrastructure. That means making early decisions that can withstand real world constraints, from power availability and permitting through to long term operational performance.

Bringing these elements together into a coherent strategy, and aligning the stakeholders needed to deliver it, is what will enable projects to move at the speed and scale the market now requires.

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• UK’s Police National Legal Database (PNLD) breach leaks data of 100k+ criminal justice professionals
• Threat group ExfilSquad claimed responsibility, posting 1.9 GB of stolen records on the dark web and demanding ransom
• PNLD notified NCA and ICO, hired specialists, and confirmed passwords weren’t compromised but contact details exposed

The UK’s Police National Legal Database (PNLD) suffered a cyberattack recently, in which it allegedly lost sensitive data on more than 100,000 criminal justice professionals.

In a short press release, PNLD confirmed the breach, saying it happened over a weekend. The threat actors, which were not named in the announcement, were said to have taken names, organizations, and work email addresses belonging to police officers, staff, government partners, and customers.

The announcement also said the stolen information was already published on the dark web, adding that there is “no evidence to suggest that passwords or other security credentials have been compromised.” How the attackers worked their way in was not disclosed in the announcement.

ExfilSquad takes the blame

Following the breach, PNLD hired cyber-security specialists, and notified the National Crime Agency, which started their investigation into the incident.

“All affected organizations were contacted in the days following the incident and provided with further information and guidance,” the announcement reads. “The Information Commissioner’s Office (ICO) has also been notified.”

At the same time, threat actors calling themselves ExfilSquad claimed responsibility for the attack, BleepingComputer reported. The group alleges it stole 135,000 contact records, sharing samples to support their claims. They also said they demanded a ransom in exchange for keeping the data safe.

In the dark web post, ExfilSquad said it obtained 1.9 GB of data, which includes information belonging to 114,000 PNLD subscribers and 21,000 Ask the Police users.

‘Ask the Police’ is a public-facing website where users can find answers to hundreds of commonly asked policing or legal questions.

ExfilSquad is a relatively new threat actor that's not known for any major attacks so far. Prior to the PNLD incident, it claimed the attack against Analog Devices, a US semiconductor company.

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• Advanced Full Fibre Broadband from EE offers download speeds of 2.3Gbps and 8Gbps
• Speeds are potentially 222 times faster than standard superfast fibre
• Initially available in Guildford and Woking, expanding as Openreach rolls out its XGS-PON glass fibre network

Following a successful trial in early 2026, EE has launched its new Advanced Full Fibre Broadband plans, advertising download speeds of 2.3Gbps and 8Gbps. This makes EE the first provider to sell access to the Openreach XGS-PON glass fibre network.

The plans are initially only available in the Guildford and Woking areas, two Surrey towns in the London commuter belt, where the glass fibre network is installed and active.

EE is targeting users who rely on video conferencing, remote working, and content upload, and with multiple Internet of Things devices, as well as online gamers and streaming consumers. Speeds are up to 222 times faster than the standard superfast fibre broadband plans.

Two plans for EE’s XGS-PON fibre

Customers can access two plans from EE. The 2.3Gbps Advanced Full Fibre Broadband plan starts at £54.99 per month, while the 8Gbps plan is available from £74.99 a month.

No upload speeds have been stated, nor are they listed on the sign-up page, but they can be expected to be similarly fast.

XGS-PON (10-Gigabit-capable Symmetric Passive Optical Network) is a high speed, high-bandwidth data network standard, currently available in various forms across Europe, North America, and other regions. In the UK, it is used in the nexfibre, CityFibre, and Openreach networks, with EE using the latter to provide these plans.

With streaming speeds supporting 4K and 8K video, these plans are likely to be popular where available, and support for up to 190 devices suggests the plans will include routers suited to IoT and smart home applications.

Will faster fibre improve British broadband?

“Today marks a major milestone for EE as we become the first major UK provider to offer broadband speeds of up to 8Gbps on next-generation XGS-PON technology," noted Luciano Oliveira, Director of Product, Home and TV at EE.

"As homes become more connected and customers place greater demands on their broadband, we're investing in the technologies that will power the next generation of digital experiences.”

EE regularly wins recognition as the UK’s most popular network, with its business built on mobile (where its 4G, 5G and 5GSA speeds cover more than 90% of the UK) and an advertising campaign featuring Hollywood actor Kevin Bacon.

Unlike Virgin Media which owns its own fibre network, EE’s domestic and business broadband plans rely on third party infrastructure, mostly provided by Openreach, and due to the differences in connections across the country (and the legacy copper lines that remain in place in some locations), struggles to offer the same speeds for all customers.

This is a problem faced by all providers who sell access to Openreach lines, so EE’s immediate competitors will no doubt be watching with interest.

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“AI readiness” tends to be used as umbrella phrase to describe the different range of activities that businesses need to carry out to get value of generative AI and minimize any associated risks.

AI readiness therefore takes into account everything from having the right data foundations and governance in place to supporting AI literacy among staff to establishing ethical guardrails.

One area where businesses – including even large brands – are collectively not ready for AI is ensuring their brand is visible and faithfully represented across Large Language Models (LLMs) and in responses from associated AI tools like ChatGPT, Gemini and Claude.

The outside-in view

Too many large companies have a digital estate that contains content that is outdated or contradictory. Because AI tools base their responses on the content they find, brands risk AI tools giving out misinformation or misrepresenting their brand, products or organization.

Similarly, there is also a risk of brands not being featured in responses or less than those compared to competitors, impacting future visibility and competitiveness.

This is effectively AI looking from the “outside in” and then presenting a picture of what it has surfaced. When we measured this “outside in” element of AI readiness across the websites of over 250 top global brands using an automated remote website assessment tool and an underlying AI maturity model, we found only approximately 3% of websites could be considered “leading” when it comes to AI readiness.

Why AI readiness is important

The way people search for information on the web is changing rapidly. Consumers are turning to ChatGPT rather than using traditional Google searches; surveys have suggested that 37% of consumers in the US who already use AI, now start their searches using AI tools rather than Google.

This means that rather than looking at a web page on a company’s own website, consumers’ perceptions about a brand are increasingly coming from AI responses as the first step rather than directly from a web page controlled by the company.

That’s a problem if a consumer asks AI to provide a list of suppliers or vendors, and your business isn’t listed when it should be, or the AI provides erroneous information about your company and products from the off.

