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Google's Pixel 11 phone uses a Tensor G6 processor with a powerful TPU. How is it different from a GPU, and what does that mean in real-world use?

If you're wondering if CarPlay works over Wi-Fi or Bluetooth, the answer is yes. It uses both at different times.

Installing a large language model on your personal computer gives you a handy digital assistant that won’t compromise your data privacy.

If your Wi-Fi signal is patchy at the far reaches of your house, this simple solution might be worth a try. Even better? It's completely free.

Are XREAL's smart glasses the way of the future for home entertainment?

Making the Migration from In-View Asynchrony to Synchronous State Management Truly Mechanical After our recent discussions on why FutureBuilder and StreamBuilder are architectural anti-patterns when placed inside Flutter widget trees, I started thinking: how can we make it even easier—even completely mechanical—to convert from a FutureBuilder or StreamBuilder to a BlocSignalBuilder ? Every Flutter developer knows the history. Years ago, I recorded a video breaking down the hidden traps of placing asynchronous builders in UI views: Why you shouldn't put FutureBuilder in your build method . Even the original official Flutter video on FutureBuilder initially instantiated the network future directly inside the build() method, until I filed an issue to get it corrected (which is why the official Flutter YouTube video still proudly bears "Take 2" on its clapperboard!). The fundamental issue has never been that developers want bad architecture. The issue was friction . FutureBuilder was simply the path of least resistance. To do it "properly" in traditional state management, developers had to create an entire BLoC or Cubit, declare separate Event and State classes (or union types), write boilerplate event handlers, wire asynchronous repository methods, manage subscription lifecycles, and inject everything into the widget tree. With bloc_signals 1.1.0 , that friction disappears completely. We have introduced universal, symmetrical adapter extensions that allow any Dart Future , Stream , ReadonlySignal , or lifted primitive ( value.$ ) to adapt into a synchronous BlocSignalBase container with a single method call. 🧭 The Universal Dual-Track Mental Model When bridging asynchronous sources into synchronous state management, developers typically have one of two distinct intents: Raw Domain Values ( T ): You want raw domain objects (for example int , UserProfile , ThemeMode ) with zero wrapper ceremony, and you have an immediate default or fallback value for frame 0. Rich Asynch

The longtime far-right operator and troll, a UK citizen, is being held in ICE custody pending his removal from the United States.

Sophia Bendz, general partner at Cherry Ventures, stopped by Equity to break down the latest in the Swedish tech ecosystem.

Cloud spending is on track to pass a trillion dollars a year, and most of it is wasted. Industry data puts idle resources, over-provisioned instances, and missed commitment discounts at 25 to 35% of the average cloud bill. For an early-stage company where hosting can eat 6 to 12% of revenue, that waste is not a rounding error. It is runway. The good news is that cloud cost optimization rarely requires a painful re-architecture. The biggest wins come from a few low-risk moves: switching off what nobody is using, rightsizing what is over-provisioned, and buying commitments for the baseline you will run anyway. The discipline that ties these together is called FinOps, and you do not need a dedicated team to practise it. You need visibility into where the money goes, a short list of high-leverage actions, and the habit of reviewing the bill before it reviews you. This playbook walks through exactly that, in the order we apply it for the startups we work with. Find the waste before you cut it You cannot optimize what you cannot see. Before touching a single instance, make your spend legible. That starts with cost allocation tags, a small enforced set like env , team , service , and customer , applied to every resource. Untagged spend is where waste hides, so treat an untagged resource as a bug to be fixed, not a footnote. With tags in place, the native tools do most of the heavy lifting. AWS Cost Explorer (and its equivalents on GCP and Azure) will show you the trend line, the biggest line items, and the resources sitting idle. Set budget alerts at the account and per-environment level so a runaway job pings you on day two, not on the invoice. The most important shift is what you measure. Don't stop at "we spent $14k on EC2." Tie cost to a unit of business value: cost per customer, per active user, or per thousand requests. That single number turns an abstract bill into a metric you can defend in a board meeting and optimize against deliberately. The number that matters

