The European Commission has slapped Temu with a €200 million ($232 million) fine for failing to prevent the sales of illegal products on its platform.

Wherever I go, whatever I do, people point at my finger and ask, "Is that an Oura Ring?" Lots of people find they like the design, and they tell me why they're thinking about switching to a smart ring from a smartwatch. But the people who scrunch up their noses? They usually say something along […]

I first realized there was an issue with Kia's flagship EV9 when I tried to unlock my car last year. The hulking three-row SUV was sitting on my driveway completely dead. The key didn't work, the app connection to the car was gone, and I was already late to an appointment. Luckily, I had prepared […]

The ring is 40% smaller than its predecessor, and comes with more accurate sensing, enhanced battery life, and more.

It’s slimmer, lighter, and more durable. But the real upgrade is Oura’s push into AI-powered health insights and proactive monitoring.

Oura describes its new wearable as the 'world's smallest' smart ring.

Learn how Endava uses Codex to build an agentic organization, accelerating software delivery and reducing requirements analysis from weeks to hours.

Reddit and X have reportedly received grand jury subpoenas from the Justice Department, seeking the identities of users who posted about ICE.

Temu has been fined €200 million (about $232 million) by the European Commission after it found that consumers are "very likely to encounter illegal items" on the popular Chinese e-commerce platform. According to the commission, Temu breached Digital Service Act (DSA) rules by failing to identify and assess the systemic risks of illegal products being […]

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

Hey all, we have a quick update for everyone who participated in the Gemma 4 Challenge. We were...

OpenClaw the open source AI agent platform with 346K+ GitHub stars had four chainable CVEs disclosed on May 15. But that was just the latest chapter. The crisis started in january and it's worse than most people realize. The numbers 245,000 instances exposed to the public internet (Shodan + ZoomEye scans) 30,000+ actively compromised and used by attackers (Flare) 1,184 malicious marketplace skills across 12 publisher accounts (Antiy Labs) 12% of the entire ClawHub marketplace was compromised 4 chainable CVEs including a CVSS 9.6 sandbox write escape (Cyera Research) 9 CVEs disclosed in a 4-day window in March 50,000+ instances exploitable via one-click RCE (CVE-2026-25253) The Claw Chain (Cyera Research, May 15) Four CVEs that chain together into a complete kill chain CVE-2026-44113 (CVSS 7.7) - TOCTOU filesystem read escape. Race condition lets you swap paths with symlinks to read outside the sandbox CVE-2026-44115 (CVSS 8.8) - Credential disclosure. Gap between command validation and shell execution leaks API keys through unquoted heredocs CVE-2026-44118 (CVSS 7.8) - MCP loopback privilege escalation. Trusts client-controlled senderIsOwner flag without session validation CVE-2026-44112 (CVSS 9.6) - Filesystem write escape. Same TOCTOU race in write ops. Backdoor placement on the host The chain malicious plugin -> read escape + credential theft -> privilege escalation -> persistent backdoor. Every step mimics normal agent behavior. Traditional monitoring cannot distinguish this from legitimate operations. ClawHavoc supply chain attack (Jan-Feb 2026) First malicious skill appeared January 27 By February 5, 1,184 malicious packages identified Skills disguised as crypto bots and productivity tools Installed keyloggers on Windows, Atomic Stealer on macOS 76 distinct malicious payloads ClawHub had zero verification for skill publishers until March 26 - eight weeks after the attack started Timeline Jan 27 - First malicious skill on ClawHub Feb 1 - Koi Security names "Cla

I've spent 18 months building agent infrastructure and watched a lot of impressive demos. Here's the uncomfortable pattern: the demo works beautifully, the founder posts it, everyone claps and then it touches real users and quietly dies. Not because GPT-5 / Claude / whatever isn't smart enough. The model is almost never the problem anymore. It dies for three boring reasons nobody wants to talk about because they're not sexy: 1. AMNESIA. Your agent forgets everything the moment the process restarts. Crash, redeploy, pod cycle gone. So everyone hacks together a pickle file or a Postgres table, and it works until they have more than one agent and the memory needs to be shared. Then it's a mess. 2. SUICIDE BY LOOP. An agent has no idea it's in a loop. It will call the same tool with the same args 400 times and cheerfully burn $200 of tokens overnight, because it has no metacognition. It literally cannot detect its own failure. The defense has to live OUTSIDE the agent and almost nobody builds that. 3. NO BLACK BOX. The agent does something weird in front of a customer. They ask "why did it do that?" and you stare at logs that show inputs and outputs but no chain of reasoning. You have no answer. Trust evaporates. The whole industry is obsessed with the brain (the model and ignoring the nervous) system (memory , the immune system (loop detection), and the flight recorder (audit).) The unsexy truth: the next wave of agent winners won't have better prompts. They'll have better infrastructure. The model is commoditising. The reliability layer is where the actual moat is. I got annoyed enough about this that I built the layer myself persistent memory, automatic loop detection, and a tamper-evident audit trail, framework-agnostic (LangChain/CrewAI/AutoGen/OpenAI/MCP . It's at) octopodas.com if you want to tear it apart genuinely want feedback from people who've shipped agents and hit this wall. But honestly even if you never touch my thing: stop optimising the prompt and star

I've been documenting some thoughts on stream plumbing in embedded systems, based on my own frustrations encountered while interfacing modules on constrained platforms. Mostly just an attempt to formalise patterns I've found to be working well recently. Interested in hearing how others approach this. submitted by /u/MickJC_75 [link] [留言]

AI bias mirrors human bias; both stem from our language and lived experiences. Ethics and AI are inseparable, but AI changes affordances, making harmful actions easier to carry out. The EU regulations apply to AI, since digital products are products. The ultimate goal is accountability: companies must ensure transparency, and laws should favor using the simplest AI that gets the job done. By Ben Linders

Google Home is rolling out a new Gemini-powered automation feature that can trigger smart home routines based on what your security cameras can see. This is one of several updates announced yesterday for Gemini for Home, including enhanced voice command support and general stability improvements, following its early access launch in October. "We are introducing […]

Created from fabric scraps that would otherwise end up in a landfill, this thoughtfully constructed bag looks great and can carry everything you need for a weeklong trip.

New mothers working in software development are staring down an AI-pilled workplace they barely recognize.