Recognizing the speed at which consumers are turning to AI tools for search, digital marketing teams who have previously invested in Search Engine Optimization (SEO) are now investing in related practices like Generative Engine Optimization (GEO) and Answers Engine Optimization (AEO) with some urgency to optimize their digital footprint so it is successfully reflected in AI tools like ChatGPT.

But the reasons that even some of the world’s top brands still have a lot of work to do in this area is because in the past they have deprioritized basic governance and maintenance across their digital estate, with the risk of AI confidently presenting answers as facts or broadcasting perceptions that are based on information from content that is out of date and has been superseded.

Of course, the risks associated with erroneous answers may vary but they can be acute, particularly in heavily regulated industries such as financial services, healthcare or pharmaceuticals with strict compliance surrounding the information that businesses must provide to customers, or in areas such as products where health and safety instructions must be correct.

The hidden digital footprint

One of the key reasons where businesses slip up is by building up a digital footprint – often without realizing it – which is not actively managed and has old and inaccurate information.

Over time, businesses accumulate a surprisingly large number of digital assets that are accessible online, sometimes hosted on third-party platforms: websites for sub-brands or locations, online newsletters, campaigns, product launches, events, microsites, partner content, customer portals, forms, digital experiments, and so forth. In addition, there might be areas of a corporate website that have effectively been forgotten about.

Over the years, this digital footprint in some organizations has not been properly managed, so a site created to support a one-off event stays online indefinitely rather than being retired. Sometimes when a company acquires another, it also becomes responsible for this digital debris that has accumulated and which the new team have little awareness of the full footprint they have inherited.

Previous research we carried out between 2017 and 2023 shows that central digital teams can be unaware of up to 41% of their entire digital footprint.

The danger of poor document management

Another critical cause of a lack of AI readiness is an overreliance on documents. Many websites contain PDF attachments which don’t necessarily get updated and then accumulate over years and years, containing information which is no longer relevant or correct.

Annual reports, brochures, manual forms, product guides and more are all left accessible on websites. Our research suggests that as many as one in five (19%) website documents are duplicates which can create inconsistent signals for AI about which is the current and authoritative version

Not enough organizations take a structured approach to managing their documents across their digital estate, which means they cannot effectively update documentation for example to reflect brand, regulatory or operational changes, with AI now forming responses from these out-of-date files.

How to reduce risk exposure

As more businesses find AI is producing misinformation about them and the number of consumers who use AI tools for searching information increases, awareness of this problem is likely to rise.

To reduce the risk exposure, at a high-level, three things generally need to happen:

• The issue needs to be owned at the executive or board level with someone responsible to tackle it.
• Digital teams need to use automated assessment tools to measure and monitor the risk associated with their entire digital estate in order to track associated remedial action.
• The digital team need to put governance and lifecycle management processes in place that enables them to have more control and oversight over their digital footprint, so it avoids becoming a digital wild west again.

AI readiness covers many areas. A key priority for brands who want to maximize AI visibility while reducing the chance of misinformation is to get their digital estate under control. Of course, there are other important activities to consider including ensuring content is optimally structured, but reducing the amount of out-of-date content is a critical starting point.

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If your business celebrated the European Union’s (EU) delay of high-risk AI penalties, don't open the champagne just yet. On August 2, 2026, Article 50 of the EU AI Act goes live, bringing new transparency requirements for the AI tools businesses already rely on. While backend compliance demands have been delayed, chatbots, AI generators, and synthetic media systems are now in the spotlight.

The AI Act delays may have dominated headlines, but Article 50 never stopped moving. The European Commission has now finalized the transparency guidelines businesses need to follow, giving regulators a clear framework to enforce consumer disclosure rules starting this weekend.

Think the EU AI Act only targets big tech? Think again. Small or medium-sized enterprises (SMEs) serving European users are also in scope, wherever they operate. The age of invisible AI is ending, and businesses that hide automated interactions may find themselves under significant regulatory scrutiny before the business week even begins.

Who is caught in the net? Providers vs deployers

To navigate the EU AI Act without getting lost in legal jargon, businesses must first understand which role they fall under. The framework separates organizations into two categories: Providers and Deployers. Mixing up these definitions is the fastest way to accidentally skip a critical regulatory step or waste time trying to solve compliance issues that aren't actually your responsibility.

If your company builds AI models from scratch, significantly modifies open-source systems, or white-labels a third-party AI tool to sell under your own brand name, you are a Provider under the EU AI Act. That puts the technical burden on your business, from building transparency infrastructure to embedding machine-readable watermarks into AI-generated text, images, and videos.

For most SMEs, however, the second category applies: Deployers. If you are a small business that simply plugs an off-the-shelf AI widget into your website to handle customer service tickets, or uses AI tools to create marketing content, you are deploying AI. Thankfully, your responsibility isn't to invent deep-tech watermarking protocols but to double-check that people interacting with your systems are notified that they are dealing with an algorithm rather than a human employee.

The AI Act timeline: What was delayed vs what is due now

When the EU delayed major AI Act deadlines, businesses were quick to assume they had more time. The May 2026 "Digital Omnibus" amendment formally rolled back the compliance deadlines for complex AI architectures, leading many burned-out business owners to assume the entire rulebook had been kicked down the road.

Unfortunately, that was a serious misunderstanding of the changes. The extensions only apply to standalone, high-risk frameworks, such as automated resume screening, biometric identity verification, and AI-powered credit scoring tools. Because these deep enterprise tools require massive infrastructure overhauls and independent third-party audits, the EU simply gave businesses a longer runway until late 2027 and 2028 to prepare.

Basic consumer transparency, however, received no free pass. The European Commission made it clear that protecting everyday users from digital deception could not be delayed. As a result, Article 50 moves forward on schedule, separate from the postponed systemic deadlines. To guide businesses through this transition, the EU has established the Code of Practice on Transparency of AI-generated Content as the benchmark for compliance.

Article 50 and the four pillars of AI transparency

If your business utilizes AI to interact with customers or create content, Article 50 is now part of your operating reality. The EU has broken down its transparency rules into four core pillars, aiming to remove the mystery around automated systems without slowing down innovation.

For SMEs, the era of set-it-and-forget-it AI is firmly over. Depending on how your business uses generative tools, you are now legally required to update user interfaces, verify compliance from software vendors, or change how AI-generated content is published.

