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For many small and medium-sized businesses, cybersecurity conversations center on endpoints like laptops, servers and cloud platforms.

Yet one category of device continues to sit quietly outside that focus: the printer.

Despite being deeply embedded in day-to-day operations and handling highly sensitive information, print infrastructure is still widely overlooked.

This lack of scrutiny is part of a broader challenge. New research shows 73% of UK SMBs fear data privacy issues in their current document management processes, highlighting widespread concern about how sensitive information is handled across both digital and physical workflows.

Yet 55% of UK SMBs consider printers a low priority in their cybersecurity strategy.

This worrying disconnect between the critical data printers handle and their low security prioritization creates a vulnerability that attackers can exploit to access sensitive workflows, intercept documents or move laterally within a network.

A growing blind spot in hybrid working environments

As we know, work no longer sits neatly inside the office. It happens across home networks, personal devices and shared spaces – environments that SMBs struggle to monitor or control. Today, print and scan workflows routinely handle sensitive data, from payroll and contracts to customer records.

Without visibility into who is printing what and where, organizations have no way of protecting that sensitive data. And it doesn’t take much – just one misdirected scan or a print job left in a tray can expose confidential information, often without any obvious sign that something is wrong.

According to Quocirca, 74% of SMBs have experienced a print-related data loss incident in the past year. A further 33% say documents printed on employee-owned home printers are now a top factor in data loss.

Behavioral factors further amplify the problem. Research shows 47% of UK SMBs believe that employees try to bypass their organization's print security guidelines. At the same time, 63% assume their printers are secure because they sit behind a firewall, and half do not consider them a security threat at all.

Together, these trends point to a clear security gap: while print workflows are handling increasingly sensitive data across distributed environments, they are not being secured, monitored or governed to the same standard as other endpoints.

Real risk in outdated hardware

Almost three-quarters (73%) of UK SMBs frequently worry about the risk posed by their outdated systems. Older printers running unpatched firmware and default credentials quietly process and store sensitive data while remaining unmanaged.

A compromised printer can serve as an entry point into wider business systems. If laptops and servers require active monitoring, printers do too.

Concerns are not limited to hardware. They also span cybersecurity exposures linked to connected printers, vulnerabilities introduced as scanned documents move through the cloud, and the risk of unauthorized access to print queues.

Alongside this are more visible, day-to-day issues, such as confidential documents being left unattended and the difficulty of tracking information once it exists in physical form.

These risks can be managed, but only if SMBs treat print and scan as part of the security perimeter.

Without this, resilience across hybrid workflows becomes guesswork. The future of work is not only about cloud and AI; it is also about securing the everyday document processes that move sensitive data across physical and digital environments.

Building control through visibility and smarter printing

Despite low prioritization, almost six-in-ten (63%) SMBs in the UK acknowledge print security needs improvement. To secure the future of work, organizations need secure print hardware foundations and protection that keeps pace with evolving threats.

Smart printing builds on these secure hardware foundations by embedding visibility, policy enforcement and audit trails directly into print and scan workflows.

Of UK SMBs that have adopted smart printing, 89% say it provides clearer visibility into printing and scanning activity across users and locations, 86% say it helps them meet compliance and security standards, and 85% say it improves enforcement of rules and restrictions.

Rethinking the role of print in cybersecurity

As we delve deeper into the future of work, printers need to be brought into the wider security strategy. A data breach originating from a printer can be just as damaging as one involving a compromised device or network, with the potential for significant financial loss, regulatory penalties and reputational harm.

Printers are not just office equipment. They are part of the digital infrastructure that supports modern work. As print and scan workflows become more digital and cloud-connected, printers deserve the same security attention as any other endpoint.

In practice, that means SMBs need three things: secure hardware as a foundation, security that keeps pace with new threats, and the visibility and control to maintain resilience at scale. Bringing printers into the security strategy is a practical step towards protecting sensitive data in a world where both work and risk are distributed.

We've reviewed and rated the best all-in-one printers.

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

Duck.ai is one of the only AI chat platforms where you can hold a conversation with GPT-5 or Claude Opus without registering an account. Launched by DuckDuckGo in early 2025, it sits inside the company's existing search and browser ecosystem. You can access it at duck.ai, through the DuckDuckGo browser, or via desktop browser extensions.

Two things set it apart from other AI chat tools. Every conversation goes through DuckDuckGo's anonymizing proxy before reaching the model provider, stripping out identifying information. Providers such as OpenAI and Anthropic are also contractually prohibited from using those chats for training purposes, which is a meaningful commitment that most direct-to-model platforms don't offer.

At TechRadar Pro, we've been reviewing business software since 2012. Our AI coverage includes an AI tools roundup and a 2026 vibe coding buying guide, among other platform reviews and news features.

What is Duck.ai?

Duck.ai is DuckDuckGo's AI chat service, designed so that you can talk to leading AI models without creating an account or sharing personal data. It's available at duck.ai, through DuckDuckGo's browser extensions, and inside the DuckDuckGo app on iOS and Android.

The service routes all conversations through a privacy proxy. Your prompts are anonymized before they reach the AI provider. DuckDuckGo also holds providers to strict contractual limits on data use, meaning chats are not stored on DuckDuckGo's servers and cannot be used for model training by either party.

It works for typical AI tasks: drafting emails, summarizing documents, answering questions, writing code, and general chat. Privacy-conscious professionals, freelancers, and anyone who wants frontier AI access without a recurring account will find it useful.

Duck.ai: At a glance

Attribute

Notes

Underlying model(s)

Free: Claude 4.5 Haiku, GPT-4o mini, GPT-5 mini, gpt-oss-120b, Llama 4 Scout, Mistral Small 3 24B. Plus: GPT-4o, GPT-5.4, Claude Sonnet 4.6, Llama 4 Maverick. Pro: adds Claude Opus 4.7.

Best for

Privacy-conscious users; general AI chat tasks; no-signup AI access

Distinguishing functions

Privacy proxy routing, no-login access, multi-model switching, voice chat

UI features

Minimal chat interface with left sidebar for model switching; chat history stored locally on device

Subscription costs

Free; Plus: $9.99/month or $99.99/year; Pro: $19.99/month or $199.99/year

API pricing

No public API — consumer product only

Buy it if…

• You want AI chat without an account. Duck.ai is one of few platforms giving you access to capable models, including GPT-5 mini, without registration or a credit card.
• Privacy matters to your workflow. DuckDuckGo anonymizes every chat through its proxy and holds AI providers to strict data-use agreements, making it a stronger privacy choice than signing up directly with OpenAI or Anthropic.
• You want multi-model value. The Plus plan at $9.99/month pairs GPT-5.4 and Claude Sonnet 4.6 with a full VPN and identity protection, making it genuinely competitive.

Don't buy it if…

• You need a developer API. Duck.ai has no API. If you're building products or automations on top of AI models, go directly to OpenAI or Anthropic.
• You already have a VPN. The paid plans bundle AI with VPN and identity services. There's no AI-only subscription tier, so you may end up paying for things you don't need.
• You depend on predictable limits. DuckDuckGo doesn't publish exact daily message limits, which makes it difficult to plan for high-volume or time-sensitive work.

My time with Duck.ai

I tested Duck.ai across the free and Pro tiers over several weeks. On the free tier, the experience is clean and fast with no friction, no sign-up, and six models ready to go. Switching between GPT-4o mini and Claude 4.5 Haiku is a single click. Both handled research queries and writing tasks without issue.

The Pro tier adds Claude Opus 4.7 with extended reasoning. The improvement shows on complex tasks: I ran the same multi-step analytical prompt across the free and Pro tiers. Opus 4.7 returned a more structured and well-reasoned response. For everyday writing or quick lookups, the free tier is more than enough. Pro earns its keep on specialist, multi-step work.

My one persistent frustration was the opacity around usage limits. DuckDuckGo's policy is to keep limits vague to prevent abuse. During testing I didn't hit a ceiling on Pro, but I can imagine high-volume users running into walls without much warning.

Duck.ai: Features

The defining feature is the privacy proxy. Every message goes through DuckDuckGo before reaching the AI provider. The company holds providers to contractual restrictions on data use, which matters most if you're typing sensitive information into an AI: prompts about financial decisions, health issues, or confidential business matters are much less exposed than they would be via a direct provider account.

The free tier's model roster is unusually strong for a no-login service. Alongside GPT-4o mini and Claude 4.5 Haiku, you also get GPT-5 mini and OpenAI's gpt-oss-120b, both capable models that would cost real money through direct API access. Meta's Llama 4 Scout and Mistral Small 3 24B round out the lineup for users who prefer open-weight options.

Paid subscribers get meaningfully stronger models. The Plus plan adds GPT-5.4 and Claude Sonnet 4.6, which excel at long-context tasks and following detailed instructions. The Pro plan goes further with Claude Opus 4.7 and extended reasoning, suited to the kind of multi-step analysis that trips up smaller models.

Voice chat, launched in February 2026, lets you speak to an AI model through an encrypted relay connection. Audio is not stored by DuckDuckGo or OpenAI after the session ends, keeping the privacy principles consistent. The feature currently uses OpenAI as the model provider, so model choice for voice is limited.

File uploads are not yet supported, which is a gap compared to ChatGPT or Claude.ai. If you need to analyze a PDF or document, you'll need to paste content manually. DuckDuckGo has indicated uploads are on the roadmap.

Duck.ai: User experience

The interface is intentionally minimal. There's no dashboard, no settings maze, and no onboarding flow. The left sidebar shows your chat history, stored locally on your device rather than on DuckDuckGo's servers. You switch models by clicking the current model name at the top of the conversation. New users can start a chat in seconds.

AI features are also fully optional. DuckDuckGo lets you hide Duck.ai buttons and AI overlays in search settings, which is a meaningful gesture from a company that treats privacy as more than a marketing position. The option to disable AI without losing other features is something many platforms don't offer.

Duck.ai: Customer support

DuckDuckGo maintains detailed help documentation at its Help Pages site, covering Duck.ai's privacy policies, model availability, usage limits, and subscription management. The documentation is well-organized and answers most common questions without requiring you to contact anyone.

There's no live chat or phone support channel. For subscription or billing issues, you can reach support through the subscription settings menu, but response times aren't publicized. Businesses planning to rely on the Pro plan for critical work should factor this in when evaluating the service.

(Image credit: DuckDuckGo)Duck.ai: Pricing

• Free: Six models, no sign-up, with unspecified daily usage limits.
• Plus: $9.99/month or $99.99/year, which adds GPT-4o, GPT-5.4, Claude Sonnet 4.6, and Llama 4 Maverick, plus VPN, Personal Information Removal, and Identity Theft Restoration.
• Pro: $19.99/month or $199.99/year, which adds Claude Opus 4.7, extended reasoning, and 2x usage limits versus Plus.

The free tier is one of the best no-login AI offers available right now. Getting GPT-5 mini and Claude 4.5 Haiku at zero cost, with genuine privacy protections, is a hard proposition to dismiss. The Plus plan at $9.99/month undercuts both ChatGPT Plus and Claude Pro (each $20/month) while providing access to frontier models alongside a bundled VPN.

The Pro plan at $19.99/month is harder to recommend to most users. Claude Opus 4.7 with extended reasoning is a premium experience, but only for tasks that genuinely require deep multi-step analysis. There's no standalone AI-only option, so if you already pay for a VPN elsewhere, you're likely paying twice. The subscription is available internationally with localized pricing: UK users pay £9.99/£19.99 per month for Plus/Pro respectively, and most EU countries are priced at EUR 9.99/19.99 per month.

Duck.ai: Alternatives you should consider

• ChatGPT: OpenAI's direct interface costs $20/month for Plus and offers GPT-4o access alongside file uploads and image generation, two features Duck.ai currently lacks. The downside is that ChatGPT requires an account and uses conversation data for service improvements unless you opt out.
• Claude.ai: Anthropic's own interface gives you Claude Opus at $20/month on the Pro plan and is stronger for deep reasoning work. It requires registration, doesn't offer multi-model switching, and has weaker privacy protections than Duck.ai's proxy approach.
• Perplexity AI: A strong alternative if you want AI answers grounded in real-time web search. Perplexity Pro costs $20/month and supports file uploads, though it doesn't match Duck.ai on privacy routing.

