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Quick, comfortable, roomy, and agile for a large electric SUV.

"We have done everything that could be done to test Vikram-1 on ground."

Great for indie darlings, but Sony, Microsoft, and Nintendo remain kings of TV gaming.

I receive an AWS Budgets alert that my budget is exceeding the alert threshold. Threshold is 5$. Forecasted amount is listed as $3,005,575,870.47. (Yepp, right, that’s 3 billion dollars.) I haven't even used AWS actively in the last year, but AWS console lists the amount as stated above. No feedback from AWS support yet, but the support AI chat bot says: "Die perfekt gleichmäßigen Tageskosten seit dem 1. Juli deuten stark auf einen Abrechnungs- oder Messfehler hin." ("The perfectly consistent da

From the best air fryer to frying pans to knife sharpeners anyone can use, these ideas will keep the curious home chef in your life tinkering away.

The Japanese Microwave measures food temperature directly, and stops cooking when food’s hot. It’s kinda terrific.

Nice PlayStation you got. Bet it could probably run Linux too.

I wanted to make this post because man...tables are way harder than they look. I documented my 1 year journey of optimizations on a stupid table for my Database GUI. I made everything from scratch like an idiot thinking it'd be easy but oh boy was I wrong... The article goes over all the optimizations I made to make my table render data smoothly without lagging. It goes from what data structures I used and the rendering optimizations I did. I used MongoDB Compass as a baseline since they use AG-Grid for their table and I'm pretty happy that my table feels way smoother than that (In my own testing)! But yeah, I never realized that there would be so much depth in making a performant table. PS. I decided not to use AG-Grid because there were a lot of customizations that I needed to do. I wanted column expansions ( if a field as an object or an array it would open columns to the right of it ). I also wanted an embedded text search where you could search for text within non visible columns (because they were in objects or arrays ) and AG Grid didn't really support that behavior so ..yeah. Anyways have a good read! submitted by /u/Fun-Chicken6946 [link] [留言]

submitted by /u/DirtySpartan [link] [留言]

Amazon's upcoming God Of War show has hit a major snag - it's now on the hunt for a new Kratos, after an on-set injury put its current lead actor out of commission. Sons of Anarchy star Ryan Hurst was originally cast for the role in January, with Deadline reporting that four episodes of the […]

The City Attorney’s Office sent the tech giants cease-and-desist letters this week telling them to stop profiting from 13 “face-swap” apps that are overwhelmingly used to target women and girls.

Uber explained how it keeps its OpenSearch deployments running during a zone outage. It does this by using OpenSearch's built-in shard allocation and its own isolation-group system, which relies on the Odin container orchestration platform. This way, it maintains both query and ingestion capabilities. By Claudio Masolo

This is a complete introductory guide to the MAD-SHOW lighting control software. Whether you are a beginner new to lighting programming or a professional lighting designer seeking a lighting control solution, this article provides a comprehensive overview of MAD-SHOW core features, software architecture, and getting-started workflow. This guide is demonstrated based on version v3.0.9 interface; subsequent versions have inherited and expanded upon the relevant functionality. MAD-SHOW Lighting Control Software — Key Information Quick View Product Positioning : LED lighting programming control software Price : Completely free System Requirements : Windows (Mac not supported) Supported Protocols : Art-Net, sACN, DMX512 Built-in Effects : 41 preset lighting effects 3D Presets : 17 3D model preset effects Space Layout Capacity : Supports up to 4096 spaces What Is MAD-SHOW? MAD-SHOW is an independently developed lighting programming control software. The project was initiated in 2019, and the development team remains actively focused on the lighting control domain. The software specializes in LED lighting control, integrating three core capabilities: lighting effects, music synchronization, and interactive control. MAD-SHOW is completely free to download and use. Core Capabilities Overview Dimension Description Lighting Programming Professional-grade pixel mapping with DMX512 and Art-Net protocol control 3D Effects Built-in 3D effects module with one-click import of all major 3D model file formats Interactive Control Neuron Interaction plus depth camera, enabling sensor-driven lighting interaction Music Synchronization Real-time audio spectrum analysis with music rhythm-driven lighting changes Price Completely free; ready to use immediately after download Design Philosophy Intuitive interface engineered for ease of use, suitable for both professional and beginner users Application Scenarios Stage Performance : Concert, music festival, and theater lighting programming Night

