Microsoft has started testing a faster File Explorer and a less cluttered and more customizable context menu in Windows 11 preview builds rolling out to Insiders this week.

As the File Explorer team explained in a Monday blog post, the changes focus on improving File Explorer speed, performance, and reliability and addressing customer-reported issues.

The redesigned context menu experience also aims to make it faster, reduce clutter, and make it more customizable than ever before.

At the bottom of the new right-click menu, Microsoft also added a “Customize menu” shortcut to the Settings page, where users can tweak the context menu to suit their preferences.

“We’ve continued refining File Explorer based on that feedback, removing friction and improving the details that help make everyday tasks feel more natural and predictable. For example, file renames no longer get interrupted by background file synchronization, and case-only filename changes now appear immediately,” Microsoft said.

“Today, we’re [also] excited to announce an updated context menu that delivers a faster, simpler, and more customizable experience. The new design reduces top-level clutter, keeps commonly used actions easy to access, and introduces a new Settings experience that gives you more control over what appears in the menu.”

​These changes follow a broader effort to improve Windows Explorer speed and performance for Windows 11 users, with the most recent changes including another set of File Explorer improvements that rolled out in April.

Microsoft also began testing a feature in November designed to preload File Explorer in the background to improve launch times and performance.

However, that was optional, allowing users who wanted to disable preloading to uncheck “Enable window preloading for faster launch times” in File Explorer’s Folder Options under the View tab.

These File Explorer changes follow the May 2025 rollout of Startup Boost, a similar optional feature for Microsoft Office apps that launches a Windows scheduled task in the background during system logon to help launch Office apps faster.

On Monday, Microsoft also announced that it is removing the Windows Management Instrumentation Command-line (WMIC) tool, a known LOLBIN (living-off-the-land binary) abused by cybercriminals, starting with Windows 11 24H2 and 25H2, as well as the Windows 11 beta builds released this week.

Overall prevention scores can hide what happens after initial access. Once attackers are using valid credentials, prevention drops sharply.

The Blue Report 2026 measures defenses technique by technique across 338 million simulations run in customer production environments.

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Earlier this month, Google announced multiple new devices at its Made by Google event, including Pixel 11 phones and the Pixel Watch 5. Back in May, the company also released its screenless Fitbit Air health tracker.

But we still haven’t heard anything about the new mystery product that’s appeared in recent Google ads.

A Reddit thread posted on Saturday revealed a Google Pixel ad on YouTube featuring the new Pixel 11 series, the Pixel Watch 5 and an unknown wearable that looks like a cross between the Fitbit Charge 6 and the Watch 5, standing out with its oblong screen with rounded edges in fog white. Sponsored by Google Australia, the ad’s caption reads: “The ultimate power trio for your wrist, ears and hands. Preorder Pixel devices now.”

Some speculate that the product may be the Fitbit Charge 7 or a rebranded Pixel Watch series. Or maybe it’s an entirely new fitness tracker?

A Google representative didn’t immediately respond to a request for comment.

That wasn’t the only Google Australia ad featuring the surprise device. The mystery wearable appears in another ad displaying the Pixel 11 phones, Watch 5, Pixel Buds Pro 2, Pixelsnap phone cases and Watch loop bands in the new olive green color.

Real or fake?

Some Reddit commenters wondered whether this mystery product was a mistake caused by an AI hallucination — an error caused by generative artificial intelligence.

But this also wouldn’t be the first time Google sneaked an unreleased product into its promotional content. Back in March, two months before its release, the Fitbit Air was spotted in a paid partnership video with NBA star Steph Curry, who is also a Google performance adviser.

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It would seem that Google is releasing a new wearable, potentially as part of its Pixel line, in both fog and olive colors. If the time between these ad leaks and the device’s release follows the same pattern as the Fitbit Air’s appearance in Curry’s video, we should know more in the coming weeks.

Anna Gragert

Senior Editor, Health and Home

Anna Gragert (she/her/hers) was previously the lifestyle editor at HelloGiggles, the deputy editor at So Yummy and the senior lifestyle editor at Hunker. Over the past 12 years, Anna has also written for the LA Times, Elle, Bust Magazine, Dazed, Apartment Therapy, Well+Good and more. At CNET, she’s a senior editor on the Healthy Home team, and her coverage includes health, wellness tech, meal kits and home and kitchen tech with a focus on the technology that aims to help us live our healthiest, happiest lives.