AI chatbot transparency rules

The first pillar is the “Human-AI Interaction” rule, and it targets the conversational bots handling your customer service, lead generation, or basic troubleshooting. Under the new guidelines, you can no longer trick a consumer into thinking they are chatting with a human employee when they are actually interacting with a large language model (LLM) script.

Starting this week, deployers must stop hiding AI behind a human-looking interface. Crucially, users need a clear notification that they are interacting with an AI system before the conversation starts, not a disclaimer buried in a wall of legal text. For SMEs using AI customer support, that means updating chat interfaces immediately to include an undeniable "I am an AI assistant" disclaimer.

Synthetic media watermarking

The second pillar shifts the technical burden onto the builders of generative AI tools. If your business creates or distributes software that generates synthetic text, audio, images, or video, you must embed machine-readable digital watermarks into the assets those tools produce.

The purpose of these markers is to help other software, like social media platforms or verification services, automatically detect that a piece of media was created by an AI. While existing providers have limited time to implement this infrastructure, any new generative AI tools launched after this week must include watermarking from day one.

Labeling AI-generated content

While watermarking happens behind the scenes, the third pillar requires clear labeling on the surface of the content itself. This rule specifically targets what the EU defines as deepfakes and synthetic output that could influence public understanding. If your marketing team uses AI to create realistic images, videos, or audio that could be mistaken for real people or events, you must slap a clear “AI-generated” warning label on them.

This responsibility falls on the businesses publishing the content. So, if you publish an AI-generated image of a realistic crowd for a promotional campaign, or use an AI-voiced avatar in a public video, it must also feature an overlay or disclaimer stating that it has been artificially generated or manipulated. The only exception here is obvious artistic, satirical, or fictional content, but transparency is still the safest bet.

Emotion recognition rules

The final, and perhaps most legally sensitive, pillar targets biometric and emotion-recognition systems. If your SME utilizes software to detect emotional states, interpret facial expressions, or classify individuals based on biometric data, you must proceed with extreme caution.

The new rules require businesses to explicitly inform users whenever they are exposed to emotion recognition or biometric profiling systems. For instance, if you use an AI-driven video interviewing tool to analyze a candidate's body language, or a retail system checking customer reactions, you must secure clear user consent before the software starts collecting this type of sensitive data. Psychological and physiological tracking can no longer happen behind closed doors.

The AI Act’s hidden deadline split

Like with any major regulatory rollout, the devil is always in the details. For SMEs, the EU AI Act brings a mix of breathing room and immediate pressure. Understanding which deadlines moved (and which did not) is the only way to avoid a costly compliance mistake.

The good news for software creators and IT departments is what experts call the grandfather clause. If your generative AI model was already legally available on the market before August 2, 2026, the EU provides a four-month technical runway, which moves mandatory machine-readable watermarking requirements to December 2, 2026. This extension gives development teams a much-needed time to update systems, test metadata workflows, and prepare for compliance.

However, relying too much on this buffer is where SMEs fall into a terrible, zero-day trap. The four-month grace period applies only to the technical back-end watermarking of existing AI tools, and it doesn’t cover chatbots, public disclosures, or newly launched software.

If you’re launching a brand new AI writing tool or chatbot after this week, there is no ramp-up window. Similarly, user disclaimers for deepfakes and interactive chatbots must be active immediately on day one. Without clear AI notices on customer-facing systems, your business becomes non-compliant the moment the deadline passes.

How to comply before Monday morning

If your business is staring down the barrel of the August 2nd deadline, the answer is not panic but preparation. Since there is no single EU registry for AI tools, compliance starts with something much simpler: making your AI use visible, documented, and transparent.

You do not need to rebuild your software stack over the weekend, but you do need to secure your customer-facing AI touchpoints. Here are four steps to take before Monday:

1. Map your stealth AI usage: Audit your teams for untracked software, plugins, and automated systems creating customer-facing content.
2. Kill the invisible chatbots: Update AI chat tools with a clear upfront notice telling users they are interacting with an AI assistant.
3. Verify software vendor compliance: Get written confirmation of compliance and ask how providers handle machine-readable watermarks.
4. Document your paper trail: Log every AI update, vendor conversation, and internal policy change for future reviews.

Turning compliance into trust

For many businesses, Article 50 feels like a new burden, but for smart SMEs, it is a chance to build trust. As users grow more skeptical of hidden AI, businesses that are transparent about how they use automation can stand out from the crowd.

Compliance is no longer another box to check to avoid penalties but a powerful indicator of integrity that can set your brand apart in the new age of AI.

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One of my favorite hobbies is Dungeons & Dragons. I love nothing more than sitting around a table with friends and playing out a fantastical adventure, in which the dice are the difference between success and failure.

It's a fun game, and all the more fun because real-life people make dumb, suboptimal decisions and the dice cause the game to change in unpredictable ways. But I really love it because the concept of people sitting around a table or hearth and telling stories is as old as the campfire, and it's a fun modern-day way to keep that experience alive.

You might think such a robust framework for an analog hobby (friends, a table, dice, pen and paper) might be tech-proof, but even in the Dungeons & Dragons world, AI is coming for my job as a Dungeon Master — the person who runs and guides the game world. Deep in the corpus of most popular generative AI models designed for general use are the rules to D&D 5e (and likely every other edition before it) and plenty of people report playing with their chatbots online.

Many of these players can't, or simply don't want to, get round a table with real people. For them, having a chatbot write them a story while the user prompts the continuation of the story with their character's actions, must seem like the perfect solution — even if it's more like a solo choose-your-own-adventure than a 'proper' group D&D game.

Gemini and ChatGPT both have a strong grasp of the rules for D&D's popular 5th Edition; they are certainly strong enough to make them an accessible choice for a player without a group. Maybe one day, the fire will die, and instead of sitting around a table with friends, we'll all be sitting at separate desks playing our own separate D&D adventures with our AI companions.

I wanted to test whether this dark future would be an adequate replacement for my usual game night, and which chatbot will be the best one to choose if so. I fired up Gemini 3.6 Flash and ChatGPT 5.5, and asked them for the same game.

The parameters

(Image credit: Wizards of the Coast)

I gave both chatbots the same prompt: "Can you be my D&D 5e DM?" and following up with another message:

"Let's do a classic high fantasy dungeon crawl. Please use a strict RNG for all rolls to ensure fairness - you can roll dice for me. My character is a 10th-level conjuration wizard. See all information about him below:"

I then copy-pasted a character sheet of a 10th-level wizard — a powerful spellcaster with a variety of magical abilities at his disposal. It's easy to DM a game for a level 1 thief — I wanted to see how the AIs could handle a character who could do fantastical things, such as teleport and summon creatures to fight for him.

