Underneath an Apennine massif, below the Jinping Mountains of Sichuan, and at the bottom of a South Dakota mine, there is a cosmic hunt afoot. Isolated deep beneath these rocky shields, massive detectors filled with liquid xenon aim to make the first direct detections of dark matter, the long-sought invisible substance whose gravity has sculpted…

Wellness influencers have stumbled onto a huge issue when it comes male fertility, though not every solution they're pitching is good advice.

The A2A protocol is an agent to agent protocol from Google. I was looking at it 6 months back but it didn't feel like I really understood how to use it at that point. Probably because we were all still trying to figure out agents and then the MCP protocol became quite a big deal. But now I'm starting to think that once an agent has tools and services and data and then contacts. Actually, the point of interaction becomes the agent itself and then if you build other agents you would want them to i

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Why your brain learns faster by doing than by studying, and the neuroscience that explains...

Cybersecurity firm Chainguard has announced the launch of Athena, an industry coalition to use artificial intelligence to find and fix vulnerabilities in widely-used open-source software before attackers can exploit them. The coalition focuses on libraries, containers and other components that underpin web browsers, data centres, smartphones and payment systems. By Matt Saunders

Researchers used an OpenAI reasoning model to help diagnose rare diseases, identifying 18 new diagnoses in previously unsolved cases.

I'm here looking through logs on my unnamed reverse proxy and CDN service. The crawler bot swarm has been hitting my PHP application like I've upset them so I'm seeing which weird user agent strings are being allowed to connect. There's "Sogou" and "meta-webindexer" and a small number of requests from "SleepBot/1.0" What's SleepBot? The ASN is Google and the UA string is: "Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; SleepBot/1.0; +http //sleepbot com/) Chrome/131.0.0.0 Safari/

Hey all! I'm the maintainer of mistral.rs. I just landed support for OpenAI-compatible Agent Skills via a /v1/skills endpoint, and it works with local open models. Until now Skills have basically been locked to closed models, and with the ability to have private, local intelligence becoming increasingly important, but this feature allows you to do XYZ with local models. It's fully compatible with OpenAI's /v1/skills API, so you can drop mistral.rs into your existing code with minimal difficulty.

When organizations scale, a simple monolithic architecture often becomes difficult to maintain, deploy, and scale. This is where microservices come into the picture. However, moving to microservices introduces new challenges: How do we migrate from a monolith safely? How do we handle transactions across multiple services? How do we scale read-heavy applications efficiently? Three popular patterns solve these problems: Strangler Pattern – Monolith to Microservices Migration Saga Pattern – Distributed Transaction Management CQRS (Command Query Responsibility Segregation) – Read/Write Scalability 1. Strangler Pattern Why Do We Need It? Most companies cannot shut down a production monolith and rewrite everything from scratch. A complete rewrite is risky because: Development takes a long time. Existing customers are affected. Bugs can impact business operations. Rollback becomes difficult. The Strangler Pattern allows teams to migrate gradually with minimal risk. What Is It? The Strangler Pattern is a migration strategy where new microservices slowly replace parts of a monolithic application until the monolith is no longer needed. The name comes from the strangler fig tree, which gradually grows around another tree and eventually replaces it. How Does It Work? [Insert diagram here showing Client → API Gateway → Monolith + Microservices] Step 1 All requests go to the monolith. Client | v Monolith Step 2 Introduce an API Gateway (or Controller). Client | v API Gateway | v Monolith Step 3 Extract one module into a microservice. Client | v API Gateway |------> Order Service | v Monolith Step 4 Gradually move more modules. Client | v API Gateway |------> Order Service |------> Payment Service |------> Inventory Service | v Monolith Step 5 Eventually remove the monolith completely. Example Consider an e-commerce application. Initially, everything exists inside one application: Monolith ├── Orders ├── Payments ├── Inventory └── Users Over time: Orders become Order Service Payme

Google's demo reel for Gemini Omni looks effortless: ask for a video, then keep talking to it until the shot is right. The question for developers is whether that conversational loop holds up outside a stage demo — and what it actually changes versus the Veo workflow it replaces. What Does Omni Add That Veo Couldn't? Omni's core addition is state. Veo produced one-shot renders — each prompt generated a fresh clip with no memory of the last. Gemini Omni holds context across turns, so changing the camera angle on turn three preserves the characters and lighting established on turn one without restarting the scene . Announced at Google I/O on May 19, 2026, the first shipped model, Gemini Omni Flash, replaces Veo as the video-generation surface in the Gemini app . Product director Nicole Brichtova framed it as "the next step towards combining the intelligence of Gemini with the rendering capabilities of our media models" — DeepMind's informal pitch is a "Nano Banana for video," extending conversational image editing to motion footage. Two claims deserve a skeptical read. Google advertises "intuitive understanding of forces like gravity, kinetic energy, and fluid dynamics," but those physics behaviors currently rest on Google demos and creator footage, with no third-party benchmarks published at launch . And on raw output, independent reviewers put Omni's generation quality on par with Veo 3.1 rather than clearly above it . The differentiation is the iterative editing loop and Gemini-grounded reasoning — not a new render engine. Before Starting: Paid Membership, Region, Age Omni access is gated behind a paid Google AI plan and a few hard eligibility rules, so confirm these before you open a prompt. Gemini Omni Flash unlocks in the Gemini app and Google Flow for Google AI Plus, Pro, and Ultra subscribers, with Plus starting at $7.99/month . If you want to test it for free, generation is available at no cost on YouTube Shorts and the YouTube Create App at launch . Two cons