How I tested Duck.ai

• Ran identical prompts covering research queries, email drafting, and complex analytical tasks across the free, Plus, and Pro model tiers to compare quality and speed.
• Reviewed DuckDuckGo's published privacy documentation, provider contracts policy, and help pages to assess how well its privacy proxy claims hold up.
• Tested the subscription sign-up, model switching, voice chat, and local history access on both desktop and mobile across several sessions.

Response latency on the free tier is slightly higher than a direct ChatGPT session, consistent with traffic being routed through a proxy. The difference was small enough that it wasn't noticeable mid-conversation. Pro-tier responses were fast regardless of model choice, with Claude Opus 4.7 taking marginally longer on extended reasoning tasks — which is expected given the additional processing involved.

• Lidl confirms cyberattack at third-party IT service provider that exposed customer data including names, phone numbers, emails, dates of birth, and customer numbers
• Passwords, payment details, and addresses were not affected, but the company warns of phishing risks and urges vigilance against identity fraud attempts
• Incident was contained quickly, reported to authorities, and investigated by forensic experts; Lidl operates ~12,900 stores across 32 countries

Lidl is warning its customers of a cyberattack which may have affected some of their personal information stored with the company.

In a data breach notification published on its Netherlands, Belgium, and Germany websites, the German discount supermarket chain said an IT security incident at one of its IT service providers affected some of the data stored by Lidl Online Shop customers.

“We were informed of this incident at the beginning of the week,” a machine-translated notification reads. “Despite high IT security standards, unknown persons briefly gained access to a separately stored file with customer data and part of the data was stolen from it. The system of the online shop itself is not affected.”

Unknown impact

Lidl said that the unnamed miscreants walked away with people’s full names, phone numbers, email addresses, dates of birth, and customer numbers. Passwords, billing and delivery addresses, bank details, and other payment information, was allegedly not stolen. Customer accounts remained unaffected, as well.

However, the company is urging its customers to remain vigilant, since there is a high chance the crooks will use the data to send personalized phishing emails.

“Although we currently have no concrete evidence of misuse of data, we warn you about possible phishing attempts or identity fraud as a precaution,” Lidl said.

The company did not say which IT service provider was targeted, or how many people are affected. It merely stated that the company “responded immediately” and “took necessary steps” to restore the full security of the affected systems. The company also filed a report with the relevant authorities, and called in IT forensic experts to investigate the incident.

Local authorities, such as the Dutch Data Protection Authority, or the Belgian “competent supervisory authority for data protection” were notified, as well.

Lidl operates around 12,900 stores across 32 countries in Europe and the United States.

Via Cybernews

IDC projects that AI infrastructure costs at Global 1000 companies will run 30% higher than current budgets by 2027. That gap shows a mismatch between how AI workloads behave in production and how enterprise IT has historically planned for capacity.

The pattern repeats across industries. A pilot project validates an AI model on a controlled dataset, and budgets are created around those economics. When the system moves into production, the bill often outpaces what anyone originally modeled.

The natural instinct is to blame the size of the model or the cost of using tokens, but that’s not where the money goes. The cost lives in the data layer, driven by how often the system reads, how many services it touches, and how continuously those operations run.

What pilots don’t show you

A pilot runs against a narrow dataset, with a handful of concurrent users, on a request-response cadence familiar to anyone who has shipped a web application. Production looks nothing like that.

Consider a generative AI customer support agent in production. A single user prompt can trigger simultaneous lookups across session activity, CRM records, inventory systems, retrieved manuals, and other sources before the model produces a response. All of this happens under sub-100ms latency budgets, with the slowest lookup gating the rest. The operational problem becomes tail latency across many small parallel lookups.

Now layer agentic workflows on top. A user request decomposes into a plan, then into a series of steps that each issue their own lookups, write intermediate state, and read it back. What starts as one inference expands into tens or hundreds of data accesses, with the system holding session and memory state across the entire arc. The cost profile that emerges is nothing like what the pilot priced.

Where the 30% comes from

The overrun comes from a series of defensive choices made under uncertainty. When teams can’t see how data flows through a single request, they over-provision to absorb spikes. When they can’t predict cache behavior under shifting context, they duplicate data across systems to reduce dependency risk.

When one downstream service slows down, they layer another service on top to insulate against it. Each choice is locally rational. The aggregate is a system that costs 30% more than the workload requires, and that’s before anyone adds a new use case.

The underlying problems are usually the same. Fan-out per request goes unmeasured end-to-end. Context gets fragmented across feature stores, session stores, user profile systems, vector indexes, and third-party APIs. KV cache and prefix reuse get left on the table because the inference layer can’t hold or share state across calls.

Replication and tiering decisions get made per system rather than per access pattern. None of these show up in a pilot. All of them show up in the production bill.

What the AI data tier has to deliver

AI in production is a continuous, distributed system whose hot path is context assembly — many small reads per request under tight latency budgets — combined with writes that must keep multiple representations of the same entity consistent.

These systems need two things at the same time: predictable low-latency reads under high concurrency and consistent writes across the data path. The infrastructure underneath has to be sized and shaped accordingly.

A few architectural decisions end up driving most of the outcome:

Match the data tier to the access pattern Session state, agent memory, feature lookups, retrieved context, and KV cache reuse all have different read patterns, freshness requirements, and durability needs.

Treating them as different data tiers — or laying them on whatever database happens to be in the stack — is the most common source of overrun. The session store and the system of record have different access pattern demands from the same data tier.

Engineer for fan-out and predictable tail latency Throughput is the wrong primary metric for an AI data tier. The right one is the predictability of many small reads triggered by one request. A batch of parallel lookups is only as fast as its slowest member, and a single slow lookup stalls the entire context-assembly step.

Storage systems optimized for write throughput pay a read amplification penalty under this access pattern. Systems that keep the primary index in memory and resolve point lookups in a single I/O behave differently at the tail.

Treat write consistency as a correctness requirement When updates across user profiles, embeddings, feature vectors, and session state aren’t synchronized, downstream context assembly reads a mix of versions and the model produces confident output grounded in contradictory data.

These are hallucinations that have nothing to do with sampling or model probability, and they don’t yield to better prompts or bigger models.

Treat inference-time data reuse as infrastructure. KV cache reuse, prefix sharing, and agent memory persistence are first-class infrastructure concerns. Teams that figure this out early run the same workloads at lower GPU utilization than teams that haven’t. This is the largest leverage point that doesn’t appear in most AI cost models.

Where to start

The most useful first step is to trace a single production request end-to-end — counting lookups, logging sources, and measuring tail latencies. That exercise reveals more than any architectural review. Once teams can see how data moves through one interaction, they can categorize data accesses by tier and verify that each is running on infrastructure suited to its pattern.

From there, the next question is what’s being recomputed that could be reused, particularly across inference calls and agentic steps. Fan-out per interaction should become a metric teams watch as closely as p99 latency — because at scale, it drives cost just as directly.

AI cost in production is a design discipline. Teams that address it early have far more control over performance and spend than teams that wait until the bill forces the issue. In many cases, the 30% gap is the cost of learning these lessons too late.

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DeepSeek landed like a thunderclap in January 2025, when its R1 reasoning model briefly dethroned ChatGPT as the most downloaded free app on the iOS App Store in the United States. Built by a Hangzhou-based AI lab backed by Chinese hedge fund High-Flyer, it claimed to match frontier AI performance at a fraction of the development cost. That claim sent Nvidia's stock tumbling 17% in a single session and sparked a global conversation about who was actually winning the AI race.

Since then, DeepSeek has grown to roughly 97 million monthly active users and released multiple model generations, most recently the V4 family in April 2026. Its API pricing stands out: the V4 Flash model starts at $0.14 per million input tokens, cheaper than most "lite" tier models from OpenAI and Google yet competitive on coding, math, and reasoning benchmarks. The open-weight licensing under MIT also means teams can self-host the models and sidestep per-token costs entirely at scale.

We've been reviewing B2B software at TechRadar Pro since 2012, with AI platforms among our most active coverage areas in recent years. Our AI tools roundup, vibe coding guide for 2026, and explainers on OpenClaw and Moltbook give you a sense of the tools we track. DeepSeek is one of the more polarizing platforms we've tested: impressive in many ways, but not without significant red flags.

What is DeepSeek?

DeepSeek is an AI chat platform and API service developed by Hangzhou DeepSeek Artificial Intelligence Co., Ltd., a Chinese company founded in 2023 and funded by the quant hedge fund High-Flyer. It offers a free web and mobile chat interface at chat.deepseek.com alongside a paid developer API, both powered by the same underlying model family.

The platform runs on DeepSeek's own large language models, specifically V4 Flash and V4 Pro, both using a Mixture-of-Experts (MoE) architecture. Only a subset of each model's parameters activates per token, which keeps inference costs low without shrinking the model's overall knowledge base.

V4 Pro has 1.6 trillion total parameters but only 49 billion active at inference. V4 Flash runs 284 billion total with 13 billion active, making it significantly faster and cheaper without sacrificing much on everyday tasks.

Developers, researchers, and cost-conscious businesses are the natural audience. The free chat tier suits individuals and small teams exploring the tool, while the API's aggressive pricing makes it attractive for anyone building AI-powered applications at scale.

DeepSeek: At a glance

Attribute

Notes

Underlying model(s)

DeepSeek V4 Flash (284B total / 13B active params) and V4 Pro (1.6T total / 49B active params), both MoE-based

Best for

Coding assistance, mathematical reasoning, document analysis, budget API use

Distinguishing functions

1M token context, thinking/non-thinking modes, prompt caching, open weights (MIT)

UI features

Web chat and iOS/Android apps with web search toggle, file upload (PDF, DOCX, TXT), Expert Mode and Instant Mode

Subscription costs

Free (chat app, unlimited queries); no paid chat subscription tiers

API pricing

Pay-per-token; new accounts receive 5M free tokens valid 30 days; V4 Flash at $0.14 / $0.28 per 1M tokens (input/output); V4 Pro at $1.74 / $3.48 standard, with promotional discounts available

Buy it if…

• You need a cheap, capable coding or reasoning API. V4 Flash at $0.14 per million input tokens is among the most affordable frontier-adjacent APIs available, and its benchmark results on coding and math hold up well against more expensive competitors.
• You want open weights for self-hosted deployment. Both V4 models are released under MIT license on Hugging Face, giving teams the option to run the model on their own infrastructure and eliminate per-token costs entirely for high-volume workloads.
• You're doing non-sensitive exploratory work. For individual researchers, students, or developers prototyping non-confidential projects, the free chat app offers web search, file uploads, and a 1M token context window at zero cost.

Don't buy it if…

• Your work involves confidential or regulated data. All user data is stored on servers in mainland China, subject to Chinese law, which permits government access without user consent. Multiple governments have banned DeepSeek from official devices for exactly this reason.
• You need consistent responses on sensitive topics. DeepSeek avoids certain politically sensitive subjects, particularly around Chinese domestic affairs. That content filtering can produce evasive or incomplete outputs on topics that other platforms handle straightforwardly.
• You're in a GDPR-regulated region. Italy's data protection authority blocked DeepSeek outright in January 2025 after the company provided what regulators called a "completely insufficient" response to data practice inquiries.

My time with DeepSeek

I tested DeepSeek's chat app and API across a range of tasks: code generation, document summarization, long-form reasoning, and general Q&A. On raw capability, the V4 models impressed me. Code outputs were clean and well-structured, long document summaries were accurate, and the one-million-token context window handled full-length PDF ingestion without complaint.

The thinking mode, accessible via Expert Mode in the chat UI, added visible chain-of-thought reasoning that proved useful for multi-step problems rather than theatrical.

What gave me pause was everything outside the model itself. Certain politically sensitive prompts returned conspicuously vague or deflective answers — the kind of behavior that wouldn't be acceptable in a professional context where consistent and complete information matters. I also found that the chat interface lacks the memory and personalization features you'd find in ChatGPT or Claude.

Value for money on the API side is difficult to argue with. A production app with well-structured prompts benefits substantially from the caching discount: cached input tokens cost just $0.014 per million for V4 Flash, a 90% reduction. For high-volume, low-sensitivity workloads, that arithmetic is compelling.