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TikTok is developing a feature that would allow users to send each other money via direct messages, according to a new report from Bloomberg. If rolled out, the feature would use the social media service’s TikTok Pay offering, which is already available in Southeast Asia for TikTok Shop purchases.

References to the potential feature were found in code hidden within the current version of TikTok’s U.S. iPhone app, according to the report. The code indicates that recipients would be able to “tap to accept” payments, while senders could include messages with their payments, similar to Venmo.

TikTok told Bloomberg that the feature is not being tested, which suggests that it’s in early development. Given that the feature is still under development, it’s unknown when or if TikTok plans to widely release peer-to-peer payments.

TikTok did not immediately respond to TechCrunch’s request for comment.

It’s worth noting that this isn’t the first time TikTok has tried to push further into financial services. Reuters reported earlier this year that TikTok had applied to Brazil’s central bank for approval to operate as a financial technology company offering lending and payment services. 

Although TikTok is widely described as a social media giant, it has gradually expanded beyond that category thanks to additions such as robust search, TikTok Shop, a local discovery map, games, hotel bookings, and more. By introducing peer-to-peer payments, TikTok would be competing with services like Venmo and Zelle.

TikTok isn’t the only social network pushing into financial services, as X, formerly known as Twitter, recently launched X Money to allow users to send each other money.

Block, the technology company founded by former Twitter CEO Jack Dorsey that owns Square, Cash App and the music streaming service Tidal, is open-sourcing Berd, a desktop application it originally built to give its own employees a single environment for working with AI agents across different models, tools and projects.

Berd is a locally installed graphical desktop application rather than a browser-based workspace. It is available now on GitHub under a permissive Apache 2.0 license — meaning anyone can use, modify and redistribute it, including commercially — with free downloadable builds for macOS, Windows and Linux. The repository reached version 0.6.2 on Aug. 18, its seventh public release, and lists 91 contributors.

“Berd is desktop-first because much of its value comes from working directly with projects, local files, tools, repositories, and agents running on or connected to the user’s computer,” Brad Axen, Head of AI Capabilities at Block, told VentureBeat in emailed responses.

A daily work surface for AI agents

Block positions Berd as a “daily AI work surface”: a single place where users can start chats, attach files or folders, choose agents and models, work inside persistent projects, configure AI providers, manage skills and extensions, review session history and build automations.

The design goal is not merely convenience. According to Berd’s product specification, users should always be able to tell which project, files, agent, model, provider and session state are actively shaping a conversation. That emphasis on visible operational state is what Block says separates Berd from a generic chatbot wrapper. Configuration — providers, extensions, skills, automations, projects — is treated as part of the workflow rather than buried in an administrative layer, and the interface is designed to expose failures, unavailable providers, and loading and streaming states plainly rather than smoothing them over with assistant-style friendliness.

Berd grew out of a practical problem inside Block. Employees were already working with capable agents — Block’s own Goose, Anthropic’s Claude Code and OpenAI’s Codex — but the experience around them had become fragmented.

“We had capable agents through goose, Claude Code, and Codex, but working across them meant navigating different interfaces, configuration systems, and ways of managing context,” Lucinda Bell, Technology Communications at Block, said in an email. Berd, she said, gives Block teams “one consistent desktop application across models and harnesses.”

For enterprises, that layer may matter as much as another incremental gain in model capability. Persistent projects mean users can return to an established collection of files, instructions and agent configurations instead of reconstructing context for each task. Block also explicitly designed Berd to make agentic work accessible beyond engineering, letting people start with a conversation and add tools, context and structure as the work requires.

Block is not positioning Berd as a mobile product. Axen said the company’s open source collaboration platform Buzz already provides a mobile experience and is Block’s preferred environment for work on the go.

Block thinks agents should look different when they are different

Berd takes an unusual approach to a problem most enterprise AI products leave implicit: how users tell one configured agent apart from another.

Instead of treating every agent as another blank chat window, Berd gives agents roles, instructions, skills, tools and recognizable visual identities. Block created collections of animated characters — its flagship designs are called “Gloopies” — and Berd’s public site showcases predefined personas such as Berdy, Pushback, Choosey, Copycat, Tinker and Wildcard, each built around a different style of work: Pushback plays devil’s advocate on drafts, Choosey helps narrow decisions, Copycat learns to write in the user’s style.