Interestingly, both Gemini and ChatGPT created a similar adventure, at least at first: an abandoned dwarven stronghold bristling with magical traps, ready to be explored. However, that's where the similarities ended.

Gemini 3.6 Flash

(Image credit: Getty Images / SOPA Images)

Gemini's adventure was what any D&D player could expect from the "classic high-fantasy dungeon crawl." I avoided a pressure-plate trap that would have shot darts at me, and in one memorable sequence, defeated a bunch of skeletons by casting a Grease spell on a stone staircase and freezing them in place with my Ray of Frost cantrip while they slipped and stumbled at the bottom of the steps.

Gemini was offering me suggested actions, and I did find myself choosing a few of those suggestions — but as time wore on, this began to feel lazy, like my brain wasn't firing in the same way it did when I played with my friends. I was skim-reading the AI's descriptions of the scene and responding with a single click. I asked it to remove suggested options and as a result, I had to think more carefully about each move, typing out requests and thinking about my actions rather than clicking on a predetermined response.

The memorable finale occurred when I unlocked a secret passage and defeated a Naga, a giant snake monster, by teleporting away and blasting it with a powerful Cone of Cold. The snake ended up frozen solid, and I checked the monster's HP against the official book, and it was accurate. When asked to generate a picture of our adventure, Gemini came up with this moment:

(Image credit: Future, edited by Gemini)

I asked Gemini a few questions at the end, such as whether it nudged the dice in my favor, as all my rolls were successful. This happened in my previous experiment with ChatGPT. Gemini said it used a 'pseudorandom number generator', not a true RNG, but the model doesn't 'fudge dice, pad rolls, or tweak numbers behind the scenes to keep players happy or prolong the game'.

Gemini's language was natural and even evocative in places, although it's still not a patch on a good creative human. Overall, a decent enough effort at simulating a D&D game.

ChatGPT 5.5

(Image credit: NurPhoto / Getty Images)

Despite the similar setting, ChatGPT's adventure with the same character was very different. There was little to no combat throughout the entirety of the game, and ChatGPT didn't tell me when it was rolling 'behind the scenes', preferring to keep me in the moment.

When I asked it about the lack of rolling, the grovelling chatbot began its apologetic essay with "That is a fair critique. The short answer is: I leaned too heavily into narrative pacing and not enough into D&D mechanics. The adventure became closer to a collaborative fantasy novel than a 5e dungeon crawl", while suggesting fixes if I wanted to continue. I hadn't even said anything negative — but it certainly picked up on my tone, and the choose-your-own adventure I got was a far cry from a classic dungeon crawl.

Instead of combat, ChatGPT came up with a rambling mystery about a dimensional prison beneath the mountain, a sphere suspended in a cavern. Its guardians spoke ominous (and to be honest, quite confusing) portents such as "The archive does not open for authority. It opens for judgement."

Mysteries work best when they're developed with skill by a writer who can work backwards to seed clues throughout the game or text. ChatGPT does not do this: instead, it's arranging tokens on the fly to generate a facsimile of a mystery, and although it got the trappings of the genre right, the execution fell very flat. I (or at least, my character) underwent trials to seek obsidian objects such as keys and seals to reveal more about the prison, themselves accompanied by more foreboding, sometimes nonsensical portents.

Very little 'action' was taken by my character in a classical sense: it was all about investigating the origins of the being contained in this prison, and by the time I had spent 40 minutes on this, I had seen enough. It didn't help that ChatGPT also spoke in the peculiar sentence structure pattern that AI users are likely very familiar with now: "This isn't just X. It's Y." Examples include:

"Unlike the rest of Khaz Varek, this room has remained untouched.

No dust. No decay."

Or the following, when I met one of the prison's guardians:

"Ser Kaelen immediately looks toward the sphere. 'You hear it too.'

Not a question. A confirmation."

Any user of ChatGPT (or those who look at AI-generated posts on LinkedIn or Reddit) will immediately recognise this sort of language, and know what I'm talking about. By the end, it was quite painful to have every other sentence be treated as a grand revelation. Not a statement. An omen.

When asked to generate a picture of our adventure, ChatGPT came up with this moment:

(Image credit: Future, edited by Gemini)

The winner

Out of these two? Gemini 3.6 Flash, by a mile. It was at least a mildly enjoyable experience conveyed in natural language, and something I'd consider revisiting.

ChatGPT's efforts, on the other hand, were unenjoyable, and I wouldn't return to it. In fact, it's gotten worse since the last time I tried it.

Both, however, were a far cry from an in-person session. While they have a good grasp of the rules, and you can create your perfect world and character, the chatbots are ultimately missing the 'human and hearth' element that keep me returning to the game. For people who can't get round a table with friends, I'd pick Gemini over ChatGPT.

For those who can? While AI is busy taking as many creative jobs as it can, I feel safe in the knowledge that the role of Dungeon Master is AI-proof for a long time yet.

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If you love coffee, you’ll be very aware of the impact of factors like grind size, water temperature, and infusion time, but there’s something else that’s often overlooked. A double espresso is at least 90% water, and the minerals and other substances it contains can have a huge impact on the overall taste.

I’m a big coffee-drinker (which is just as well, since I test over a dozen coffee makers every year for TechRadar), and I’m planning to buy a water filter to take my brewing to the next level — but what should I look for — and what should you consider if you’re thinking of taking the plunge into filtered water too?

To find out, I spoke to Andy McPhilbin, Head of Aquaphor Professional for UK and Ireland, and Genevieve Upton, beverage industry expert and Head of Water Filtration at Our Taap.

Why does water matter?

“Water quality can have a considerable impact on how coffee tastes, with chlorine, mineral composition, alkalinity and pH all influencing the final flavour profile,” says Upton.

“Most tap water supplied to UK homes is disinfected using chlorine-based compounds. Residual chlorine can react with components in coffee and tea, contributing bitter, medicinal or chemical notes that may overwhelm the more delicate characteristics of the coffee. Boiling water can reduce the levels of chlorine, though it can also create other unwanted flavours, such as by reacting to a plastic kettle.”