DeepSeek: Features

DeepSeek's core chat feature set covers the bases you'd expect: text generation, code writing and debugging, document summarization, mathematical reasoning, and web search. The web search integration is a manual toggle rather than always-on, which keeps responses faster by default but requires you to switch it on when real-time information matters. File uploads support PDF, DOCX, and TXT formats, with the model able to summarize and answer questions based on the uploaded content.

The standout capability is the 1M token context window introduced with V4, up from 128K in the previous generation. That's a meaningful jump for anyone analyzing long contracts, codebases, or research documents in a single session. Most competitors at comparable price points max out at 128K to 200K tokens.

V4 Flash covers both thinking and non-thinking modes, so you don't need to switch between separate models depending on task complexity. Non-thinking handles fast general responses; thinking adds structured multi-step reasoning for harder problems. That flexibility matters more than it sounds when you're toggling between casual tasks and complex analysis in the same workflow.

Where DeepSeek falls short is multimodal support. The platform does not currently support image generation or image understanding in the web app, putting it behind ChatGPT, Claude, and Gemini on that front. Agentic capabilities are available in the V4 Preview but remain early-stage compared to dedicated agentic platforms.

DeepSeek: User experience

The chat interface at chat.deepseek.com is straightforward and fast to get started with. Signing up requires only an email address from a global provider like Gmail or Yahoo, and the default experience drops you straight into a conversation window. The distinction between Expert Mode (thinking-enabled, slower) and Instant Mode (faster, non-thinking) is surfaced clearly at the top of the interface, and mobile apps on iOS and Android mirror the web experience with file upload and web search included.

The learning curve is shallow for casual use. Switching between thinking and non-thinking modes takes one click, and the file upload workflow is drag-and-drop simple.

The API experience is less forgiving for first-time integrators. Unlike the chat app, the API is stateless, meaning every call must include the full conversation history in the messages array. DeepSeek's documentation covers this clearly, but it catches developers accustomed to managed conversation state elsewhere off guard.

DeepSeek: Customer support

Support options for free chat users are limited to a Discord community server and an email channel for API service inquiries (api-service@deepseek.com). Community responses on Discord can be prompt, but they depend on other users rather than official staff. There is no live chat or phone support.

API customers have slightly more recourse through direct email support, though response times vary. The official documentation at api-docs.deepseek.com is thorough and well-organized, covering model details, pricing, rate limits, and code examples in both Python and curl. For developers comfortable with self-service documentation, it's adequate.

(Image credit: DeepSeek)DeepSeek: Pricing

• Chat app is free with no query limits. The web and mobile apps give you unlimited access to V4 Flash and V4 Pro at no cost, including web search, file uploads, and the full context window.
• New API accounts receive 5M free tokens, valid for 30 days, giving developers a zero-cost window to prototype and test.
• API billing is pay-as-you-go. V4 Flash costs $0.14 per million input tokens and $0.28 per million output tokens. V4 Pro runs $1.74 and $3.48 respectively at standard rates, with promotional discounts periodically dropping those to $0.435 and $0.87. Cached input tokens cost one-tenth of the standard input rate on both models.

The free chat tier is generous by any measure. Unlimited queries with a 1M context window puts it ahead of most free-tier competitors in raw access terms, and there's no paid chat subscription to worry about. Power users who need more control either stick with the free app or pay per token via the API.

On the API side, DeepSeek makes a strong case for developers managing costs at scale. Off-peak pricing discounts of up to 75% are available during 16:30–00:30 UTC, giving teams with flexible scheduling another cost lever. For production apps with well-structured prompts sharing a common system context, effective input costs can drop well below $0.02 per million tokens with caching applied.

DeepSeek: alternatives you should consider

• ChatGPT (OpenAI): The most capable all-around AI platform, with image understanding, voice, and memory. API pricing is higher, but US-based data residency and enterprise data agreements make it a safer choice for sensitive business workloads.
• Claude (Anthropic): Particularly strong for long-form writing and document analysis, with comparable context windows and clearer data handling policies. Claude Pro starts at $20/month for individual users.
• Gemini (Google): Tightly integrated with Google Workspace and built for multimodal work across text, image, and video. Gemini 2.5 Flash offers competitive API pricing with no Chinese data jurisdiction concerns.

How I tested DeepSeek

• Used the free web app for code generation, document summarization, mathematical reasoning, multi-turn Q&A, and file analysis, covering both Instant Mode and Expert Mode across each task type.
• Ran API calls across varying prompt sizes to verify context window behavior, caching discounts, and response consistency, following DeepSeek's own temperature guidance for different task types.
• Cross-referenced DeepSeek's official privacy policy, third-party security research from NowSecure and SecurityScorecard, and regulatory actions from Italy, Australia, South Korea, and US government bodies to build a complete picture of the data risk profile.

Beyond hands-on testing, I reviewed DeepSeek's official API documentation, the V4 technical report published on Hugging Face, and benchmark data from the April 2026 release. Pricing figures were sourced directly from the official DeepSeek API documentation and corroborated against third-party tracking services.

• Microsoft produced 20.3 million tons of CO2e emissions last year, up from 16.2 million tons
• Of the 37.5 million MWh of energy used, only 422,000 MWh came from unsustainable sources
• A rise in diesel/crude oil consumption and Scope 2 emissions are key drivers

In its latest sustainability report, Microsoft has admitted its greenhouse gas emissions actually rose 25.1% year-over-year from 16.2 million tons to 20.3 million tons in 2025.

With the company targeting a 2030 carbon negative deadline, rising emissions presents a major challenge that it must overcome, however current trends point to emissions continue to rise even further.

Microsoft said its rapid expansion of AI and cloud data centers as a key driver for rising emissions, and with more projects in the pipeline, this could be an ongoing challenge for years to come.

Microsoft's emissions are moving in the wrong direction

The company also noted its decision to stop buying short-term renewable energy certificates that do not directly support additional clean capacity. While the previous year's 16.2-million-ton figure was lower than last year's, it was largely offset by carbon credits and doesn't accurately represent the true emissions.

More broadly, Scope 2 and Scope 3 emissions are also under pressure from the continued data center expansion, due to electricity purchases, unsustainable construction materials and compute hardware. For example, Scope 2 emissions went from accounting for 1.6% of total emissions in FY24 to a staggering 13.3% in FY25.

As for fossil fuel use, the company saw a 51% rise in diesel and crude oil consumption despite reductions in natural gas (-6.5%), propane/LPG/jet fuel (-10%) and gasoline (-16%) use. Still, of the nearly 37.5 million MWh of energy the company used in FY25, only around 422,000 MWh came from non-renewable sources (per a separate data sheet).

However, despite expansion-related challenges, Microsoft did make significant progress to reducing overall emissions, hitting around 20 million tons last year instead of the 34 million tones it could have hit without work on carbon-free electricity, sustainable fuels, energy efficiency improvements and other supple chain refinements.

Microsoft isn't the only company battling the impacts of AI – Amazon also recently noted a 16% annual increase in emissions, while also blaming AI and data centers. Google also saw a 25% rise in emissions for its most recent full year.

IBM’s launch of its AI coding assistant “Bob” points to a much bigger shift in enterprise modernization. Across the industry, AI tools are being positioned as a way to make legacy systems easier to understand, assess and eventually modernize. And there is real value there.

Some of these tools can read thousands of lines of legacy code, identify deprecated APIs, summarize business logic and surface technical debt in minutes. For organizations carrying decades of operational history, that kind of visibility is a big step forward - but let’s not confuse visibility with modernization.

Understanding how a system works is necessary. It is not sufficient. I have seen teams produce clean dependency maps, detailed code summaries and impressive technical assessments, only to realize the hardest part starts after the AI has finished scanning the code.

Legacy estates rarely sit neatly off to the side. They are woven into the operating model of the business. They reflect years of process decisions, integration choices, compliance requirements, customer-specific exceptions and institutional knowledge that is often scattered, tribal or barely documented. Lovely little treasure hunt, except the treasure is risk

An AI model may identify an ageing integration point or highlight an application that supports a critical business process. That is helpful. But the real challenge begins when teams realize how many other systems, workflows and operational teams are connected to what looked like a straightforward change.

In many large organizations, legacy systems are still in place for a very simple reason: they work. They continue to perform reliably under demanding conditions, even if parts of the surrounding environment have evolved, degraded or become harder to support over time.

That is why modernization is not just a technology exercise. It is a sequencing exercise. It is a risk exercise. And, done properly, it is a business decision.

The multi-layer challenge

Every technical decision inside a legacy estate has consequences somewhere else. A change to one application can affect recovery procedures, audit requirements, licensing agreements, batch schedules, integration layers or support processes that have been stable for years.

This is where many modernization programs stall. Teams underestimate how interconnected these environments have become. AI can accelerate the technical assessment, but its real value comes when those insights are connected to the operational and commercial context around the system.

That distinction matters. Enterprises are moving away from broad “replace everything” strategies and becoming more selective. Not every legacy platform needs to be ripped out. Some systems need restructuring. Some need better interfaces. Some need to be moved. And some, frankly, should be left exactly where they are because they are doing their job reliably at scale.

Workload placement has become much more nuanced. Moving a service to public cloud may improve scalability and speed up software delivery, but it can also introduce data sovereignty concerns, latency issues, cost variability or new support dependencies.

At the same time, keeping workloads on modernized IBM Z or Power environments may provide more predictable performance for applications that already run effectively at scale.

The real question is not, “How do we get everything off legacy platforms?” The better questions are, “Which systems genuinely benefit from relocation, which need to be modernized in place, and which can be extended through modern interfaces?”

Without that context, organizations can spend a lot of money moving systems around without actually fixing the underlying problem. Congratulations, you now have the same complexity in a newer location.

We are already seeing this play out in enterprise environments where legacy platforms still sit at the center of high-volume operations. In one recent assessment, AI coding assistants were used to analyze more than six million lines of RPG code running on IBM Power systems, processing roughly 30 million requests a day.

The work surfaced technical debt and concentrated areas of complexity in weeks, giving the organization a clearer basis for deciding what to modernize, where to start and how to sequence change without disrupting core operations.

That is the practical value of AI in modernization: not magic, but better visibility, faster assessment and smarter prioritization.

Why enterprise AI deployments are becoming more specific

This broader shift is also showing up in how hyperscalers talk about enterprise AI adoption. Microsoft CEO Satya Nadella has described the market as moving from “discovery” into “widespread diffusion.” In plain English, the challenge is no longer just building impressive models.

It is embedding AI into real workflows, real operations and real business systems at scale. That is much closer to how modernization actually works inside large enterprises.

The same shift is happening with AI models themselves. The industry still loves to talk about scale, but most enterprise teams are not sitting around hoping for a trillion-parameter model to save them. They need tools that help engineers solve very specific problems inside environments that are already complicated enough.

In many cases, smaller, specialized models are proving more useful because they can be deployed in controlled ways, focused on specific tasks, and governed more tightly.

That governance point matters. Bringing AI into infrastructure operations raises very practical questions: What data can the model access? What systems can it touch? Can it recommend changes? Can it execute them? Who approves movement toward production?

That is another reason task-specific models are gaining traction. Teams can define exactly what the model is allowed to do, where human approval is required and how changes move through existing controls. In enterprise environments, that kind of control is not bureaucracy. It is how you avoid turning a productivity tool into tomorrow morning’s outage bridge.

Where AI is delivering practical value today

The organizations getting real value from AI are usually not the ones making the loudest claims about it. They are applying AI to engineering and infrastructure work that already consumes huge amounts of time: investigating incidents, mapping dependencies, validating changes, supporting regression testing and understanding how complex systems actually behave.

A lot of that work comes down to giving engineers better visibility and helping them get to root cause faster.

AI models can help connect runtime anomalies to recent code changes. They can reduce the time teams spend manually tracing incidents across hybrid environments. They can support regression testing around older applications and surface integration dependencies that were previously difficult to visualize across multiple infrastructure layers.

That becomes especially important in environments where cloud-native services sit alongside long-established mainframe and midrange systems. In many organizations, the hardest problems show up in the seams between those environments, particularly when different teams manage different parts of the estate with different tools, different metrics and different operating rhythms.