The visual layer is not meant to substitute personality for substance. Block’s own formulation, from a company blog post on Berd’s design, is functional: “The avatars make the agent recognizable. Its role, skills, and tools make it useful.”

That distinction could grow more important as workers juggle several specialized agents at once. A recognizable identity serves as visible shorthand for an otherwise invisible package of instructions, tools and permissions — agents appear on the workspace as distinct animated characters rather than identical entries in a chat list, so users can tell them apart before opening a conversation.

The product specification guards against the characters turning Berd into a novelty. It describes the intended personality as “focused, capable, companionable,” while explicitly rejecting toy-like presentation, oversized decorative UI and interfaces that hide operational state behind friendliness.

An orchestration layer, not another model or agent runtime

Architecturally, Berd is neither a new foundation model nor a new agent runtime. The application is built with Tauri 2 and React 19 — frameworks for building lightweight desktop apps with web technologies — and communicates with Goose, the open source agent framework Block introduced in January 2025, through a standard called the Agent Client Protocol (ACP). Goose runs quietly alongside Berd as a bundled “sidecar” process and handles the underlying agent loop; Berd handles projects, sessions, context, agents and configuration on top.

For readers unfamiliar with it, Goose is a model-agnostic agent framework and runtime, originally focused on software development workflows. It connects large language models to files, commands and outside systems — including through the Model Context Protocol (MCP), an open standard for wiring AI systems to external tools and data — so agents can take actions rather than merely generate text.

Goose works with proprietary model providers as well as locally run open models. Block has since contributed Goose to the Agentic AI Foundation, the Linux Foundation body it helped establish with Anthropic, OpenAI and others in December 2025, giving the framework a vendor-neutral home alongside MCP.

Axen drew the boundary explicitly: agent harnesses such as Goose, Claude Code and Codex manage the loop between a model, its context and its tools, while Berd provides the consistent desktop environment around those harnesses. In the public release, users configure whichever providers and harnesses they want rather than inheriting a Block-selected model stack.

The project’s README adds an operational detail that matters for anyone evaluating the software: Berd does not simply pull whatever Goose build happens to be current. Its build process pins a specific Goose backend version through a lockfile, verifies the cached binary matches that pinned version, and packages it with the app. Developers can explicitly substitute another Goose binary for local testing. For organizations inspecting Berd, that creates a defined version boundary between the desktop application and its default agent backend rather than letting the backend silently drift.

How Berd compares to Codex, Claude Code, Cursor and Goose

That separation matters because the agent-tooling market is already converging on products that manage increasingly autonomous AI workers. OpenAI describes its Codex app as a “command center” for agents, with separate project threads and multiple agents operating in parallel.

Claude Code, Anthropic’s agent for reading codebases, editing files and executing commands, now spans the terminal, IDEs and a desktop app. Cursor describes its latest release, Cursor 3, as a unified workspace for software development with agents, including handoffs between local and cloud agents and multi-repository workflows. And Goose itself remains available directly, as a free command-line tool and desktop app for technically comfortable users.

Berd’s differentiation is therefore less about inventing the agent workspace than about making that workspace open source, multi-harness and potentially useful outside coding. Every other product in the table below is either tied to a single vendor’s models, priced as a subscription, or aimed squarely at developers — and in most cases all three.

Portability is part of Block’s pitch. Axen said much of the underlying work in Berd is deliberately kept portable: folders, Git repositories, files and plain-text instructions remain accessible outside the application; skills are file-based; and Berd agents can be exported and shared between Berd users with their instructions and settings intact.

He pointed to ACP and MCP as part of Block’s direction toward “clear, user-owned formats and open protocols wherever possible.” That does not make every piece of state interchangeable across every harness, but it makes portability an explicit architectural goal rather than a side effect of using local files.

Local-first data, telemetry and enterprise distributions

Berd is designed around a local-first data model. Axen said conversation history is stored on the user’s device in the local Goose session database, while credentials live in the operating system keychain by default.

That does not mean all AI processing happens locally. “Local-first does not mean that no data ever leaves the device,” Axen said. When a user asks a configured model to work on particular context, the relevant prompt and material are sent to that model’s provider — so the actual data path, and the contractual terms governing it, depend on which provider an organization chooses.