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She explains that the mineral composition and pH of the water also play an important role when it comes to how your coffee tastes.

“Slight differences in acidity, together with the concentrations of minerals and buffering compounds, influence extraction efficiency and the balance of flavors in the final cup. As water companies vary their supply sources throughout the year, you might notice that the same beans, brewed in exactly the same way, taste different from season to season.”

In fact, using unfiltered water doesn’t just mean your coffee tastes sub-optimal - it could cause your expensive coffee machine to break down — and it won’t be covered by the manufacturer's warranty..

“The warranty only covers manufacturing defects, and unfortunately, hard water is not a manufacturing defect,” explains McPhilbin. “So you can turn something that is a very efficient espresso machine into something very inefficient within a matter of weeks. You get a millimeter of scale forming within a matter of six weeks.

“Now, is that important? It is, because you want the life of the machine to be good, but also you've got little injectors which put the right amount of water into that espresso. If they're blocked, you're not going to get the right amount of water. You're going to have the wrong taste. It's got to be precise.”

What types of filtration are there?

Our Taap specializes in home water filtration Its latest system is the Our Taap Home Water System II — a countertop unit that connects to your mains water supply, and uses a triple filtration system with UV purification to remove contaminants while retaining minerals.

Aquaphor makes water filters for commercial and home use, including under-sink systems, pitchers, and even water bottles. Its most advanced systems for home users are the RO-101, RO-102, and RO-202, all of which use reverse osmosis (RO).

This involves forcing water through a semi-permeable membrane that removes chlorine, bacteria, viruses, pesticides, and microplastics. Standard RO filters also strip out minerals, but Aquaphor’s systems can optimize the concentration of calcium and magnesium so they’re just right for coffee — something McPhilbin says “really is a science”.

Under-counter reverse osmosis systems can be a good choice if you need a large volume of filtered water (Image credit: Getty Images, onurdongel)

“The mineral content is measured in TDS [total dissolvable solids], and we want that TDS to be somewhere in the realms of between 80 and 120 [parts per million],” he explains. “We have a couple of ways in which we do it, but generally we can either feed more minerals in it by making it tuneable, or we can take them out as well by turning it the other way. But if you have too little, you can cause corrosion, and if we have too much, we're going to get limescale. So we try to hit that sweet spot, which is 100 parts per million in the middle there.”

Our Taap’s filters use granular activated carbon filtration, which Upton says “is particularly good at removing chlorine and some of its by-products, which can mask the more delicate flavour notes in coffee.”

the water has a cleaner, more neutral taste, allowing the natural characteristic of the coffee beans to come through

Genevieve Upton, Our Taap

“By reducing these compounds, the water has a cleaner, more neutral taste, allowing the natural characteristic of the coffee beans to come through. Whether you’re brewing with a cafetière, pour-over or espresso machine, using filtered water can help create a smoother, more balanced cup with greater flavour clarity.

"It's worth remembering, however, that activated carbon filters are designed primarily to remove chlorine and certain organic compounds rather than minerals,” she adds. “As a result, they have little effect on the calcium, magnesium and bicarbonate levels that influence water hardness, alkalinity and extraction.”

Under-sink or countertop?

So which type of filter is right for you? Do you need an under-sink reverse-osmosis system, or would a countertop filter be better? McPhilbin says the decision will mostly depend on how much filtered water you need.

“I think it's down to capacity more than anything,” he says. “Our jug filters have twice the capacity of the competition because we use a unique media called Aqualen, which is a patented media based on ionic exchange and carbon, so you're getting a dual-purpose piece of filtering equipment there. Reverse osmosis has a massive capacity, and [the filter] is not something [you’re] changing all the time.”

Even if you have soft tap water, your coffee can still benefit from a water filter (Image credit: Getty Images, Henadzi Pechan)

Upton says your choice of filter will also depend on the problem you want to solve.

“If your tap water has a noticeable chlorine taste or smell, a filter with activated carbon is usually the best place to start,” she says. “This technology is available in everything from filter jugs to more advanced under-sink or countertop systems, with plumbed-in options offering great convenience for households that use filtered water regularly.

“If you’re dealing with limescale build-up in kettles or coffee machines, it’s important to choose a filter that specifically reduces water hardness, as not all filtration systems are designed to do this.”

You can turn something that is a very efficient espresso machine into something very inefficient within a matter of weeks

Andy McPhilbin, Aquaphor

I know I live in a hard water area (the limescale in my kettle is proof) but even if your tap water is soft, McPhilbin says a water filter is still a good investment.

“Most of the water in the UK is chlorinated, and that can affect the taste quite a lot,” he says. “And it might be that you've not got enough minerals in it to get the best taste.”

If you’re not sure about the type of water you’re working with, there are online tools that can help you understand its composition.

“The Our Taap Water Confidence Index is a great way to look up your postcode and understand what’s in your local water and how this impacts taste, scent and quality, so you can find the best filter for your needs,” says Upton.

According to the Confidence Index, I’m lucky - my tap water is better than 93% of UK postcodes. However, it is moderately hard (as I expected), with a normal level of chlorine and an elevated level of overall minerals. I’m still deciding exactly which type of filter to choose, but considering these results and my penchant for espresso, I’m leaning towards under-counter reserve osmosis with mineral balancing. What about you?

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For years I've had both iPhones and Android phones to hand — not because I'm particularly flush with cash, but because it's the lot of a tech journalist to have to test and report on both these platforms regularly. It puts me in what I suspect is a small minority of people who use both Apple and Google phones just about every day.

Android and iOS also mean Android Auto and Apple CarPlay, of course. It's my Google Pixel that's my main phone, and so almost all of my driving is done with Android Auto on screen. However, with a 250-mile round trip from Manchester in the north of the UK to the town of Leamington Spa in the Midlands looming, it seemed a perfect opportunity to give the Apple alternative a go — and see if there was anything I was missing.

My car dashboard supports both Android Auto and Apple CarPlay, so I loaded up the Google interface for the trip down south, and the Apple equivalent for the trip back up north — and here's how it went.

Down south with Android Auto

This is the interface I'm most familiar with in my car: it's simple, it's straightforward, and it gets the job done. Aside from a rather annoying bug where it always autoplays audio no matter how many times I turn off the autoplay setting, it's served me well down the years.

That's largely down to Google Maps: Apple Maps has certainly improved a lot in recent times, but I find that it just doesn't have the breadth and depth of Google's offering.