That is why the most useful AI deployments tend to focus on practical engineering work, not grand attempts to automate everything at once.

Organizations are seeing value in areas that are repetitive, complex and difficult to scale manually. Automated test generation can reduce regression risk around legacy applications. AI-supported observability correlation can shorten incident investigation cycles. Dependency analysis can help teams prioritize infrastructure work that removes bottlenecks affecting service delivery.

In most cases, AI is not replacing engineering judgment. It is improving the work engineering and infrastructure teams already understand well. And that is where the expectations need to be clear.

AI can absolutely speed up discovery. Work that once took weeks of manual assessment can now happen much faster. But that is usually the point where the real work starts.

A model can tell you how systems connect. It cannot tell you how much disruption the business is prepared to absorb. It cannot decide which customer commitments matter most. It cannot magically unwind 25 years of operational dependency while everyone politely keeps breathing.

Technology leaders should view AI coding assistants as decision-support tools for broader infrastructure and modernization strategies, not as stand-alone solutions to legacy complexity.

IBM’s Bob announcement shows how quickly these capabilities are advancing, especially when it comes to understanding legacy code and helping teams work through large, complex estates. But visibility only matters if organizations can turn it into practical change without creating instability elsewhere.

AI can help you read the legacy estate. It can help you understand the risk. It can help you move faster. But modernization still requires judgment, sequencing and operational discipline.

That part is still very human.

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• The Nvidia Shield TV (2019) is out of stock pretty much everywhere
• Nvidia says it's down to consumer demand for the streaming device
• It's not yet clear if we'll ever get more stock or a replacement gadget

While there hasn't been any new Nvidia Shield TV hardware for seven years now, the streaming devices continue to be popular — but it looks as though it could finally be the end of the road for the cheapest base model in the series.

As spotted by Android Authority, this $149 / £129 / AU$289.95 model is now out of stock via Nvidia's official channels, and Nvidia has stopped short of promising that those stock levels will be replenished anytime soon.

In a statement to Android Authority, Nvidia said the Shield TV was out of stock "due to demand", and that there was nothing to say "regarding future availability at this time" — so make of that what you will.

Nvidia also took the opportunity to highlight that all Shield TV models continue to get software updates and continue to be supported by Nvidia, even though it's now more than a decade since the first of these gadgets went on sale.

More to come?

The latest Nvidia Shield TV launched in 2019 (Image credit: Future)

Both the base model Shield TV and the more premium Shield TV Pro were given a refresh in 2019, and Nvidia says the Pro version is still on sale. Whether or not Nvidia is planning to let the stock run down on that model too remains to be seen.

I've had several Shield TVs down the years, and have always been impressed with the hardware and the software on offer. They support a wide variety of apps and games, come with local storage, and can be customized in a variety of ways too.

Even something like the recently launched Google TV Streamer only just about catches up to everything that's possible with the Shield TV boxes — and that's saying something considering Nvidia's devices made their debut in 2015.

Nvidia execs are on the record as saying they're open to the idea of new Shield TV hardware in the future, so hopefully this clearing out of stock will be followed by a brand new model in the not too distant future.

The PC gaming landscape has changed dramatically in the last handful of years. We've seen the slow and steady move away from native (purely rasterized) performance and onto the crutch of AI-powered upscaling technology. Whether Nvidia DLSS, Intel XeSS, or FSR 4, Multi-Frame Generation, or "fake frames", have become a core part of the experience.

It doesn't really matter how powerful the best graphics cards are anymore, as AI-powered upscaling has shifted the playable performance expectations across the board. We see this as standard in the system requirements for today's demanding PC games; it's a huge asterisk that developers use to claim otherwise unheard of FPS in intensive software.

Are the likes of Nvidia DLSS, Intel XeSS, and AMD FSR just a failsafe to make up for poor software optimization? That's part of the story, sure, but it's far more nuanced than that. As computing components become more expensive, and AI muscles its way into the territory in a more aggressive manner, the two, which used to go hand in hand, have now become inherently parasitic in a wanton race to the bottom if things are not course-corrected. Here's what AI-powered upscaling means for the future of PC gaming.

Nvidia DLSS 5 is the first symptom of a wider issue

I've been a champion of DLSS for many years, primarily for how it can boost weaker graphics cards to give users playable framerates. It's an ever-evolving AI-powered tech that's continuing to improve and deepen. Some of its best features include Ray Reconstruction, which makes Path Tracing more viable, Frame Generation/MFG, and DLAA for smoother anti-aliasing. When used as an assist to your hardware, it can be the difference between smooth and stuttering, but DLSS 5 is where things simply went too far.

Instead of being a supporting tool, as with DLSS 4.5's Dynamic MFG, the only thing people can take away from DLSS 5 is how AI is actively impacting image quality, and not for good reasons. Described as a "breakthrough in visual fidelity for games", and said to bridge the "cinematic gap", this upcoming AI model uses an algorithm to re-color and overlay motion vectors.

DLSS 5's showcase of results is troubling to say the least. At best, it slightly improves the lighting in EA FC, and at worst, it completely overwrites the distinct visual art style of PC games like Starfield, Resident Evil Requiem, and Hogwarts Legacy. Sure, the lighting is a little better, but it comes at the cost of a flat and artificial-looking brightness of the entire scene, making everything (ironically) look far more lifeless and void of personality.

Nvidia tends to be the frontrunner that AMD and Intel later catch up to. With the DLSS 5 release date still unconfirmed, but claimed to be coming in the autumn of 2026, we (likely) won't see the full ramifications of this on the wider gaming industry until next year, but when this glorified AI-filter drops, it's likely to become an ingrained option in many flagship titles. There's a reason why Team Green started by showing off some of the largest games from the most well-known publishers and developers in the business; if you enforce it at the top, the rest will follow for fear of being left behind.

The frightening reality of how expensive new graphics cards could be

Nvidia's next generation of graphics cards will have AI at the forefront, and they will not come cheap (Image credit: Future)

It's no exaggeration to say that 2026 is one of the worst times on record to build a custom gaming PC. DDR4 and DDR5 RAM prices have skyrocketed due to the global supply of memory modules being drained en masse to build data centers, and the less said about what's happened to flash memory found in the best SSDs, the better. While these individual components doubling in price overnight is already troubling, there are even worse consequences for graphics cards, made all the more infuriating by the fact that it's a self-destructive cycle with (seemingly) no end in sight.

Graphics cards rely on VRAM to have enough bandwidth to perform properly. For Nvidia's current-generation RTX 50 series, that's the superfast, denser GDDR7, whereas AMD and Intel are still using the slower, older GDDR6 standard. As memory modules are becoming scarcer, it massively drives up the price for core components, such as the Samsung, Micron, and SK hynix memory modules needed to build the video cards in the first place.

Put simply, graphics cards will become more expensive because manufacturers are too busy building data centers with the components, meaning the end consumer ends up paying considerably more. We've already seen countless examples of this, such as the Steam Machine's overpriced nature, the Steam Deck's price increase, and even how it's made the PS5 and Xbox Series X more expensive six years in than at launch.

We've seen prices of graphics cards increase massively since the semiconductor shortage, which plagued the RTX 30 series launch. You paid more, you got less, and now the manufacturers know they can overcharge you. In a computing landscape where components can shoot up anywhere from 20 to 50% overnight, it puts the reinforced focus on DLSS, XeSS, and FSR as a necessity rather than an optional helping hand.

The future of AI-powered upscaling is a necessity

The Steam Machine relies on AMD FSR to hit Machine Verified status (1080p at 30 FPS) (Image credit: Valve)

While we're heading towards more expensive graphics cards that rely on AI upscaling tech just to keep up, we can also look at what the future of DLSS, XeSS, and FSR will need to do to keep up. We've already established that DLSS 5 made a contentious call with its AI art filter, but what about real-world, practical uses in 2027 and beyond?

Intel XeSS 3 launched with Multi-Frame Generation, which was rolled out to both its Alchemist and Battlemage graphics cards, even bringing true MFG to handhelds like the MSI Claw 8 EX AI+ and Acer Predator Atlas 8. To look positively at AI-upscaling tech in this regard, its major benefit will be to make handheld gaming PCs, such as a Steam Deck or Lenovo Legion Go S successor, more competitive.

The most recent update to AMD's AI-powered upscaling tech, FSR 4 Redstone, still trails behind DLSS 4.5, which means Team Red will need to strike back with FSR 5 to have a chance at dethroning Nvidia while it is down. AMD's image quality is far better than it used to be, even though its frame pacing leaves a lot to be desired. Based on the track record, from what I've seen from Intel and AMD, XeSS and FSR look to continue to iterate on the core fundamental technologies, whereas Nvidia is looking to do its own thing in counter to what was expected.

The future of AI upscaling tech becomes two-fold. Ideally, enabling any of these settings should be as normal and natural as turning on TAA (temporal anti-aliasing) and forgetting about it. It's easy to forget that there was a time when such a setting was contentious, and now it's almost universally used across the board. It's a similar story to when Nvidia's PhysX SDK was pushed so heavily, as it's now a default setting that's enabled within game engines as standard.

So, AI-powered upscaling is best when it's not noticeable. If you're playing a game and you're noticing smooth performance and a high average FPS, then it's doing its job properly. Problems only really arise when that tech tries to overtake the core experience rather than in support of it, and chiefly as a symptom of a wider problem that we're still experiencing. AI-trained algorithms need data servers; we're making more of those, which means taking away the resources to build graphics cards, meaning you'll pay more for them when the Nvidia RTX 60 series, Intel Celestial, and AMD RDNA 5 eventually roll out.

Will native performance ever be relevant again?

I mentioned above about the asterisk of estimated performance when a game's benchmarks and recommended system requirements go live. Oftentimes, these developer/publisher-approved tables promise 30-60 FPS as standard, and try to discreetly hide that DLSS, FSR, and XeSS are needed to hit that cap. It's something that Valve is just as guilty of with its somewhat questionable claims of 4K60, which was walked back when using FSR.

When the biggest and most well-known entity in PC gaming makes a move like this, the gaming world takes notice, particularly with who Valve was targeting in the first place. If FSR is essential for playable framerates, then it becomes non-negotiable; a forced standard, an excuse for developers to rush out unoptimized games, which have plagued countless PC ports over the last five years.

We find ourselves at a crossroads then. AI-powered upscaling does just as much harm as it does good; it is simultaneously the answer to (and cause of) a fair amount of the problems we're currently experiencing as PC gamers, as the benefits and cons constantly battle out for pole position. It looks as though AMD and Intel are on the right track, even if Nvidia is pacing its own trail, one that (hopefully) isn't followed by its competition. If we're already expected to pay four figures for a "mid-range" GPU, let us hope that it can perform decently enough.

I almost can't write too much of an intro because I'll cry, but Nick (Kit Connor) and Charlie's (Joe Locke) beautiful love story is about to come to a close in Heartstopper Forever.

Since 2022, Heartstopper has captivated the hearts of Netflix subscribers, faithfully adapting the graphic novel series by Alice Oseman of the same name. In fact, if this is all too much for you, you can literally relive the ending again — Oseman has just published its sixth installment.

Frankly, I think Heartstopper will really live up to its "forever" subtitle. But when does Heartstopper Forever arrive on Netflix?

What time can I watch Heartstopper Forever on Netflix?

Heartstopper Forever drops on Netflix on July 17, 2026.

As for exact time, it should be the standard 12am PT release that we saw across seasons 1-3.

For global regions, here's when you need to be prepared:

• US – 12am PT / 3am ET
• Canada – 12am PT / 3am ET
• UK – 8am BST
• India – 12:30pm IST
• Singapore – 3pm SGT
• Australia – 6pm AEST
• New Zealand – 8pm NZDT

When do new episodes of Heartstopper Forever come out?

(Image credit: Netflix)

Heartstopper Forever isn't actually season 4... it's a feature-length film.

According to the streamer, it's clocking in with a runtime of 114 minutes, so that basically the equivalent of 4.5 episodes.

Sadly, this will be it for the show's run on Netflix.

Marshall Stanmore IV review

If you want to invite a speaker that looks as good as it sounds into your living room, then the new Marshall Stanmore IV could be a great pick for you. It aims to deliver everything its predecessor did, but better, with a broader soundstage, enhanced bass, and superior controls.