Telemetry — the usage data software sends back to its maker — is disabled by default in official Berd distributions. If a user opts in, Block says it collects a random installation identifier and a limited set of predefined usage events, while excluding prompts, messages, files, source code, credentials, names, email addresses and IP addresses from the telemetry payload itself (Block and its service providers still process IP addresses for transmission, security and rate limiting). Users can switch telemetry off again in settings. Block cautions that third-party forks can modify or redirect the telemetry system, so enterprises evaluating a customized build need to review that build’s actual behavior rather than assume Block’s defaults carry over.

The public repository builds a self-contained, general-purpose distribution that does not depend on private package registries or enterprise credentials — technical teams can build and evaluate it without access to Block’s infrastructure. But Block has also created what it calls “distribution seams”: defined points where organizations can overlay managed provider settings, private agents, runtime configuration, optional companion tools, their own update channels and their own signing and publishing infrastructure, all without adding private material to the public source tree.

Block’s own deployment shows how an enterprise can put governance around that architecture. Axen said Block runs its managed distribution on approved devices using approved model-provider infrastructure, managed configuration and governed tool connections. “The application can remain open and inspectable, while an organization decides which models, tools, permissions, and policies are appropriate for its environment,” he said.

One caveat: “enterprise distribution” should not be read as a complete enterprise management plane. The README does not describe capabilities such as single sign-on, centrally enforced administrator policies, organization-wide permission controls, data-retention rules or audit logs. It establishes that companies can customize and distribute Berd; it does not by itself explain how those installations are centrally governed after deployment. Berd should be understood as endpoint software installed on users’ computers, not a centrally hosted SaaS product.

Pricing, models and a closed contribution model

Block has not announced a subscription price for Berd, and there is no indication one is coming. That does not make agent usage costless: organizations still pay whatever model, API or provider charges they incur. The economic pitch on Berd’s site is flexibility — users can match the model to the job rather than paying for an expensive frontier model on every task. As the site puts it: “Some tasks need the big brain. Most don’t.”

Neither Block’s announcement nor the README provides a definitive matrix of supported model providers or recommends particular models. Internally, Block does not treat any one model as a permanent default: Axen said the company’s managed distribution exposes employees to “a curated mix of frontier and open-weight models,” with the catalog changing as models improve. “The best choice depends on the work,” he said.

There is also a governance distinction developers should note. Although Berd’s source is public and Block solicits issues and feedback, the repository does not accept outside pull requests — external code contributions are automatically closed.

The README says Berd is built by “a small team at Block” and directs outside participants toward well-formed, reproducible bug reports instead. Users are free to inspect, build and fork the code, but Block retains a tightly controlled upstream. For companies considering Berd as infrastructure rather than an experiment, that makes Block’s long-term maintenance and support plans worth clarifying.

Block is not presenting Berd as a revenue product today. Axen said the first return on investment comes from Block’s own use of the software — making internal agent work more consistent while teaching the company how employees actually use agents — and that open-sourcing it adds leverage by letting outsiders inspect, adapt and give feedback on the architecture. A commercial layer around enterprise deployment may eventually follow.

“Supporting organizations that want to deploy agents at work is an area of interest for us,” Axen said, adding that Block will share more when there is more to share.

From private agent work to multiplayer workflows

Berd supplies the individual desktop experience; another Block project, Buzz, focuses on shared rooms where people and agents collaborate against a common, searchable record.

Buzz is Block’s free, Apache 2.0-licensed collaboration workspace for humans and AI agents. Built on the decentralized Nostr protocol, it combines familiar team features — channels, threads, direct messages, voice and media sharing — with agents that hold their own cryptographic identities and defined permissions, and that can participate in conversations, code review and approved automated workflows. Unlike Berd’s local, single-user focus, Buzz is explicitly multiplayer, and can be self-hosted or used through Block-hosted infrastructure. It is likewise model- and harness-agnostic: teams can bring agents powered by Goose, Claude Code, Codex or others.

Axen framed the split between the two products partly as a question of trust boundaries. “A local agent may have access to your filesystem and credentials,” he said. “An agent in a shared Buzz room has its own identity and access scoped through the relay.” Berd begins with one person and comparatively privileged access to that person’s machine; Buzz begins with multiple participants, explicit identities and shared-workspace permissions.

The more consequential roadmap detail is that Block does not intend the two products to remain separate. “Going forward, our focus is Buzz, and we plan to bring the best parts of Berd’s single-player experience into it,” Axen said. Block wants work to begin privately and become collaborative without users switching tools or rebuilding context, with cross-device continuity — including mobile via Buzz — part of that ambition. In the meantime, Axen said, Berd remains available as an open source desktop application, but Buzz is the product Block encourages people to download and adapt.