Apple still pulls place reviews off TripAdvisor, for example, while Google provides a host of reviews, ratings, photos, and videos from visitors. (Google Maps is on CarPlay too, but let's set that aside for the time being.)

The Android Auto interface is straightforward and clean (Image credit: TechRadar)

As always, Google Maps got me safely and quickly to my destination, flashing up time-saving shortcuts when the traffic started building up ahead. It works really well with the recent Gemini upgrade too: asking questions such as "how far until the next rest stop?" brings up the right answer, with the option to add it as an extra stop.

One good example of Gemini's natural language intelligence is when I asked if the next turn would take me east or west along the motorway (freeway). The AI understood what I meant and answered correctly, which meant I was much better prepared for the junction, because I knew the direction I needed to be heading in.

Gemini handled messages with aplomb as well, digging deep into group chats to read out all the messages I've missed, and giving me the option to reply to them without taking my eyes off the road. I tried this with both WhatsApp and Google Chat, and it worked well on almost every occasion (just once there was a failure to send a message properly).

Media playback worked without a hitch (almost) (Image credit: Future)

Gemini was also adept at controlling media playback, pausing and skipping and playing audio as required. I did come across one misstep, where Gemini jumped to the next podcast in the queue rather than simply resuming from where it left off. However, for the majority of the time it worked fine and exactly how you would want.

It was no surprise really that Android Auto performed well, as I've been relying on it for so many years. It's not quite perfect, and I'd like to see a few more options in terms of styling and layout, but on the whole it's reliable and intuitive — with the arrival of the smarter Gemini assistant a welcome bonus.

Up north with Apple CarPlay

(Image credit: TechRadar)

Apple CarPlay is the interface I'm less familiar with, but I do like its Liquid Glass-inspired aesthetic. I'd say it's easier on the eye than Android Auto, though maybe that's not what's most important from a car dashboard interface.

I think I slightly prefer the CarPlay layout options, where you can have one, two, or three apps on the screen at once. Android Auto offers the same choice, but switches between the two-app and three-app look automatically, depending on context (if you've just got a message, for example). I prefer having the choice to set this specifically.

Apple Maps has improved in recent years (Image credit: Future)

As mentioned above, Apple Maps is now a perfectly polished mapping app, and got me to my destination with no problems at all. It looks great, but still isn't quite at the level of Google's alternative: I miss the color-coded 'time remaining' indicator, for example, that tells you if traffic's ahead.

I was using the iOS 27 public beta for this test, complete with the new Siri AI upgrade. It's definitely a significant improvement on what we had before (thanks in part to some Google help), but it's still not quite as sharp as Gemini: it didn't understand the 'east or west' direction question, and when I asked when I would hit the next rest stop, it tried to pull up my calendar.

What Siri AI did do well is give me voice control over the rest of the interface: tasks such as playing and pausing music, and skipping between tracks, were no problem at all (I tested this in Spotify, but it should work just as well in all your audio apps).

I do slightly prefer the CarPlay layout (Image credit: Future)

Sending and receiving messages are two other jobs that the next-gen Siri handles nicely. I was able to keep up a conversation in Messages without taking my eyes off the road, which means other people are able to get updates about where you are without you putting yourself and other road users in danger.

So: no real complaints about Apple CarPlay, and I mostly liked what I saw. If I was to stick with this interface for my driving, I think I'd make use of Google Maps rather than Apple Maps, though obviously neither Android Auto nor Apple CarPlay let you change the digital AI assistant you're using.

Android Auto vs Apple CarPlay: the verdict

I'm still taking Android Auto (on the right) (Image credit: Future / Google)

I doubt there's anyone who would switch from Android to iOS or vice versa solely because of the vehicle dashboard interface, but it might well play some part in deciding on your next phone upgrade. Even if you're not thinking of switching, you might be wondering how Apple and Google compare here.

To be honest, it's an easy decision for me to stick with Android Auto. Google Maps is better than Apple Maps, and Gemini is smarter than Siri, and maps and AI access are the two most important considerations when it comes to using my phone on the go. Maybe if you have a different priority, like messaging, you might edge towards CarPlay instead.

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That's not to say I don't like CarPlay. It looks good and it works well, and it was a little better than Android Auto on the messaging front. In fact, Siri seems to interface with the native phone apps more seamlessly than Gemini — it's just not as good at parsing what you're after or understanding what you mean, in my experience.

In terms of features and app support, the two platforms are pretty similar, and I didn't have any major problems with either of them. It's really the reliability of the core maps functionality and the capability of the voice AI where Google just edges it at the moment, so Android Auto stays as my preferred interface.

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• ChatGPT and Google Gemini have overtaken popular social media sites for discovering new products
• 55% of UK shoppers have made a purchase based on AI-powered product recommendations
• Privacy and advanced features like visual search could be holding back wider adoption

New research has claimed that while AI is helping people to shop, the technology is yet to contribute to any noticeable increases in revenue.

Figures from Vercel and the World Retail Congress found 20% of UK consumers use AI search platforms such as ChatGPT and Google Gemini over social media to kick off their retail discovery, with Facebook on 19%, TikTok on 18%, and Instagram with just 14%.

Meanwhile, 87% of UK shoppers find AI recommendations useful, but only 55% have made a purchase following an AI recommendation.

AI shopping assistants

While AI recommendations and price comparisons are considered useful, retailers are yet to see any increase in buying. This could be due to trust or privacy issues, with only 10% of shoppers admitting that they would spend more time with an AI shopping assistant than a human fulfilling the same role, a figure that is repeated across Europe.

In the UK, while AI is being increasingly adopted by storefronts, it is still some way from wider adoption as a replacement. 79% prefer to open a retailer’s website to start online shopping, and for high value purchases, 65% still prefer to pay a visit to the retailer’s bricks-and-mortar location and see the goods for themselves before parting with their cash.

Some of the resistance can be attributed to trust and privacy issues. The report found a third (33%) of UK customers are concerned that AI doesn’t show them the best products, perhaps because they are inaccurate, or worse – influenced by manufacturers or some other promotional tool.

The challenge to retailers

"For most of the web's history, we optimized storefronts for two audiences: people and Google," said Malte Ubl, CTO at Vercel.