And as someone who owns (and loves) the previous model in this line, best believe I was expecting big things from the Stanmore IV. Luckily, it delivered, offering up impressive sound, a solid set of features, and an eye-catching design. But is it worth its relatively premium price tag? Here’s what I think after many hours of testing.

But before we decide whether the Marshall Stanmore IV can sit alongside the very best Bluetooth speakers, let’s take a look under the hood. This thing essentially uses the same setup as its sibling, the Marshall Acton IV, but crucially with a larger woofer. That means you’re getting a single 5-inch sub with 60W of amplification alongside two 0.75-inch tweeters with 25W of amplification. The result? Big, commanding, and engrossing sound.

I started by firing up Are You Gonna Go My Way by Lenny Kravitz, and the Stanmore IV handled it masterfully. Wailing electric guitars had excellent tonal accuracy and cut through with clarity; vocals also sounded driven and emotive.

Moving over to a deeper track, like Vision of Love by Lewis Taylor, and the Stanmore IV continued to impress. Deep bass pumping through the track hit with tremendous impact while remaining regimented and clean. But thumping low-end never came at the expense of sounds elsewhere in the frequency range. High-pitched drums sounded expressive and vibrant, while vocals in the mid-range were granted plenty of room to play in. Bass can even reach down to 38Hz, meaning you get brilliant, low extension — even sub-bass comes through with vigor and confidence.

LDAC is also on board now for higher-res Bluetooth listening, which helped to illuminate breathy vocal details in Black Eye by Allie X. And even though I’d argue the speaker has a more energetic sound signature, with a lot of focus on the hard-hitting low end, it still supplies a detailed, nuanced listen.

One of the limitations of the Stanmore IV’s little sibling, the Acton IV was its stereo playback. Although it whipped up a decent impression of stereo sound, its small size made it a little difficult to create the most meaningful sense of separation. But the larger, wider build of the Stanmore IV takes things up a notch, and in Jimi Hendrix's Foxey Lady I picked up on a stronger sense of separation, with lead guitar brilliantly placed on the right.

And, more generally speaking, the Stanmore IV whips up a broad, engrossing soundstage. Marshall has improved the tweeters and waveguides on this model to help disperse sound more evenly and provide room-filling sound. However the extra width has been achieved, it certainly gets the nod from me.

Marshall’s Dynamic Loudness tech also ensured that tracks maintained admirable clarity, even at higher volumes. Of course, you can still expect a bit of compression at 100%, say, but I was impressed with the speaker’s control in the upper echelons of loudness. The Stanmore IV is even better in this regard than the smaller Acton IV — perhaps thanks to its larger woofer and larger cabinet size.

Overall, the Stanmore IV provides powerful, driven, and exciting sound, with commendable depth and expression. It's bullish and confident, but still takes time to smell the flowers — and its wider soundstage and refined bass even helps it surpass its already impressive predecessor.

(Image credit: Future)

But now it’s time to move on from sound and look at a few of the features you can enjoy on the Stanmore IV. If you’ve already seen my Marshall Acton IV review, then you’ll get the gist of what’s on board. The Stanmore IV uses the newer Marshall app, enabling you to save three EQ calibrations (using a five-band equalizer), and you can use the M button to cycle between these if you like. The app also opens up placement compensation, enabling you to optimize the speaker’s audio output depending on its positioning, and there’s an option to change the brightness of the LED indicators.

Like the Stanmore III, there’s also RCA and 3.5mm connectivity, allowing you to hook up a turntable, or connect the speaker up to an AUX cable.

Something I wish the Stanmore IV did have is Wi-Fi connectivity. Not only does Wi-Fi provide the highest quality wireless listening experience, but it also prevents pesky sounds from your device — like phone calls and notifications — blasting from the speaker. What’s more, this is a home speaker, so it could easily have a stable connection to your home network at all times.

Marshall has multi-room covered with Auracast tech, which enables a bunch of its speakers to pair together, but I would’ve loved to have seen Wi-Fi onboard for the most seamless, quality-focused listening experience.

Another thing the Stanmore IV leaves out is voice assistant capabilities. Unlike models such as the Sonos Era 100 or Bose Lifestyle Ultra, there’s no smart voice control onboard. Although this is a function that I personally don’t tend to use on speakers, I know that some may wish for it on a model designed primarily for home use.

But something that’s sure to be a hit with most is the Stanmore IV’s design. This thing is an absolute beauty, and although it looks very similar to its predecessor, I’d argue that there’s no need to fix something that’s not broken. The new Stanmore stuns with a gorgeous faux leather exterior, beautiful speaker grille, and luxurious golden detailing. It looks like a true statement piece, and an item that will complement any living space (while still producing excellent audio).

As was the case on the Acton IV, buttons and control knobs are also perfectly responsive and pleasing to use, and there are also onboard EQ controls for altering bass and treble levels if you want to make some changes in a pinch.

So, now we come to the big question. Is the Marshall Stanmore IV worth the money? Well, it’s not the cheapest speaker around, with a price tag of $399.99 / £349.99 / AU$679, making it $100 / £90 / AU$180 more than the Acton IV. On the surface, that may seem like a significant jump for a speaker that’s almost identical — bar a larger cabinet and slightly larger woofer. But these seemingly small changes actually make a significant difference, in my view.

It maintains tighter control at the highest volumes, and also produces the seismic sound that Marshall has become associated with. And that’s not to do the Acton down — it’s just to say that I think you get your money’s worth when stepping up to the Stanmore. I’d also say that the Stanmore competes well against rivals in its price category, with a lower price tag yet more might than a rival like the Denon Home 400. I’d also argue it produces a more striking sound than a model like the Sonos Roam 2 — though you do miss out on Wi-Fi and a few smart features.

Overall, the Marshall Stanmore IV is a great speaker that produces energetic, impactful sound, alongside a stunning look and nifty companion app. Yes, I would’ve loved to have seen Wi-Fi on board, but with LDAC for higher-res Bluetooth streaming added into the mix, I’d still happily recommend this musical maestro from Marshall.

(Image credit: Future)Marshall Stanmore IV review: price & release date

• $399.99 / £349.99 / AU$679
• First released July 2026

The Marshall Stanmore IV was released in July 2026, around four years after its predecessor hit the shelves. This newer model launched alongside the Marshall Acton IV, which is — in essence — a smaller version of the Stanmore. This model comes in at $399.99 / £349.99 (AU$580).

Marshall Stanmore IV review: specs

Weight

8.8lbs / 4kg

Dimensions

13.8 x 8 x 7.3 inches / 350 x 203 x 185mm

Connectivity

Bluetooth 5.3, 3.5mm, RCA

Speaker drivers

1 x 5-inch 60W woofer / 2 x 0.75-inch 25W tweeters

Waterproofing

Not stated

(Image credit: Future)Should I buy the Marshall Stanmore IV?

Attribute

Notes

Score

Features

Multi-room with Auracast, new app works well, LDAC brought in, but lack of Wi-Fi is a shame.

4/5

Performance

Impactful yet detailed audio with tremendous depth, control, and power.

5/5

Design

Very similar to predecessor, but gorgeous amp-inspired aesthetic is massively appealing.

4.5/5

Value

It’s pricey, but stacks up well against competition.

4/5

Buy it if…

You’re focused on getting amazing sound quality
I have to say, the Stanmore IV surprised me by just how good it sounded — even though I already loved its predecessor. Bass is phenomenally powerful yet regimented, mids are driven yet layered, and treble is vibrant yet controlled. Throw in LDAC for higher-res listening and a decently wide soundstage, and you’ve got a great-sounding speaker.

You want a speaker that’s a statement piece
Although the Stanmore IV sounds great, it’s something else that truly helps it to stand out: its design. It maintains that gorgeous amp-inspired aesthetic that’s become synonymous with the Marshall brand, with enticing golden detailing, quality faux-leather casing, and the brand’s iconic logo front a center.

Don’t buy it if…

You’re looking for a portable speaker
When using the Stanmore IV, you’ll need to keep it hooked up to the mains. As a result, it’s better-suited to home use rather than being taken on the road. If you want a more portable option, I’d strongly recommend the Marshall Kilburn III, or awesome non-Marshall alternatives like the JBL Xtreme 5.

You want a smart speaker with Wi-Fi
The Stanmore IV is designed for the home, but it doesn’t have the smart features you’d expect from a rival like Sonos, say. For instance, it leaves out Wi-Fi connectivity (no AirPlay or Spotify connect), which is the most seamless and high-quality way to enjoy music wirelessly. It also leaves out voice assistant compatibility. If those features are important to you, I’d suggest checking out my alternatives below…

Marshall Stanmore IV review: also consider

Marshall Stanmore IV

Sonos Move 2

Klipsch The Three Plus

Price

$399.99 / £349.99 (AU$580)

$449 / £449 / AU$799

$399 / £379 / AU$529

Weight

8.8lbs / 4kg

6.6lbs / 3kg

10.6lbs / 4.8kg

Dimensions

13.8 x 8 x 7.3 inches / 350 x 203 x 185mm

6.3 x 9.5 x 5 inches / 160 x 241 x 127mm

7 x 14 x 8.4 inches / 178 x 355 x 213mm

Connectivity

Bluetooth 5.3, 3.5mm, RCA

Bluetooth 5.0, Wi-Fi, USB-C

Bluetooth 5.3, RCA, USB-C, digital optical

Speaker drivers

1 x 5-inch 60W woofer / 2 x 0.75-inch 25W tweeters

2 x angled tweeters, 1 x mid-woofer

2 x 57mm full-range drivers, 1 x 133mm subwoofer

Sonos Move 2
I’ve used the Sonos Move 2 plenty of times, and I absolutely love it. It plates up gorgeous, detailed audio, alongside seamless Wi-Fi streaming, multi-room capabilities, and convenient voice assistant functionality. It also has a 24-hour battery life, enabling you to take it on the go, and it looks incredibly stylish as well. You can’t ask for much more. Read our full Sonos Move 2 review.

Klipsch The Three Plus
Here’s another stylish speaker that seriously impressed us. Klipsch’s The Three Plus speaker offers assertive and intricate audio, fantastic build quality, and plenty of connectivity options. Read our full Klipsch The Three Plus review.

(Image credit: Future)How I tested the Marshall Stanmore IV

• Spent days testing the speaker
• Used at our dedicated music testing space at Future Labs
• Mainly streamed music over Tidal

I tested the Marshall Stanmore IV over the course of a few days, during which time I listened to hours worth of music and exhausted every feature the speaker had to offer.

Most of the time, I used the Stanmore IV in our dedicated music testing room at Future Labs, where I mainly streamed tunes via Tidal on my Xiaomi 17. To begin with, I sifted through the tracks in our TechRadar reference playlist — which features songs from a wide variety of genres — but I also bumped a bunch of tunes from my personal library.

More generally, I’ve spent years testing audio gear here at TechRadar. I’ve reviewed everything from premium wireless headphones like the Sony WH-1000XM6 through to Dolby Atmos soundbars such as the JBL Bar 1300MK2. I’ve also tested more than 50 Bluetooth speakers, including lots of Marshall models, including the Marshall Middleton II and Acton IV.

• Read TechRadar’s reviews guarantee
• First reviewed: July 2026

Generative AI has given rise to a new breed of business that can generate synthetic content, be it video or music, and Suno AI is among the biggest names in this category.

The startup's CEO, Mikey Shulman, however, landed himself in hot water when he made comments about the joy and fulfilment that musicians get from practising their craft.

Making music 'enjoyable' again

Shulman was speaking on the 20VC podcast in January 2025 when he remarked that making music isn't something that most people enjoy doing.

Quote of the day

This article is part of TechRadar Pro's QOTD project to provide an insight into the minds of the brightest and most recognized figures in the technology industry today and in years gone by. Read the full series here.

He framed his words in such a way that would suggest that his platform, Suno, cuts out a lot of these steps – largely centered around mastering the skills that you need – which would, in turn, lower the barrier to entry for those who aren't naturally gifted or have the time to 'get good' at making music.

