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Thirteen other medical groups have already endorsed the independent schedule.

Anthropic released Claude Fable, its first Mythos-class AI model, yesterday and it's already causing concerns inside Microsoft. Sources tell me that Microsoft is limiting the use of Claude Fable 5 for employees because of Anthropic's new data retention requirements. While Microsoft quickly rolled out Claude Fable 5 to its GitHub Copilot and Foundry customers, I'm […]

Cybersecurity researchers are complaining that Anthropic's new model Fable has guardrails that are too strict for any cybersecurity work.

AI coding agent startup Niteshift has raised a $7 million seed round from a who's who of angels. It's betting companies will want power over, not lock-in with model makers.

Following the launch of the surprisingly popular Kobo Remote, Boox has released its own device to ease the burden of reaching for an e-reader’s touchscreen that’s an arm’s length away. The Tappy isn’t Boox’s first page-turning remote, but its design takes a much different approach to the company’s slim but boring B.T. Remoter. The Tappy […]

A cybercrime group known as The Gentlemen has emerged as the second most active ransomware gang by victim count, rapidly attracting a talented pool of hackers through an aggressive recruitment strategy that promises affiliates 90 percent of any ransom paid by victims. This post examines clues pointing to a real life identity for the administrator of The Gentlemen ransomware group.

The ACLU is suing two Florida police departments over the arrest of a Fort Myers man in a child-abduction case, saying officers treated a flawed face-recognition match as a near-certain ID.

There are many ways to create memorable experiences. Sometimes it's as simple as a form that completes smoothly. But here I'm interested in sharing techniques I reach for when I want a site to feel alive and be remembered. Creating Memorable Web Experiences: A Modern CSS Toolkit originally handwritten and published with love on CSS-Tricks . You should really get the newsletter as well.

You’ve spent weeks, maybe months, tracking down bugs, optimizing your user interface, and wrestling with backend security rules. You compile your native release build or run your final production compilations, thinking the hardest part of the journey is officially behind you. Then you open the Google Play Console, and you’re hit with the ultimate indie developer roadblock: the mandatory 12-tester and 14-day closed testing requirement . Many independent creators view this process as a simple download checklist. You might think, "I'll just find 12 people to download the app, leave it on their phones for two weeks, and wait it out." However, treating the testing phase as a static metric is the fastest way to get rejected during the final production access review. So, what is Google actually tracking in the background during these two weeks? Let’s take a deep dive into the core algorithmic requirement that determines your success: Continuous Engagement . 🔄 Decoding "Continuous Engagement" Google Play policies are not designed as a simple box-checking exercise. The underlying goal of the algorithm is to verify if your application is genuinely functional, stable, and being tested by an organic user base before it reaches millions of production users. To enforce this, Google's advanced systems actively monitor the devices connected to your closed test track over the 14-day timeline: Background Device Pings: Google Play Services regularly collects background automated signals (ping logs) from the devices where your test build is active. Real User Interaction: Leaving an app to rot in an application drawer without ever opening it is instantly flagged by the algorithm. Google measures whether the app is actively opened daily and tracks active interaction metrics within the build. Feedback Loops: The system monitors whether your test community is utilizing the internal testing channel on the Play Store to send private developer feedback and crash reports. 📉 The Illusion of "Ju

Electricity demand from AI data centers is pushing everyone — including automakers like GM and Ford — into the energy storage business.

Waymo made a virtual driver called ReD to help its robotaxis avoid accidents.

Fusion power startup Avalanche Energy said its reactor prototype heated a plasma to over 10 million degrees C.

What device do we use almost all the time? Our mobile phone, almost certainly. If we wanted to...