For a decade the advice was simple: put everything in the cloud and never look back. In 2026 that consensus is cracking. A Barclays survey found 83% of enterprises plan to repatriate at least some workloads from public cloud to private infrastructure, and IDC puts the share expecting to move compute or storage within the year near 80%. The most-cited example is still 37signals, the team behind Basecamp, who left the public cloud and reported saving roughly $7 million over five years. It is tempting to read those numbers as "cloud was a mistake." It was not. The cloud is still the right home for spiky, unpredictable, early-stage workloads where you are buying speed and optionality. What changed is that a lot of companies have now run the same steady, predictable workload on rented hardware for years, paying a premium for flexibility they stopped using. Repatriation is not a reversal of cloud strategy. It is the correction that comes after the bill gets big enough to read carefully. The question worth answering is not "should we leave the cloud" but "which specific workloads no longer earn their cloud premium," and that is a question you can answer with numbers. What is actually driving the move Cost is the headline, and it is real. Organizations that repatriate the right workloads commonly report 30 to 60% lower infrastructure spend for those workloads, because on-demand cloud pricing carries a large convenience margin that only makes sense when your usage is genuinely variable. Run a database at a steady 60% utilization every day for three years and you are paying a premium for elasticity you never touch. But cost is not the only force. Just over half of organizations name data security and privacy as a top driver, and in Europe the regulatory pressure is sharper than the cost case. Frameworks like DORA are already enforceable, and regulators increasingly want evidence of control over where data physically lives, not just a contractual promise from a hyperscaler. Fo

Your phone should be able to still sound your morning alarm when it's in silent mode. If it's not, here are some settings to check.

A recent paper argues that AI is often better at doctoring than doctors. Guess who isn't thrilled.

The finding EventCatalog exposes a common monorepo failure mode: generated code may exist, its producer may be green, and the real downstream consumer can still fail. Its Langium language server generates AST, grammar, module, and syntax files; a sibling VS Code extension consumes that output alongside the workspace SDK and visualiser. The useful question is therefore not "did generation finish?" It is whether the repository can execute the complete consumer closure from declared dependency hydration through the package that needs the generated result. The contract boundary Ota models the generated output separately from the tasks that establish and consume it: artifacts : language-server-ast : kind : generated_source producer : language-server:generate paths : - packages/language-server/src/generated/ast.ts - packages/language-server/src/generated/grammar.ts - packages/language-server/src/generated/module.ts - packages/language-server/syntaxes/ec.tmLanguage.json - packages/vscode-extension/syntaxes/ec.tmLanguage.json inputs : - packages/language-server/src/ec.langium - packages/language-server/langium-config.json tasks : vscode-extension:build : depends_on : - language-server:generate - language-server:build - sdk:build - visualiser:build requires_artifacts : - language-server-ast The setup task owns typed, frozen-lockfile pnpm hydration with the language-server package filter. That removes bespoke install shell glue without pretending the dependency path is harmless: it reaches the package registry, so the selected closure is intentionally not routine agent-safe execution. Humans and CI can run the declared verification workflow; unattended agents cannot silently acquire that networked setup authority. What Ota had to learn This pressure case made two platform requirements concrete. Generated-source lineage had to remain visible at consumer admission and in execution evidence, rather than surfacing only after a build failure. And pnpm dependency hydration needed a

The art portfolio platform Cara, designed for creators who don’t want their work used to train AI, has been under assault by trolls seizing and publishing its data.

The company is testing robots that can swap cables, reset servers, and take on other tasks performed by technicians, fueling concerns among some workers that their jobs could be at risk.

Launched by Belgian startup Any, LUV1 is a modular electric motorcycle with 120 liters of cargo space that can be used to carry bags, work equipment, or even pets.

A federal judge has called the Department of Defense’s designation of Anthropic as a national security supply-chain risk “illegal and baseless.”

People in the US don't have much choice beyond Apple, Google, and Samsung phones. But there are so many more choices that aren't sold in the region.

This week on “Uncanny Valley,” senior writer Will Knight talks his recent visit to China and the future of AI collaboration.

The potential for AI to automate scientific research and manufacturing must be balanced with new risks, Anthropic says.