In his words, he wanted to "[give] everybody the joys of creating music" which he deemed a huge departure from the status quo. His remarks, however, drew the ire of countless working within the music industry as well as regular people on social media.

Struggling artists

The threat of AI to the lives and livelihoods of those working in the music industry is very worrisome, according to research, with workers standing to lose 25% of their income over the next four years. It's no surprise, then, that Shulman's comments instigated such a fierce and violent backlash – forcing the CEO to row back and apologize a couple of months later.

His critics also suggested that the comments fundamentally misunderstood the nature of art and working in a medium such as music, where the hours of toil, practice and refinement are, in and of itself, part of what makes it such a fulfilling endeavor.

However, generative AI is still a new phenomenon and companies like Suno have only just entered the arena. Although the nature of the existential threat to the creative industries is clear, the specific economic impact on artists in the years to come remains unclear – especially in an uncertain landscape in which a strong backlash against AI art is brewing.

• Video showcases China's road-mobile electromagnetic catapult launching an aircraft for the first time
• The footage comes from a now-deleted social media post from the Beijing Institute of Technology's School of Mechanical Engineering
• Leverages China's existing EMALS tech by miniaturizing what it already uses on its aircraft carrier

China seems to have solved one of the biggest challenges modern drones face: deploying without a runway anywhere on the planet, thanks to a miniaturized version of the EMALS catapults found on its newest aircraft carrier.

A short video clip that surfaced towards the tail end of last month, from a social media post by the Beijing Institute of Technology's School of Mechanical Engineering, shows three eight-wheeled trucks linked together in a Lego-like fashion to form a runway that allows a propeller-driven drone to take flight.

The footage also shows all three trucks detached, coupling with each other, and exhibiting all-wheel steering that, in principle, enables them, if given enough space, to launch drones or small aircraft in any direction.

Replacing a runway in the modern battlefield?

China's move is not one that occurred in a vacuum: the United States was the first country in the world to deploy an Electromagnetic Aircraft Launch System (EMALS), sparking an arms race when it launched its first aircraft in 2017 aboard the USS Gerald R. Ford.

China followed suit with its own aircraft carrier, the Fujian, which sports three EMALS catapults to the US's four, possibly accounting for the Chinese carrier's smaller size relative to its principal naval rival's largest.

China has, however, beaten the US to the punch when it comes to demonstrating a portable EMALS, it seems, with its three-truck solution essentially marking a first for either country.

Chinese state-owned giants account for a significant share of the 70+ organizations directly involved in an impressive achievement that sets the stage for the next generation of drone-based combat.

Despite the video making its way across social media, it was taken down by the Beijing Institute of Technology's School of Mechanical Engineering, which originally posted it. The move, however, has not stopped defense forums and Chinese analysts from offering insights into what is clearly a major technological achievement for the country.

With France and India both committed to launching EMALS (albeit on future aircraft carriers for now), only two countries currently have the tech deployed on a ship, and only one of them has a land-based, portable option in play for now: China.

Big news for foldable phone fans this week. Reservations for the next generation of Galaxy Z Fold and Flip series phones have just arrived at the official Samsung Store ahead of the next Galaxy Unpacked keynote event.

The event will take place on July 22, 2026, at 9 a.m. ET / 6 a.m. PT / 2 p.m. BST, which means preorders are likely just a few weeks away. If you're interested in picking up a new device, then you'll find everything we know so far right here, including speculation on pricing and potential preorder deals.

While we're expecting the next generation of the Galaxy Z Fold and Galaxy Z Flip, Samsung has already suggested there's something more in store. In its first teaser for the event last week, the company said that "after seven generations of pushing the boundaries of foldables, Samsung is taking a different approach to how it builds anticipation this year."

That message, coupled with months of rumours about a wider foldable design, has sparked speculation that Samsung could finally be ready to introduce an entirely new type of foldable smartphone. With that said, details are still pretty scant as of writing, so take any speculation here as an educated prediction, rather than the gospel.

You can already reserve a device now

You can sign up to reserve the next Galaxy at Samsung directly at no cost and unlock $30 Samsung Credit towards the preorder of the next device and up to $1,230 off with an eligible device trade-in.

In the UK? Reserve your device right hereView Deal

How much will the devices cost?

Right now, we don't even know what these devices will be called, let alone official pricing, so any speculation here is an educated guess. The Galaxy Z Fold 7 and Flip 7 debuted at $1,999 / $1,299 respectively, so that's a rough ballpark of what to expect. Over in the UK, the last-gen devices debuted at £1,799 / £1,049.

I have a suspicion that Samsung might increase the price for this year's devices, however. RAM shortages and inflation are potential contributing factors here, and I think the brand could potentially increase the price anyway if the upgrades are big enough. If there's a new form factor, for example, I could see Samsung leaning heavily into that as a justification for a price increase.

How much can we expect to save?

(Image credit: Lance Ulanoff / Future)

• Trade-in rebates of up to $1,100 to $1,200
• Additional store credit at Samsung
• Major carriers matching discounts

Samsung itself has confirmed that there will be discounts of up to $1,230 with a trade-in rebate once preorders open. That will most likely cover both unlocked and carrier devices, so that gives you an idea of how premium these devices are likely to be.

Up until now, we've usually seen discounts of up to $1,100 on the latest Galaxy S26 and iPhone 17 series, so it looks like Samsung is being particularly aggressive with its discounts at launch.

Breaking that deal down, it could potentially resemble something like a trade-in rebate of up to $1,100, $100 of bonus credit to spend at Samsung (usually on accessories), and the $30 bonus for reserving a device. That's roughly in line with what the brand has offered over previous launches.

In terms of major carriers, you can definitely expect Verizon, T-Mobile, and AT&T to match those trade-in rebates on their sites. We could potentially see these major carriers waive the trade-in criteria altogether, but they usually only do this when you pair up the device with one of their super high-end plans. We're talking about plans that cost over $60 to $80 a month over a three-year duration, so they're usually pretty damn pricey in their own regard.

What about over in the UK?

You can already reserve a device if you're in the UK too, but annoyingly, Samsung hasn't confirmed any of the opening deals with its reservation page in this region. All we know is that you'll be able to get an extra £100 with your trade-in rebate, plus £30 in store credit if you reserve a device right now.

We've seen trade-in rebates of up to £700 with the Galaxy Z Fold 7 in recent months, so I suspect a rebate of anywhere between £650 and £850 is likely to be the maximum saving on the next-gen device when it arrives. Major networks like EE, Three, and O2 might have higher discounts than this, but those won't be for unlocked devices — you'll probably need a pretty substantial contract to get big savings.

Here at TechRadar, I test some of the best 4K Blu-rays each month as part of the Blu-ray Bounty. This is where we look at the latest 4K releases from that month and judge whether they’d be a worthy addition to your collection, focusing solely on the video and audio quality of each disc.

Every so often, a disc wows me so much that I add it to my rotation for testing the best TVs and best soundbars. 4K Blu-ray is my go-to source for AV testing, as it delivers a higher video bit rate, resulting in better picture quality than streaming, and uncompressed soundtracks for the best audio.

Some of the discs from the near-100 discs I’ve tested as part of the Blu-ray Bounty that have joined over the years include Wicked, The Mask, The Sound of Music and Dark City, to name just a few.

As part of the most recent June 2026 Blu-ray Bounty, there’s another disc that will definitely be joining the testing rotation, as it performs at a reference-quality level. And that disc is Speed Racer.

Breathtaking color

Speed Racer's bold red colors proved an interesting test for the Samsung S95H/S99H (left) and LG G6 (right) (Image credit: Warner Bros / Future )

My go-to 4K Blu-rays for color testing have been Wicked and The Sound of Music. Wicked features an oversaturated, candy-color style that really generates a lot of pop on the right screen, while The Sound of Music delivers still-vibrant but more authentic and realistic colors.

Speed Racer falls in Wicked’s camp, but takes it to another level. Throughout the movie, there are some seriously vivid colors. Red is a prominent feature throughout the movie, as it's the color of Speed Racer’s ‘M’ logo and the interior of his car, both of which are often front and center on screen. It’s also the color of the Racer garage at home and Papa Racer’s shirt, which he wears throughout the movie.

When I tested the Samsung S95H/S99H and LG G6 side-by-side, both TVs interpreted the red differently: the G6 gave it a much deeper red hue, while the S95H/S99H made it look paler, almost orange in some places. Both of these TVs, likely to be two of the best OLED TVs I’ll test in 2026, captured the visual punch of this red, but it was useful to see how each TV interpreted the color.

Both the S95H/S99H (left) and G6 (right) do a great job delivering the vibrant purples of Royalton Industries accurately. (Image credit: Warner Bros. / Future )

There are plenty of scenes where a single color dominates. As the Racer family arrived at Royalton Industries, there were a lot of bold purples, including the airship's color, the walls, and even the transport. On the OLEDs I tested the disc on, these purples had a beautiful richness to them that again was displayed in different ways by the S95H/S99H and the G6, with the latter again adding that bit more depth.

This trend continued throughout the movie, whether it was the neon greens of a grass field in a flashback, the fantastic pink/purple/orange gradients in the sky during sunset or the lush blues of the sky during daytime race sequences (or Speed’s iconic blue and white shirt.) Even the white of the Mach 5 / 6 and Speed’s helmet had a glorious clarity to them, really dazzling on the S95H/S99H and G6.

The use of color is fantastic in Speed Racer, and if you have a TV with Dolby Vision, you’ll be rewarded with the most breathtaking colors, some of the best I’ve ever seen on a 4K Blu-ray. But it’s not just color reproduction where this disc is useful.

A Dolby Atmos showcase

Speed Racer's races sequences are fantastic for sound testing, particularly Dolby Atmos (Image credit: Warner Bros. / Future)

When it comes to testing soundbars and TV audio, my go-to 4K Blu-rays have been The Batman, namely the Batmobile/Penguin car chase scene for its detail and bass, and Top Gun: Maverick, for its all-around expansive Dolby Atmos soundtrack.

Speed Racer has proved to be a far more compelling disc, audibly, than I ever thought. While I anticipated some hefty bass from the car’s engines, I didn’t anticipate the level of detail and sound mapping I would hear.

During the opening race, there are plenty of demonstrations of pinpoint accuracy as cars swerve wildly through the corners of the winding track. The sound of squealing tires demonstrates excellent directionality and is fully connected with the action on screen. As a car moves from side to side on screen, you can be sure to hear it in the front channels.

One moment in this scene, in particular, really grabbed my attention, though. As Speed makes his way around the track, he has to grind the rear axle of the Mach 5 against the edge of the track and as I was watching, I heard the sound of a grind come through crystal clear in the left rear speaker of the Samsung HW-Q990C soundbar I was using (an 11.1.4 channel Dolby Atmos system comprising of a soundbar, subwoofer and two rear speakers). This was the moment that made me realize just how precise and detailed the Dolby Atmos mix of this disc is.

Speed Racer's Dolby Atmos soundtrack is truly immersive and exceptionally detailed (Image credit: Warner Bros. / Future )

There’s good use of Atmos effects and height channels too. As Speed uses his spring-loaded chassis to jump over a rival racer, a cut to said rival’s cockpit reveals a burst of not only bass but also the sound of the wind from the Mach 5 as Speed flips over. This sounded immersive, clean, and incredibly precise. There are plenty of helicopter sequences too, which are great for showing what Atmos can do.

There were plenty of highlight moments throughout the movie, but it is the race sequences that showcase the clarity and depth of this Dolby Atmos soundtrack. But there’s one final area where this disc is a perfect testing disc.

Always in motion

Fast-paced race sequences are frequent throughout Speed Racer, and are a great 'stress test' for a TV (Image credit: Warner Bros / Future )

Motion handling is a key component of any TV. If a TV can’t accurately handle fast-moving images, then action movies and sports won’t look good. While motion interpolation settings, such as judder and blur reduction, can reduce these, they can introduce unwanted side effects, such as the ‘ghosting’ of a ball in a soccer game (where a trail of the ball appears as it travels across the screen).

I anticipate that Speed Racer is going to act as somewhat of a ‘torture test’ for some TVs (like The Batman can be due to its low brightness), as there are not only plenty of fast-paced driving sequences with plenty of quick shifts in direction, but one other real challenge: slow panning shots.