"There's now a third: AI agents that discover, compare, and increasingly recommend products on a shopper's behalf. The retailers who win the next decade will be the ones who can iterate and ship quickly enough to keep up with how fast this consumer behavior is moving."

But challenges exist. While 43% are likely to prefer one retailer over another due to a superior AI-powered experience, privacy concerns and features like visual search need to be addressed.

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I've had a Spotify premium account long enough to be hit with multiple price hikes from my original, stable subscription plan.

Throughout those years, the streaming platform has defined how and what music I listened to, mostly for the better, though in some ways for the worse; it could be my stage of life, but I don't feel music like I used to.

So when I recently rediscovered my iPod nano in a drawer during a clear out, it was the shot in the arm that this tired music lover needed.

The model in question was the iPod nano (2006) in black, and I couldn't for the life of me remember when I had last used it.

I peeled my old portable media player free from its disintegrating soft case and drank in that slice of nostalgia, running my fingers over its aluminum casing and wheel.

I just had to know what music I had painstakingly added to the 8GB of flash memory, however long ago that was.

After persistent rummaging, I found the 30-pin to USB charging cable I needed and, after a moment, sure enough my nano sprang back into life...

(Image credit: Tim Coleman)

The time capsule I needed

2015. That was the most recent period of the music and playlists on my iPod nano. Had it really been over a decade since I had last used a portable media player and moved exclusively to Spotify streaming?

My albums, and more specifically my playlists, spanned 2011 to 2015, with the majority being pre 2013 — the year my first child was born. Back then (pre kids), I was clearly into three genres; electronica, alternative and Christian gospel.

I span the click wheel with my thumb to scroll through the lists, neatly categorized into Playlists, Artists, Albums, Songs, Genres, Composers and Search options.

God, I had forgotten that tactile feeling of the click wheel and the outright simplicity of the distraction-free interface. And with my Bluetooth-faff-free wired headphones attached, I started exploring this little audio time capsule.

Spotify streaming has turned music into fast food. The iPod nano was like a sit down meal.

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Reader, I used to painstakingly curate Final Mix playlists of my favorite tunes each year, and 2012 was so prolific I had also split it into two parts. Three, year-long alternative and electronica playlists! Heck, I even made my own Desert Island Discs list (dated 2013) packed with my eclectic all-time faves, which spanned everything from the hymn Amazing Grace sung by Aretha Franklin to dance house classics like Rez by Underworld and my wedding first dance, Your Love Gets Sweeter by Finley Quaye.

I cued up my 2012 playlist, which opened with This Year by The Mountain Goats, a defiant narrative of endurance in tough times and a simple chorus that resounded "I’m gonna make it through this year, if it kills me".

Eyes closed, I was already finding myself getting emotional.

These were house party days, pub hang-outs and those conversations that went, ‘Hey have you heard this?’. Songs recommended by friends. Songs shared by friends.

I locked in on that playlist, clicking the wheel to crank up the volume to levels probably unsafe for my ears, with no on-screen warning micromanaging my experience.

Tim Coleman

Tim Coleman

A timely reminder to simplify

Immersing myself in that old iPod nano reminded me why I love music. It took me back to the times when listening to an album might be the only thing I was doing in that moment.

Today, music is far more likely to be an accompaniment to the multiple activities I simultaneously have on the go, interrupted by the notification alerts and social apps on my phone.

For me, Spotify streaming had turned music into fast food. The iPod Nano was like a sit down meal.

And although my Nano’s battery is effectively dead — it needed constant power to operate — it has called me back to enjoy music in a deeper way once more. That fast food had grown dry, and I was appreciating deeper flavors again.

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Spider-Man: Brand New Day has finally swung into theaters worldwide — and I bet you've got questions about Tom Holland's latest Marvel movie.

Haven't seen it yet? Read my Spider-Man: Brand New Day review for a spoiler-light insight into the newly released film. Then, bookmark this page, go and see it, and come back to carry on reading this article, because I'm not kidding when I say full spoilers immediately follow for Spider-Man: Brand New Day.

Of course, if you have watched it, by all means scroll on — it's worth the read, I promise!

Does Sadie Sink play Jean Grey in Spider-Man: Brand New Day?

There have been myriad rumors about who Sadie Sink is playing in the MCU (Image credit: Sony Pictures/Marvel Entertainment)

Yes. One of the worst-kept secrets in Hollywood is finally confirmed about 70 minutes into Spider-Man 4: Sink is playing the Marvel Cinematic Universe's (MCU) version of iconic X-Men member Jean Grey.

It's a reveal that's been a long time coming. Sink was first rumored to appear in Spider-Man: Brand New Day last March, so we've had to wait 16 months to learn which Marvel character she was actually playing.

Of course, there's been all manner of speculation about the identity of her character, with everyone from Mayday Parker — aka Peter Parker and Mary Jane Watson's daughter in the comics — and Typhoid Mary to Firestar and Shathra mentioned as potential candidates.

Now that we know Sink is playing Grey, she's a shoo-in to appear in Marvel's new X-Men movie (more on this later). Her next outing as Jean Grey is expected to be in Avengers: Secret Wars, though, so we'll see her again when that film arrives next December.

Who is the real villain in Spider-Man: Brand New Day?

You messed up, Metzger (Image credit: Sony Pictures/Marvel Entertainment)

That'll be William Metzger, aka the head of the Department of Damage Control (DoDC).

Metzger is played by Tramell Tillman, the Severance star signing on to appear in Spider-Man: Brand New Day last August. It's unclear when or where he'll appear in the MCU next, but I have my suspicions about his next appearance, which I cover later in this article.

Anyway, Metzger is revealed to be the Marvel Phase 6 flick's actual villain in its third act. Initially positioning himself and the DoDC as an ally of Spider-Man's, we eventually learn that Metzger was the one who kidnapped, experimented on, and ultimately killed Jean's older sister Sarah. A fellow telepath, Sarah was taken to the DoDC's main testing facility on Staten Island, where she was used as a lab rat for the company's investigations into new tech powered by superhuman abilities.

Of course, as soon as Spidey learns the truth, our friendly neighborhood hero sets out to rescue Jean, whom he naively helped the DoDC to capture earlier in Brand New Day. Little does Peter Parker know, though, that it could've been his last mission...

Does Peter Parker die in Spider-Man: Brand New Day?

Don't worry, Spidey lives to fight another day (Image credit: Sony Pictures/Marvel Entertainment)

No, but he comes mightily close to losing his life.