What enterprise adopters should take away

The short version for IT and security teams: conversation history stays local by default; credentials use the operating system keychain; context sent to a model leaves the machine on whatever terms the configured provider offers; official telemetry is off by default and excludes prompts, files and source code; and organizations can package their own governed distribution — though central management tooling is not yet documented.

The larger idea behind the release may matter more. Models and coding agents are becoming increasingly interchangeable components inside larger workflows. Berd is Block’s bet that the surrounding context — the projects, skills, tools, identities and persistent working environment — becomes the stable layer instead.

Whether you like it or not, ChatGPT is already everywhere. People use it to research complicated topics, clean up their writing, learn new skills, plan their lives, and, in my case, ask an embarrassing number of questions I could have figured out myself. Teenagers are no exception. In fact, OpenAI says nearly nine in 10 teens who use ChatGPT turn to it to learn, find information, develop skills, or get things done during a typical week. So rather than pretending students aren’t going to use AI, OpenAI is taking a different approach: give them a version built specifically for them. The company has announced ChatGPT for Teens, a new experience for users between 13 and 17 that’s designed around learning, healthier usage habits, and significantly stronger safety protections. 

ChatGPT wants to teach, not just hand over the answer

What interests me most is how OpenAI is approaching homework. Imagine you’re preparing for an exam and calculus has suddenly decided to ruin your evening. Instead of asking ChatGPT for the answer and copying it into your notebook, the teen experience is designed to walk you through the problem, explain the concept you don’t understand, and then help check whether you’ve actually understood it. That’s a much healthier role for AI in education. ChatGPT for Teens brings together features such as Study Mode, quizzes, learning visualizations, homework reminders, and dedicated study hours. The idea is to make ChatGPT more like an always-available study companion.

OpenAI is pushing that idea outside ChatGPT, too. The company has announced a partnership with CodeAI to give students and teachers resources for developing AI literacy. Instead of simply teaching students how to prompt a chatbot, the initiative is meant to help them understand how AI works, question what it produces, direct it effectively, and eventually use it to build things themselves. That distinction matters. Today’s teenagers aren’t going to enter a world where AI suddenly disappears after graduation. Learning when to trust it, when to challenge it, and when not to use it could be just as important as learning how to use it in the first place.

Helpful? Absolutely. Human? Let’s not get carried away

Of course, once you put a powerful AI chatbot in front of teenagers, safety becomes a much bigger part of the conversation. OpenAI is putting stricter guardrails around accounts for users under 18, particularly when it comes to sensitive topics such as graphic violence, dangerous activities, unhealthy dieting, extreme beauty standards, and sexual or romantic roleplay. Another equally important part is that it is also setting boundaries around how ChatGPT interacts with teens on a more personal level. The chatbot shouldn’t encourage emotional dependence, pretend it has real feelings, or make users believe there’s a human-like consciousness behind those responses. It might sound like a small detail, but think about how natural these conversations have become. When an AI can talk back instantly, remember the context of a conversation, and respond at 2 AM when nobody else is awake, it can be easy to forget that you’re still talking to software.

The company is adding a few smaller reminders to reinforce that distinction. Teens will be warned before uploading potentially private or sensitive images, while a dedicated onboarding experience will explain the learning and safety tools available to them. There are also break reminders encouraging teens to put ChatGPT down occasionally. They can still make the experience feel more personal by changing things like the accent color or voice, but ChatGPT is still supposed to make it clear that it’s AI. Parents get some controls as well. With linked accounts, they can manage certain settings and set Quiet Hours. In a limited number of higher-risk situations, they may also receive safety notifications intended to help them step in when offline support could be useful.

I’m cautiously optimistic, with a very big asterisk

While this feels like a step in the right direction, OpenAI still has plenty of work to do, especially when teenagers are using ChatGPT. We’ve already seen serious concerns around AI-generated deepfakes, people turning to chatbots during moments of emotional distress, and conversations that probably need a trusted person on the other end rather than an AI model.

That also leaves me wondering how comfortable parents will actually feel with all of this. Will these safeguards be enough for them to trust ChatGPT with their teenagers? I’m not entirely convinced yet. Still, AI is quickly becoming part of how younger people learn, communicate, and create. Keeping them completely away from it probably isn’t realistic anymore. Helping teens understand how to use AI responsibly while knowing when to put it down and turn to a real person instead may ultimately be the more important lesson.