Frequently throughout the movie, commentators from various countries slowly track across the screen from side to side, and even on the S95H/S99H and G6, which have proven to have great motion handling with the right settings, these shots still struggled at times. The commentators sometimes showed judder as the TV’s tried to interpolate the motion, meaning this is something I’ll be using in future tests. With these panning shots, however, there is sometimes natural judder.

(Image credit: Warner Bros. / Future )

Again, though, it’s the fast-paced race sequences that can make or break a TV’s motion. Chaotic driving as cars swerve to avoid debris, smash into one another, or pull a tight turn can look unnatural if a TV’s motion isn’t right. Too much blur and judder reduction, and it’ll look artificial; not enough, and it’ll look like a juddery mess.

Speed Racer really is one of the best Dolby Vision and Dolby Atmos 4K Blu-rays I’ve ever tested and is a triple threat disc for color, motion and sound, so if you’re a regular reader of our TV and soundbar reviews and comparisons here at TechRadar, expect to see Speed Racer appear very soon.

• Samsung quietly prepares DRAM-free PCIe 4.0 SSD with flagship-level read performance
• Host Memory Buffer replaces dedicated DRAM inside Samsung's upcoming budget SSD
• Leaked specifications reveal 7,150 MB/s speeds from Samsung's mystery SSD

Samsung appears to be preparing a budget PCIe 4.0 NVMe SSD which removes the onboard DRAM cache found in traditional drive designs.

The unannounced model surfaced briefly on Samsung's website recently, before the listing was taken down without any official confirmation from the company.

Listed specifications describe a 1TB drive with sequential read speeds reaching 7,150 MB/s and write speeds reaching 6,450 MB/s.

How Samsung plans to compensate for missing DRAM

Traditional SSDs rely on dedicated DRAM to store the flash translation layer, letting the controller locate data across NAND flash quickly and efficiently.

However, as the global “RAMpocalypse” continues to worsen, even the largest vendors are looking for ways to reduce their dependence on DRAM.

Without that DRAM, drives can suffer higher latency and weaker performance during sustained workloads or heavy multitasking sessions.

To offset this gap, Samsung is using NVMe's Host Memory Buffer (HMB) feature, which reserves a small portion of system memory over PCI Express instead.

That borrowed memory holds mapping metadata rather than user files, connecting logical addresses to their physical NAND locations directly.

HMB generally cannot match the responsiveness of dedicated DRAM, though it improves performance compared to drives with no caching mechanism at all.

The drive carries a 400 TBW endurance rating, a modest figure for a 1TB SSD by current industry standards.

That number hints at Quad-Level Cell (QLC) NAND flash, which stores four bits per memory cell and lowers both cost and durability.

Samsung has not disclosed publicly which specific NAND flash technology sits inside this particular unannounced drive model.

Rising component costs are reshaping SSD design choices

Samsung's move comes as NAND flash and DRAM pricing continue climbing sharply across the broader global storage industry this year.

Removing the DRAM package cuts component costs directly, simplifies PCB design, and helps maintain competitive pricing within the mainstream SSD segment overall.

QLC NAND increases storage density and lowers manufacturing costs, though it trails Triple-Level Cell NAND in sustained write performance and long-term endurance ratings.

It also remains considerably less durable than older Multi-Level Cell (MLC) and Single-Level Cell (SLC) NAND technologies still found in some enterprise storage products.

Despite those trade-offs, the listed sequential speeds of 7,150 MB/s and 6,450 MB/s place the drive alongside many mainstream PCIe 4.0 SSDs with dedicated DRAM caches.

Samsung has not announced pricing, availability, the official product name, or the specific NAND technology used in the drive.

Until those details emerge, the leaked specifications point toward a lower-cost PCIe 4.0 SSD designed to balance competitive performance with reduced manufacturing costs as memory prices continue rising.

Via The Guru of 3D

If you love cinematic action games like The Last of Us, then there’s one upcoming release that should be on your radar. Summer Game Fest 2026 gave me the opportunity to go hands-on with Blood Message, which seems set to deliver a killer mix of gripping stealth, visceral melee combat, and intense set-piece moments.

Under the Radar

Under the Radar is our way of highlighting great games that might have passed you by. Through a regular mix of news stories and features, we'll cover great experiences that we feel haven't found the audience they deserve. Read the full series here.

Set in Ancient China, it follows a nameless hero and his son on an epic 1,000-mile journey through the scorching deserts of East Asia towards the historical city of Chang'an to deliver a vital message. The pair must survive against impossible odds, navigating vast sieges and escaping the clutches of relentless enemy forces.

An epic journey

(Image credit: NetEase Games)

Because this is the first single-player title by Naraka: Bladepoint developer 24 Entertainment, I had no idea what to expect when I sat down for my demo.

Showcasing an early segment of the game, the demo opens with our protagonist searching a house, desperate to recover an important letter as hostile soldiers comb through the surrounding town. The high production values are immediately apparent: everything here is rich in detail, with plenty of high-fidelity objects for you to pick up and pore over. The architectural style of the building around you is striking as well, with clay walls, sandy floors, and thatched reed roofs.

While Ancient China is certainly becoming a more common setting in games, I can’t think of the last time I saw its arid desert regions depicted. I’m desperate to explore more of its tantalizingly exotic environments and soak in the unique aesthetic.

Playing with a DualSense Wireless Controller, I also quickly appreciate how the movement feels very fluid and benefits from some impressive animation that, like The Last of Us Part 2, looks seriously cinematic and realistic without sacrificing responsiveness.

(Image credit: NetEase Games)

It’s not long until I find myself in combat against a group of foes, and it’s just as excellent. You have a heavy attack and a light attack, plus the ability to parry. This is by no means a unique formula, but the impeccably slick way that the protagonist interacts with the environment leads to some of the most gripping encounters that I’ve ever experienced. There’s a real meatiness in your swings, which realistically causes enemies to trip and stagger.

Attacking a foe next to a stacked wooden shelf will send them tumbling into it, knocking objects onto the floor and stunning them for a moment. Launch a heavy kick while your opponent is standing in front of a table, and they’ll be pushed right over it onto the floor, creating vital distance when you’re surrounded. Fail to deflect an incoming strike yourself, and you’ll often be forced onto your knees, tapping a button to pelt anything heavy that’s within arm’s reach to give you a few moments to escape.

Although my combat time was limited, I was still impressed by the variety of ways in which fights could unfold, particularly when there was an allied companion in the mix. There were definitely some moments that felt scripted, like when two enemies locked swords with me at the same time near the end of a brawl to trigger a climactic struggle. That’s not necessarily a bad thing, as it helps introduce unexpected and exciting moments.

(Image credit: NetEase Games)

I really enjoyed going in with my sword drawn, but most of the time, combat is entirely optional thanks to a robust stealth system. This is another area where Blood Message feels similar to The Last of Us Part 2, forcing you to scurry through long grass and crouch in cover to avoid patrols. Get behind one of your quarries undetected, and you can initiate a brutal takedown, though be warned that any wrong move risks thrusting you straight into open combat.

At certain points, getting seen is inevitable, triggering bombastic chase sequences that have you sprinting away from barrages of arrow fire, scrambling up ledges, and leaping over perilous gaps. The path you need to take always feels very intuitive, though there are a few little alternative routes sprinkled throughout if you want to experiment.

Everything I played could easily rival the output of a developer like Naughty Dog, and with Blood Message set to release on consoles and PC, this should be at the top of gamers’ wishlists.

Whether rain or shine, weekday or weekend, my morning starts with a scroll.

It’s one of my most enduring habits. I’ll start by checking the time, before allowing myself a few texts or emails in the name of ‘productivity’, and before long, I’m lying there watching people throwing bowling balls at TVs or reading ragebait in the comments section.

I’ve long suspected that this isn’t the optimal way to start the day, but it was only after a recent moment of mid-scroll lucidity that I began to wonder why I reach for my phone first thing in the morning.

As it happens, research on early-morning phone habits suggests that it’s not just me diving into social media as soon as the alarm goes off.

The Independent reports that 81% of Brits reach for their phone as soon as they wake up, while a 2025 YouGov report found that the majority of US adults under 30 often use their phone right before sleeping and right after waking up.

These figures could suggest that most of us shared a mental tendency to pick up the phone right after waking up, but without additional context, they can’t tell the whole story.

So, to find out more about why I and so many others scroll first thing in the morning, I spoke to two psychology experts to connect the dots between ancient human behaviour and the supercomputers we keep in our pockets, and indeed our beds.

Information vs stimulation

Social media offers much more information that we evolved to handle early in the morning (Image credit: Getty Images)

“To boil it down as simply as possible, it’s a combination of our natural dopamine reward system and the fact that we are communal people,” says psychotherapist and addiction specialist John Puls.

Puls tells me that long-standing psychological drivers are pushing us to use our devices in the mornings, where in the past we might’ve sought different kinds of connection

“We are pleasure-seeking people, and one of the ways we do that is through engagement with our smartphones, particularly social media,” he explains, “and we want to know what’s going on in the world.”

Puls continues: “Previously, in closer communities with less technology, it wouldn’t be uncommon to just spend some time with your neighbours or your family in the morning. In the absence of that, people are looking for immediate connection, and the easiest way to do that is through the smartphone. You have to take into account the changes that have come with the smartphone, but these are natural impulses that social media is fulfilling.”

For clinical psychologist Dr. Ari Lakritz, the smartphone and all the news it connects us to fulfil an evolutionary impulse to detect threats: “The brain is somewhat hardwired to look for pertinent information, especially the more threatening information. The part of the brain that deals with that is called the amygdala — it’s one of the most ancient parts of the brain, one that’s most responsible for the fear response.”

“News sites, with their slant towards negative news, are hacking into an inborn part of ourselves,” he adds, “and when you’re looking at your phone as the first thing you’re doing, it may not be all that different from one of our ancestors scanning the horizon for threats.”

People are looking for immediate connection, and the easiest way to do that is through the smartphone.

John Puls

“We develop very early on to be aware of possible threats to ourselves, and to scan the environment for those [threats],” Lakritz continues, adding that the availability of information that may not be relevant to phone and social platform users could be increasing stress levels: “The existence of something we feel is negative or threatening in a far off country has no direct relevance to us, but we do find ourselves psychologically pulled to that.”

“It’s really assaulting people with a great deal of information that is not directly relevant to them, and definitely doing more harm than good… there’s this whole other aspect of life, which is positive news and uplifting stories that people are either not drawn to or simply not sent as much.”

Social media algorithms are blackboxed — meaning users aren’t privy to the decisions and equations that decide the content they see. With that said, it’s generally accepted that algorithms are designed to maximize engagement of any kind, and, as The Conversation reports, anger spreads more quickly through social media networks than other emotions.

As John Puls notes, this has a physical effect as well as an emotional one: “When you immediately go into your smartphone [in the morning] and start doomscrolling, so to speak, you’re releasing cortisol, a stress hormone, and your brain is getting overstimulated.”

“We’re basically in the middle of a giant experiment,” Puls continues, “our brains were not necessarily meant to be this stimulated first thing in the morning and then consistently throughout the day. Where it becomes problematic is with the risk of overstimulation — there’s a risk of constant pleasure-seeking that dulls the senses.”

Effects of the morning scroll

(Image credit: Getty Images / Cristina Quicler)

According to Dr. Ari Lakritz, beginning the day with an intake of highly charged, negative information can have major effects on one’s mood and focus. He describes social media as “unlimited scrolling” of “dramatic news that can get our fight or flight response very worked up.”

“It’s really not good,” he explains, “and it very much sets the tone of one’s cognitive framing. It’s very fast, intense stimulation, whether that’s YouTube Shorts, TikTok style videos, or even just Reddit-style scrolling through very short, snappy comments or news stories.”

Lakritz continues: “If my baseline is very fast, short, intense bursts of entertainment, when confronted with something that takes more focus or deeper thinking it’ll be hard to move on from that set point.”

When asked whether early morning phone use is always problematic, Dr. Lakritz makes few exceptions: “Aside from more extreme circumstances, it’s hard to think of a good advantage one is getting with the phone right there that couldn’t be gotten in a non-technological way.”