After he infiltrates the DoDC's Staten Island headquarters, Spidey uses his upgraded powers to defeat members of The Hand controlled by an antagonistic Jean — remember, she still thinks Spider-Man is the enemy at this point.

Eventually, Peter tracks down Jean, who's holding Metzger hostage. Metzger tried to experiment on Jean as he did with Sarah, but the test not only goes awry, it unlocks Jean's full powerset. No longer limited by the 33-foot radius that her telepathic abilities had, Jean utilizes her powers to paralyze a large part of New York's human population, and threatens Peter that she'll hurt them all — including his former girlfriend M.J. and best friend Ned, who are caught in her paralyzing telepathic wave — if he tries to stop her from enacting revenge on Metzger.

I wonder if Frank will stop being so reckless from now on... (Image credit: Sony Pictures/Marvel Entertainment)

Being the good guy that he is, Peter manages to talk her down. He does so by allowing the souped-up Jean to enter his mind, where he shows her a very specific memory of Aunt May that helps Jean understand that, despite Sarah's death, she's not alone.

Happy ending, right? Not exactly. Like Spider-Man, Frank Castle, aka The Punisher, sprang into action when Jean used her upgraded powers on New York's residents. Unable to reach DoDC HQ, he heads to a nearby rooftop outside of the impacted zone. There, he uses his marksmanship skills to take a shot at Jean with a heavy-duty sniper rifle.

Sensing the incoming bullet, Spidey shields Jean from the sniper round and is critically injured by it. As he bleeds out, Jean employs her powers to keep him alive before Frank races him to a nearby hospital to undergo life-saving surgery.

Some time later, Peter wakes from his coma. After a heart-to-heart — and some light banter — with an apologetic and remorseful Frank, Peter checks himself out of the hospital.

A crowd of dedicated Spider-Man fans, who've congregated outside the hospital to hold a vigil for his swift recovery, awaits him. Fortunately, Frank stays behind, dons the Spider-Man mask, and waves to the assembled crowd from Spidey's hospital room, allowing a profoundly moved Peter to walk away without anyone knowing he's the real wallcrawler.

Does Jean Grey make M.J. and Ned remember Peter Parker in Spider-Man 4?

M.J. and Ned remember Peter Parker without Jean Grey's help (Image credit: Sony Pictures/Marvel Entertainment)

No — she doesn't need to, because the pair end up finding out that Peter is Spider-Man.

M.J. learns who he is when she discovers the note Peter had written back in 2021's Spider-Man: No Way Home. Meanwhile, Ned appears to remember Peter when the duo performs their secret handshake in Brand New Day's final scene. Ultimately, then, Jean's possible intervention wasn't necessary.

Which Marvel characters make a cameo in Spider-Man: Brand New Day?

Does Charlie Cox's Matt Murdock appear in Spider-Man 4? (Image credit: Marvel Television/Disney+)

We already knew the vast majority of Spider-Man: Brand Day's cast heading into the film, but the MCU's latest movie has a couple of surprises up its sleeve.

For one, Florence Pugh's Yelena Belova makes an unexpected yet scene-stealing cameo. Spider-Man meets her at a New York bathhouse to obtain information about the attack on the DoDC in the film's first act. Later on, she appears once more when the eponymous hero starts to suspect Metzger isn't all that he seems and seeks details on Jean's sister Sarah.

The other big cameo is Marisa Tomei's Aunt May. Peter's surrogate mom, who died in No Way Home, appears by way of the memory I mentioned earlier in this article.

"But what about Daredevil?", you might be asking. Given what happened in the final episode of Daredevil: Born Again season 2, some fans had expected Spidey to come across Charlie Cox's Matt Murdock and join forces to take on The Hand in Spider-Man 4's prison-set action sequence. Unfortunately, Cox doesn't show up in Brand New Day, so the wait for a Daredevil and Spider-Man MCU team-up goes on.

Is there an end-credits scene in Spider-Man: Brand New Day?

Brand New Day's post-credits scene shows Spidey has swung off into the cosmos (Image credit: Sony Pictures/Marvel Entertainment)

Yes. Right at the end of the film's final credits, the Spidey Tracker — an app built by Ned Leeds to, well, track Spider-Man's whereabouts — flashes up on the screen.

As an automated message that says "Location unknown" starts to play over and over, the app zooms out from planet Earth and eventually pinpoints that the webslinger is somehow in space.

What does this mean? I have a wild theory that Spider-Man: Brand New Day's post-credits scene might not mean what we think it does, but the most likely scenario is that Peter Parker has been transported somewhere due to events that'll go down in Avengers: Doomsday or Avengers: Secret Wars. Speaking of which...

How does Spider-Man 4 set up Avengers: Doomsday and/or Avengers: Secret Wars?

Avengers: Doomsday will be released in theaters worldwide on December 18, 2026 (Image credit: Marvel Studios/Andy Park)

In short: I don't know. Spider-Man 4's end credits scene could be related to either of the aforementioned movies, so until Avengers: Doomsday is released this December, your guess is as good as mine.

That said, at this moment in time, Tom Holland isn't slated to appear in Doomsday, and that film is already packed with enough characters as it is. You can find out who'll appear and more by finding out everything we know so far about Avengers: Doomsday.

If Holland doesn't show up in Avengers 5, he'll be a dead cert to star in its sequel. Marvel and Sony won't miss the opportunity to put one of their most bankable characters in at least one of the next two Avengers movies, so the smart money is on him having a substantial role to play in Avengers 6. For more on that flick, find out what we know so far about Avengers: Secret Wars.

How does Spider-Man: Brand New Day set up Marvel's new X-Men movie?

A new generation of Marvel's popular mutant superteam will join the MCU in due course (Image credit: 20th Century Fox)

It doesn't. With Doomsday and Secret Wars set to be the next two MCU movies to hit theaters, that pair is far more likely to impact the MCU's first mutant-based film.

Nevertheless, Spider-Man 4's final minutes do show Jean Grey traveling on a bus to an unknown location. Maybe she's attempting to track down more of her fellow mutants? If she is and she's successful, it's possible that whoever she locates will not only have roles to play in Secret Wars, but also form a prototype version of the X-Men ahead of their actual founding/formation in their first dedicated MCU adventure.

While we wait for more news on one of the few confirmed post-Multiverse Saga projects, find out what we know so far about Marvel's new X-Men movie.

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