Adi Polak discusses the architecture required to transition from stateless prompts to state-aware, context-rich AI agents. Drawing on 15 years in distributed systems, she shares how engineering leaders can leverage Apache Kafka and Flink for real-time stream processing, dynamic memory tiering, and tool orchestration via MCP to solve token limits, cost spikes, and latency bottlenecks. By Adi Polak

Chinese EV colossus BYD has announced plans to speed up its conquest of the European auto market with the rollout of superfast Flash Chargers across the continent. BYD has already installed the first new chargers in Germany and the UK, and plans to roll out 3,000 across Europe by the end of next year. At […]

The games start June 11 and end with a grand finale in New Jersey on July 19. There are 104 of them. Here’s how to watch ’em all.

Referees for the 2026 World Cup will be wearing cameras positioned at their temples, allowing TV audiences to see a live view of the pitch from a vantage point they never have before.

Most US World Cup stadiums are surrounded by surveillance cameras. Want to know if you’re being watched on your way to a match? These maps will help you.

The real question isn't which framework is better. It's which one you can stop thinking about six months into the project. Key Takeaways Project Suitability — Django is built for weight. Flask is built for speed. Know which one your project actually needs before you commit. Development Flexibility — Django makes decisions so your team doesn't have to. Flask hands those decisions back. Both are features, depending on who's writing the code. Scalability & Performance — Scaling is an architecture problem first, a framework problem second. Pick the one that matches the system you're building — not the one you hope to build. Security Features — Django's protections are on by default. Flask's require you to turn them on. In a fast-moving team, that difference is more significant than it sounds. Ecosystem & Community — Both communities are active and well-documented. You won't be stuck either way. The Decision Nobody Takes Seriously Enough I've watched this play out more times than I'd like to count. A team kicks off a Python project, someone picks a framework — usually the one the most senior person knows best — and everyone moves on. Fast forward six months and the codebase is exhausting to work in. Either they're dragging a full framework through a service that should've been twenty lines of Flask, or they're rebuilding authentication from scratch on something that outgrew its lightweight origins two sprints in. The framework choice isn't irreversible. But undoing it mid-project is expensive in a way that doesn't show up in any estimate. Django and Flask are both genuinely good. What they're good for is different. That's the part worth slowing down on. What You're Actually Getting With Each One Django arrives with almost everything a web application needs already assembled — an ORM, an admin panel, authentication, form handling, CSRF protection, and more. The design assumption is that most web applications need most of these things, so it makes more sense to ship them i

WorkManager is the right tool for deferrable, guaranteed background work in Android. But the default setup pushes you toward boilerplate fast: you end up calling WorkManager.getInstance(context) inside ViewModels, "passing Context where it doesn't belong", re-registering observers scattered across the codebase, and getting no consistent way to query the state of your enqueued work. This tutorial shows how to build a clean, injectable WorkManagerHandler using Dagger Hilt, a single interface that any ViewModel can receive through constructor injection, with zero Context and a guaranteed WorkQuery callback on every call so you always know what to observe. By the end, you'll have: A WorkManager singleton provided through Hilt A custom Configuration.Provider that plugs Hilt's HiltWorkerFactory into WorkManager at initialization A WorkManagerHandler interface with a WorkManagerHandlerImpl that encapsulates enqueueing, chaining, and query registration ViewModels that declare WorkManagerHandler as a plain constructor dependency The pattern scales cleanly as you add workers: each new worker is one method on the handler, and the ViewModel never knows or cares how work is scheduled underneath. Prerequisites : familiarity with Dagger Hilt basics, Jetpack WorkManager fundamentals, and Kotlin coroutines. A working Android project with Hilt already configured is assumed. Part 1: Application Setup and Custom Configuration.Provider By default, WorkManager initializes itself automatically using its own internal factory. The problem is that Hilt-injected workers need Hilt's factory HiltWorkerFactory to resolve their @Inject constructor dependencies. If you let WorkManager self-initialize, your workers won't have access to any of your Hilt bindings. The fix is to disable auto-initialization and take manual control via Configuration.Provider and AndroidManifest.xml 1. Disable auto-initialization In your AndroidManifest.xml , remove WorkManager's default initializer: <application ... > <