John Puls tells me that he’s noticed that several of his clients experience discomfort when away from their phones for even short periods of time: “It almost becomes an emotional support phone — if anything happens in our life, an interpersonal problem, a problem with our relationship, we could experience that discomfort until we scroll on Instagram.”

And for young people, even higher stakes could influence phone use from dawn till dusk.

‘If they don’t exist online, they don’t exist socially’

For those born in the digital era, connection to social media can feel absolutely essential (Image credit: Getty Images)

It’s worth noting at this point that I interviewed John Puls and Dr. Ari Lakritz separately, and without either knowing of the other’s involvement in this article. With that said, both professionals agreed that early morning phone use has a tighter hold — and greater impact — on young people.

“The teens that I’m working with that struggle with this, I have them check their screen time, and on average it’s between 14 and 15 hours,” says Puls, “that’s the majority of time that they’re awake.”

“Naturally, what comes with that is being pretty disconnected from people in real life [...] so there’s this pressure to constantly be online. Teens want to psychologically individuate from their families and feel part of a community, particularly with their friends. So they often feel the pressure that they can’t be part of that unless they’re on their phones.”

“For younger people, they feel that if they don’t exist online, they don’t exist socially.”

Dr. Ari Lakritz says that phone use in general has a huge impact on young people’s psychological growth: “It touches child development in a profound way. It’s a huge compound for something like ADHD, and makes assessment of ADHD very complicated — you have to piece apart how much of this is inattention issues, or developmental, and how much is very, very high exposure to electronic entertainment.”

Taking back time

Apple's Screen Time feature helps you keep track of your device usage. (Image credit: Future / Thomas Deehan)

Olivia Yokubonis, known online as Olivia Unplugged, is a digital wellness strategist for Opal, one of the best-known screen time limiter apps. She tells me that she “meets people where they are” with a message of digital balance and wellbeing, sharing tips and tricks to a combined social media audience of 600,000 followers.

"I was an Opal user before I even started working here,” Yokubonis explains, “the goal is to help people stop feeling like they’re the victim of their phones, and actually feel like they’re in control again.”

“I’m not anti-technology, I’m pro agency,” she adds, “you have to focus on awareness. I’m a big advocate of the idea that we can’t change what we don’t notice. And the morning scroll is very often unconscious.”

A post shared by Olivia Unplugged (@olivia.unplugged.ig)

A photo posted by on

At the time of writing, Opal boasts more than a million daily users, and in 2026 announced that the app had saved its user base a total of 500 million hours — but Yokubonis’ strategies go further than just using the app: “Something I’ve implemented with my family is no-phone zones. The bedroom is one of those places — we put our phones in the other room, our alarms go off, and we have to get up and go get it.”

She adds: “Digital wellness means your attention is not constantly being fragmented, that you can think in complete thoughts and sentences, and that you don’t lose hours of your day, especially the first few hours of the day, without realising it [...] We need the ability to choose to go on a social media app rather than have it be a habit, or something that’s just automatically happening because my nervous system is reaching for something.”

“We have a finite amount of willpower, and these apps have an unlimited amount of resources. They are designed to use up that willpower.”

On a similar note, Dr Ari Lakritz explains that even a marginal reduction in screen time can make a big difference: “Check your screen time, add up how much you do per week, and try to cut it down by 10%. If it’s 60 hours a week, just cut off six, see what you can do. You don’t have to be a digital hermit to improve.”

Though high screen time correlates to higher revenues for many phone makers and mobile software developers, a rising tide of social media legislation and backlash against big tech could push some brands to recognise its problematic potential.

Indeed, some smartphone manufacturers are beginning to acknowledge the issue of excessive phone use, and are developing software-based features to help users curb their screen time.

Nothing, for instance, believes its Glyph Matrix and Essential Space features will ‘help you be more human’, while Google's upcoming Pause Point tool will redirect you away from social media apps towards more meaningful forms of smartphone engagement. Apple, too, recently announced a slew of wellbeing-focused upgrades for its Screen Time feature in iOS 27.

In the pre-AI era, buying a Windows laptop or Windows desktop used to be pretty simple.

You looked at the processor, checked how much RAM and storage it had, considered a few screen size options, and tried to work out whether the battery claim sounded even vaguely realistic.

Fast forward to 2026, however, and most PC spec sheets look much busier and lot more focused on AI.

Alongside the usual phalanx of numbers and brand names, you’ll now find labels such as AI PC, Copilot+ PC, Snapdragon X Elite or X2, AMD Ryzen AI, NPU, and TOPS, among many others.

Some of these terms are definitely useful and relatively easy to understand, others are easy to misread, and a few sound more important than they are.

The good news is that the fundamentals have not disappeared.

The best laptop still depends on your apps, workload, budget, and the parts of the machine you’ll notice every day, such as CPU speed, memory, battery life, screen quality, ports, and weight.

The newer AI specs can help, especially if you want the latest on-device Windows features, but they are only one part of the picture.

To help demystify the laptop buying process, let's take a look at how to read a laptop spec sheet in 2026 – from AI PC to TOPS – and what actually deserves your attention before you buy.

(Image credit: Microsoft)AI PC vs Copilot+ PC: what’s the difference?

“AI PC” is the broadest label on the spec sheet. In most cases, it means the laptop has some form of dedicated AI hardware, usually a neural processing unit, or NPU, built into the chip.

While AI PC can be a useful shorthand, especially if you’re comparing newer laptops against older models, it is still a flexible term; different manufacturers use it in slightly different ways.

“Copilot+ PC” is Microsoft’s own branding category for Windows laptops that meet a defined hardware standard.

In 2026, that means a compatible processor or system-on-chip with an NPU capable of at least 40 TOPS, 16GB of DDR5 or LPDDR5 RAM, and at least 256GB of SSD storage. (Basically, a powerful set of specs.)

A Copilot+ PC should be ready for Microsoft’s latest on-device AI features, like smarter search and Live Captions, but it does not automatically tell you whether the laptop has enough storage or enough graphics heft.

(Image credit: Microsoft)NPU and TOPS: the new numbers in town

The NPU is the new spec most likely to trip people up. Short for neural processing unit, it is a dedicated part of the chip designed to handle AI tasks more efficiently than the CPU alone.

TOPS is the number usually attached to the NPU, and it stands for "trillions of operations per second", giving you a rough sense of how much AI work an NPU can handle.

For a Copilot+ PC, the important number is 40 TOPS or higher. Once a laptop clears that bar, it should be able to run Microsoft’s current on-device AI features.

A higher TOPS number may help with some local AI features, especially as software catches up, but it does not tell you how fast the laptop will feel when you open a big Photoshop file or fill Chrome with tabs.

For most people, NPU performance is worth checking, but it shouldn't take precedence over the specs you’ll feel every day, like battery life or screen size.

(Image credit: Qualcomm)Snapdragon X, Intel Core Ultra, and AMD Ryzen AI explained

Processor (or CPU) names have quietly become one of the easiest parts of the spec sheet to misread.

Qualcomm’s Snapdragon X chips brought Windows on Arm laptops into the mainstream, focusing on battery life and thin-and-light designs, which had often been Apple's main advantage.

Newer Snapdragon X2 laptops push that further with more powerful NPUs and improved graphics, but the basic buying question remains the same: will your apps run properly on Arm?

For most everyday tools, the answer is now likely to be yes.

Browsers, Microsoft 365, video calls, media apps, and many creative tools either run natively or work well through Windows’ translation layer. The areas to check are usually more specific, like older Windows software or specialist work apps.

Intel Core Ultra and AMD Ryzen AI laptops take a more familiar x86 route, while still adding NPUs for newer AI features.

One thing to note: the exact model wording is important. A laptop with “Core Ultra” on the box is not automatically a Copilot+ PC, and the same goes for older Ryzen laptops without the right AI hardware.

(Image credit: Unsplash / Liam Briese)RAM still matters more than most AI labels

RAM is likely to be one of the specs most familiar to many Windows laptop buyers, and with good reason: it's still one of the clearest signs of how a laptop will feel in daily use.

For a mainstream laptop in 2026, 16GB should be treated as the baseline – especially if the machine is being sold as an AI PC or Copilot+ PC – giving you enough headroom for normal work, video calls, web apps, and so on.

Anyone buying for heavier work like photo editing or coding should look at 32GB if the budget allows. As the AI boom takes hold, though, RAM is getting extremely expensive, so make sure you do really need it.

One benefit of buying a laptop with more RAM is that, in general, it will make the laptop eel useful for longer, especially on machines where the RAM is soldered and cannot be upgraded later.

(Image credit: Getty / Deagreez)Storage: 256GB is the minimum in 2026

Storage is another spec where the minimum and the sensible choice are not the same thing. A Copilot+ PC only needs 256GB of storage to meet Microsoft’s hardware requirements, but that can start to feel tight in everyday use.

For most people, 512GB is the better starting point, and leaves more breathing room over the lifetime of the laptop.

A 1TB drive is worth considering if you work with large files or want more local storage for games, video, or AI tools. However, as mentioned in the RAM section, AI companies are rapidly driving up prices for higher-storage SSDs.

External drives and cloud storage can help, but they are not a complete substitute for having enough fast storage inside the laptop you use every day.

(Image credit: Future / John Loeffler)Battery life: look for real-world testing

Battery life is one of the biggest promises behind the latest AI PCs, especially newer Arm-based Windows laptops.

More efficient chips and dedicated NPUs can help away from the charger, but battery life is still one of the easiest specs to oversell. A claim such as “up to 20 hours” may be based on video playback or controlled test conditions, rather than a normal day of usage.

Reviews are much more useful here, and TechRadar puts every laptop through a series of real-world battery tests to really dig into the real endurance.

Look for tested battery life that reflects mixed use, rather than assuming the biggest number on the box will match your working day.

(Image credit: Getty / Deagreez)The boring specs still matter

While AI labels are useful, they obviously don't make the rest of the laptop disappear. The screen, keyboard, trackpad, ports, weight, heat, and fan noise will shape your experience far more often than a fancy Copilot+ badge.

The best way to read a laptop spec sheet in 2026 is to start with your own needs: enough RAM, enough storage, tested battery life, and a screen and keyboard you’ll be happy to use for hours at a time.

After that, the NPU and TOPS figure can help you understand how ready the machine is for newer on-device AI features.

Windows laptop spec sheets have not become meaningless, just easier to misread. The best laptop is still the one that gets the fundamentals right first, then uses its AI hardware to add something useful on top.

• Disney+ is reportedly mulling over a completely free tier with ads
• The cheapest tier already includes some adverts
• We're seeing streaming platforms become more like traditional TV

The line between streaming platforms and traditional TV continues to blur: there's a fresh report that Disney+ is considering adding a free tier to its platform, completely supported by ads, so some shows and movies could be watched without paying anything.

This comes from Business Insider, which says that "people familiar with the matter" have revealed that Disney+ product and tech chief Adam Smith mentioned the possibility of a free tier during a town hall meeting inside the company on Thursday (July 9).

Those are all the details we have, for now — so it's just a possibility. Smith didn't give any indication of when the free tier might be offered to consumers, or how much of the Disney+ library might be available without paying anything.

There is some indication from Business Insider that Disney+ is worried about YouTube and its continued growth. While you can opt to pay for YouTube Premium, all of the content on the platform is available for free, with opts.

Free vs paid-forDisney is exploring adding a free tier to Disney+ as YouTube draws TV viewers | The tier would enable accessibility to some movies and TV shows without a paywall from r/television

While streaming platforms like Netflix and Apple TV don't have a completely free tier, there are of course services such as Pluto TV and Tubi that are built entirely around free, ad-supported streaming television (known as FAST).

Statistics from Nielsen, quoted by Business Insider, say that the three largest free streamers accounted for 18.7% of watch time in the US in April 2026, up from 16.8% a year earlier, and 12.7% the year before that — figures Disney+ will have noticed.

Reactions to the rumors on Reddit have been mixed, with the observation that "we're so close to the streamers inventing television" and a quip that "we're just getting TV again huh" summing up the general sentiment among users.

One poster suggests the new tier would be "unwatchable" given how many ads already appear on the cheapest Disney+ tier, while another airs concerns that a completely free tier would eventually come with a monthly cost as time goes on.