Anthropic accused of spying on users; engineer says “experiment” is over.

It’s been 10 years since we had the last leap second and it looks like we will get the first negative one soonish. Are systems ready for that?

Talk Once. Publish Everywhere. Discussion | Link

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Get excited for a feature film starring an AI character that doesn't exist in any real way.

Microsoft is spinning off four of its Xbox game studios - Compulsion Games, Double Fine Productions, Ninja Theory, and Undead Labs - as part of the restructuring announced today. However, two that are going independent, Double Fine and Compulsion, will get to keep their franchises and games catalogs, according to Xbox CEO Asha Sharma. "Compulsion […]

Apple has started a phased rollout of card payments for Apple Account purchases in India after adapting to the country's payments framework.

Hey HN, I'm Shreyash, founder of Feyn. We built Pulpie, a family of Pareto optimal models for cleaning the web. Pulpie strips boilerplate (ads, footers, sidebars) from raw HTML and returns just the main content as HTML or Markdown. We match SOTA extraction quality while being 20x cheaper. Cleaning 1 billion webpages costs $7,900 with Pulpie versus $159,000 with Dripper, the current leading extractor. The gains come from architecture. Today's leading extractors are decoders that generate output o

Move affects ~20% of the gaming division, which will refocus on its biggest franchises.

Originally published on satyamrastogi.com Seqrite Labs identifies multi-stage DcRAT campaign impersonating India's Income Tax Department. Attackers exploit tax professional workflows to deliver remote access trojans capable of data exfiltration and lateral movement. Operation DragonReturn: DcRAT Deployment via Fake ITR Utilities Executive Summary A China-nexus threat cluster is actively exploiting the predictable workflows of Indian tax professionals, corporate finance teams, and individual taxpayers through phishing campaigns distributing DcRAT (Dark Crystal Remote Access Trojan). Operation DragonReturn, as tracked by Seqrite Labs, demonstrates sophisticated understanding of Indian taxation cycles and organizational structures - critical operational intelligence required for high-success-rate social engineering. From an attacker's perspective, this campaign is methodologically sound: it targets a specific, predictable event (tax filing deadlines), uses trusted entity impersonation (Income Tax Department), and deploys a mature RAT with established evasion capabilities. The selection of DcRAT indicates access to commodity malware-as-a-service (MaaS) infrastructure, likely from Chinese underground forums where such tools are actively monetized and continuously updated. Attack Vector Analysis This operation chains multiple MITRE ATT&CK techniques into a cohesive infection chain: Initial Compromise: Spear-Phishing with Pretexting Attackers execute T1566.002 (Phishing - Spearphishing Attachment) by crafting emails impersonating legitimate Indian Income Tax Department communications. The social engineering layer leverages T1598.003 (Phishing - Spearphishing Link) with URLs pointing to malicious tax filing utilities. Pretexting is enhanced through T1589.001 (Gather Victim Identity Information - Credentials) , as attackers likely harvested tax professional contact lists from public records, LinkedIn OSINT, or previous data breaches. The timing of campaigns around Indian fis

I've long argued that Hollywood has simultaneously set and ruined our expectations for smart glasses. But after binge-watching two seasons of Netflix's A Man on the Inside, this is perhaps the first time I've seen Hollywood, perhaps inadvertently, illustrate the biggest cultural problem with smart glasses as they stand today. In a nutshell, Ted Danson […]

For internal websites, client portals, development environments, and WordPress projects that should not be publicly accessible. Not every private WordPress website needs a complete membership system. Sometimes there is no need to manage subscriptions, membership plans, payments, complex user roles, or dozens of content-access rules. Sometimes the requirement is much simpler: The website should only be accessible to logged-in users. That is the reason I created Supracorona Login Gate , a lightweight WordPress plugin that places a simple access gate in front of a website. When the plugin is enabled, logged-out visitors cannot browse protected site content. Instead, they are redirected to the standard WordPress login page or to a custom page selected by the site administrator. The plugin is now published on WordPress.org: Supracorona Login Gate The problem the plugin solves Many WordPress projects are not intended to be publicly accessible at every stage of their lifecycle. They may be: development or staging websites; internal company or organization websites; client portals; private knowledge bases; documentation websites intended only for team members; projects being prepared for launch; demo websites available only to selected users; websites temporarily closed during migration or reconstruction. WordPress provides privacy controls for individual posts, but that is not the same as restricting access to the entire website. Installing a full membership plugin is possible, but it is often far more than the project requires. Such systems may introduce additional database tables, large settings panels, custom profiles, login forms, subscription management, and complex rule engines that will never be used. Supracorona Login Gate has a much narrower responsibility. It is not intended to become a complete membership platform. It is intended to answer one clear question: Is the current visitor logged in? When the answer is yes, the website behaves normally. When the answer

Orasort, a sorting algorithm from Oracle, came into the public domain in 2024 after its patent expired, providing massive benefits to open-source software. submitted by /u/Ok_Stomach6651 [link] [留言]

In this blog post, we will see how to performance test a RAG (Retrieval-Augmented Generation) application properly, covering both speed and correctness, and how to wire both into a CI/CD pipeline so regressions get caught before they reach production. Performance testing a RAG application requires two separate testing gates: one for speed and one for answer quality. Traditional load testing tools measure response times but cannot detect hallucinations, where a model returns fast but factually incorrect answers grounded in fabricated context rather than retrieved documents. The guide demonstrates using k6 for load testing end-to-end latency and DeepEval for evaluating faithfulness and answer relevancy using an LLM-as-judge approach. Both gates are integrated into a GitHub Actions CI/CD pipeline so regressions in either performance or output quality are caught automatically on every pull request before reaching production. If you've come from a JMeter or k6 background like I have, your first instinct with a RAG endpoint is probably to point a load test at it and check response times. That gets you halfway there. A RAG app can return a fast, confident, completely wrong answer, and a plain load test will never tell you that. You need two testing surfaces, not one: performance and quality. This guide covers both, using a single running example throughout: a documentation assistant that answers "How do I run JMeter in non-GUI mode?" against a small knowledge base. Why RAG breaks traditional load testing assumptions A conventional API returns a complete response and you measure the round trip. A RAG endpoint does two expensive things before it answers: it retrieves context from a vector store or search index, then it streams a generated response token by token. That second part matters a lot. A single request can stream hundreds of tokens over several seconds, so "request duration" as a single number hides two very different problems: how long the model took to start answe