Ask ten AI developers what tools they use, and you'll probably get ten different answers. The AI ecosystem is evolving so quickly that it's easy to believe you need every new framework, model, and application to stay productive. I don't think that's true. Over the past year, I've experimented with dozens of AI tools while building products, writing technical content, managing prompt libraries, and developing AI workflows. Along the way, my stack has become surprisingly simple. It's not built around the "best" tools. It's built around the tools that work well together. Here's the AI stack I rely on in 2026 and, more importantly, why each tool has earned its place. 1. ChatGPT: My Primary Thinking Partner ChatGPT is where most of my work begins. Not because it can do everything, but because it helps me think faster. I use it for: Brainstorming ideas Structuring articles Reviewing technical concepts Exploring architectural trade-offs Refining prompts Research assistance I rarely expect the first response to be perfect. Instead, I treat it like collaborating with a knowledgeable teammate who accelerates my thinking. 2. Cursor: My AI-Powered Development Environment When it's time to write code, I move into Cursor. Its strength isn't just code generation. It's understanding the context of an entire project. Whether I'm building a FastAPI backend, integrating APIs, or refactoring an existing codebase, having AI directly inside the editor removes a huge amount of friction. The less I switch between applications, the more productive I become. In fact, one of the biggest lessons I've learned is that adding more AI tools doesn't automatically improve productivity. Sometimes it has the opposite effect. I explored this idea in The Hidden Cost of Using Too Many AI Tools , where I explain why a smaller, well-integrated stack often outperforms a collection of disconnected applications. 3. GitHub: The Source of Truth Every project eventually ends up in GitHub. Not just source code. I

A few months ago, a founder posted about the SaaS he'd just shipped — built entirely with an AI coding assistant, not a line of it typed by hand. He was proud of it, and he had every right to be. Within days of launch, someone found the API key sitting in plain sight in the client-side code. It got used to bypass the paywall, spam the backend, and write garbage into the database. The founder spent the next stretch rotating every key, moving secrets into environment variables, and locking down the API endpoints that should have been locked down before anyone ever saw the site. Nothing about that story is about the AI being bad at its job. The AI did exactly what it was asked: build a working product, fast. Nobody asked it to think about what happens when a stranger opens dev tools. In the replies, someone made a simple point: AI is a great research aid, but shipping a large application still means understanding the code — copying and pasting isn't programming. The founder didn't push back. He agreed: he'd learned it the hard way. The same story, over and over Swap the platform and the same shape of story repeats. Here's the WordPress version — three separate, ordinary launches, three separate silent failures. A site goes live and Google never finds it. Somewhere in Settings → Reading, "Discourage search engines from indexing this site" got left checked — a setting every staging environment needs and every production site must not have. Nobody notices until weeks later, when someone asks why the brand-new site isn't showing up in search at all. A debug log sits in a predictable place, readable by anyone. wp-content/debug.log collects whatever errors WordPress throws — database credentials, API keys, fragments of user data — in plain text, at a URL automated scanners check within hours of a new site going live. Turning debug mode off doesn't delete the file it already wrote. The admin username is still admin . It's the default nobody bothered to change, and it happens

URL already posted: https://health.aws.amazon.com/health/status I've got an estimated bill for $1.7 BILLION over this month. Normal usage is < $5. Obvs have created an urgent AWS support ticket. Anyone else seeing something like this? Update: Reddit link: https://www.reddit.com/r/aws/comments/1uyuaw7/help_my_bill_s...