Grand Theft Auto fans will have to wait until later this month for a deep dive into the next game in the series, which will premiere on Netflix before hitting YouTube later that day (though probably much sooner on unofficial channels). But despite Rockstar Games’ efforts to keep a tight lid on Grand Theft Auto VI leaks — especially after the 2022 incident — some legitimate-looking gameplay footage is now out there.

The publisher has reportedly been hitting people who are sharing two minute-long gameplay clips and a screenshot of the Florida-inspired map with DMCA takedown notices. While we can’t share the materials here or tell you where to find them, you’re a citizen of the internet. You may just stumble upon them yourself. What we can do, however, is describe what we’ve seen.

Let’s start with the map of Leonida, which looks like a distorted, compact version of south Florida. As with GTA V, it features a large city (Rockstar’s version of Miami this time). That’s on the east of Leonida, with lots of greenspace in the west and the north. There are many, many large and small islands dotted across the map, with a group that looks like the Florida keys in the south. There are a bunch of markers on the screenshot as well. Most are nondescript, but others include a home icon, a balaclava-covered face, cars and (gulp) an alligator.

One clip shows Jason, one of the game’s dual protagonists, at a waterside home. There’s gym equipment on the balcony, which brings to mind the workouts from GTA San Andreas. Jason hops over the ledge and runs by a jetski before picking up a basketball and making a few shots. After he scores with his first attempt, he gets a focus stat boost, which suggests GTA VI will lean into RPG mechanics.

There isn’t much else to speak of in terms of the HUD in this clip. There are two dollar values in the top right of the screen that match the font from previous games. What seems to be a focus bar appears in the top left when Jason has the basketball in hand.

For what it’s worth, the building looks identical to one that appears in an official screenshot of GTA VI. It’s labeled as Jason’s safehouse on the game’s website.

Rockstar Games

The second clip has more action. It opens with Jason looking like he’s about to drive over a bridge toward an area called The Keys before making a U-turn and causing relatively mild carnage. 

After colliding with a delivery truck, he and the driver get in a fight. Jason kills the guy with a wrench (each swing of which depletes an energy bar) the latter was holding. This earns Jason a two-star wanted level. A devil icon with a minus sign appears on the right of the screen, as well as on a portrait of Jason that pops up. This indicates there’s an honor/karma system, like in the Red Dead Redemption series.

As Jason returns to his vehicle, “loadout” and “storage” prompts briefly appear, suggesting that you can change your weapons and store items (say, a wrench) in your car. After he gets back in the driver’s seat, an icon pops up with the car’s name and a gas meter, so it looks like you’ll have to fuel up your vehicles this time. The clip — which also features a GTA V-esque minimap — ends just as Jason approaches an air ambulance.

It’s worth treating the clips and map with some skepticism, since they may not be entirely legitimate. It’s also unclear how old they are and what may have changed in the meantime, though Rockstar’s servers were breached earlier this year. They’re at least plausible looks at GTA VI.

The materials are watermarked with URLs that claim to offer fans more details alongside a “fighting for gamers’ rights” message. The alleged leaker claimed to have released the footage and screenshot to protest Rockstar’s decision to only include a code in the box of the game’s physical edition, rather than a disc. They’re threatening further action against Rockstar and other publishers over purported anti-consumer practices like digital pre-orders, “fake single-player DLC” and failing to maintain access to single-player games.

Grand Theft Auto VI will hit PS5 and Xbox Series X/S on November 19. An extended look at the game will stream first on Netflix on August 27.

Google is promising a better modem with the Pixel 11 series. The company claims its new MediaTek-made hardware is both faster and more power-efficient than the modems used in previous generations.

The switch is a notable one for Google’s Tensor chips, as earlier Pixel phones were criticised for modem performance. Previous generations of Tensor relied heavily on Samsung’s Exynos-based technology; however, the Pixel 11 marks a key change as the Tensor G6 moves to a MediaTek modem.

This partnership seemingly aims to bridge the gap with formidable rivals like Qualcomm’s Snapdragon, which has long set the gold standard in the Android space for connectivity. For Google, finally securing a dependable, uncompromising cellular experience is crucial if the Pixel line is to truly compete at the premium end.