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Nvidia knows that DLSS 5 left a bad first impression. In March, many gamers took one look at Resident Evil Requiem protagonist Grace Ashcroft's DLSS 5-ified face and declared it AI slop. So this week, the company's re-introducing its controversial "neural rendering" with firm messaging about how it "preserves artistic intent," "respects the rendered frame," […]

Nvidia is officially launching DLSS 5 this week, following a divisive announcement in March where we likened the AI upscaling tech to a "real-time generative AI filter for video games" and "motion smoothing for video games, but worse." DLSS 5 will officially be available on RTX 50-series desktop and laptop GPUs and through GeForce Now […]

HashiCorp is positioning HCP Terraform as the governance and control plane for a new generation of AI-driven infrastructure, arguing that the rapid adoption of coding agents is shifting the biggest infrastructure challenge from writing configuration to verifying and safely executing it. By Craig Risi

Disclosure: I work on an access tool (Tessera), mentioned once at the end. Everything before that is about evidence, and applies whatever you use. The most common surprise in a first SOC 2 or ISO 27001 audit is not that a control is missing. It is that a control exists, works, and cannot be evidenced — so it counts as absent. The distinction is worth stating precisely, because it is not obvious until it has cost you something. A control is a thing that is true about your system. Only authorised engineers can reach production. Evidence is an artefact, produced by a system rather than by a person, that demonstrates the control was operating throughout the audit period — not on the day someone checked. Most organisations have decent controls. Most cannot produce evidence, because their controls live in places that do not emit artefacts: a bastion's authorized_keys file, a spreadsheet, a Slack thread where someone approved something, and the collective memory of three engineers. What gets asked for Reconstructed from what people have told me, this is the shape of the questions: "Show me everyone who could access production on 14 March." Not today. A specific date in the past, usually chosen by the auditor. This is the one that catches people, because most systems can tell you the current state and cannot tell you a historical one. authorized_keys has no history. A spreadsheet has whatever history git gives it, if it is in git, which it usually is not. "Show me that this person's access ended when their employment ended." Both timestamps, from two systems, matched. HR has the first. The second is the problem. "Show me the approval for this elevated access." Not that a policy requires approval — the specific approval, for this specific grant, with who approved it and when. "Show me what was done in this session." Increasingly common where production access to customer data is involved. Not "we log commands", but the actual record for a named session. "Show me that these c

Most email APIs are send-only. But if you're building an agent that needs to have a conversation over email — support, scheduling, invoicing — it needs to receive replies too, with thread context. In this post we'll set up an agent with its own mailbox using the Model Context Protocol. This is an official EngageLab Email tutorial, so feedback from developers is welcome. What you'll end up with An agent that sends email from its own address (not your personal inbox) Replies arriving as structured data the agent can read Conversation threads as a first-class object Step 1 — Get a Secret Key Create an EngageLab account and generate a Secret Key from the console (it looks like sk_sg_xxx — the prefix encodes the region). Or use the CLI to create one via browser login: npm install -g @engagelabemail/cli engagelab-email-cli login You'll also need a mailbox — create one in the console (shared subdomain is fastest to start; custom domains need DNS verification). Step 2 — Register the MCP server For Claude Code: claude mcp add engagelab-email \ -e ENGAGELAB_EMAIL_SECRET_KEY=sk_sg_yourkey \ -- npx -y @engagelabemail/mcp Or in claude_desktop_config.json : { "mcpServers": { "engagelab-email": { "command": "npx", "args": ["-y", "@engagelabemail/mcp"], "env": { "ENGAGELAB_EMAIL_SECRET_KEY": "sk_sg_yourkey" } } } } Step 3 — Talk to it Ask your agent: List my mailboxes, then send an email from the first one to me@example.com saying "invoice #42 approved", then check for new messages. The agent now has 9 tools: send, reply, list inbound mail, get a message, poll for new mail, and browse threads. Why a dedicated mailbox (not Gmail access) Blast radius: the agent can only read/write its own mailbox Threads: replies group into conversations, so the agent keeps context Machine-first: everything is JSON over MCP — no IMAP parsing Gotchas Sandbox mode ( sandbox: true in send_email) skips real delivery while you're iterating on prompts Attachments are base64 in the tool schema — fine for do

A WordPress database doesn't tidy itself up over time. Spam comments pile up, expired transients linger, post revisions accumulate, and tables left behind by uninstalled plugins never quite go away. All of that adds up to bloated tables, and occasionally to actual table corruption. This is territory the admin dashboard barely shows you — but WP-CLI reaches it directly with two short commands: wp db check and wp db optimize . Note: WP-CLI's wp db subcommands operate directly on the MySQL (or MariaDB) database WordPress uses, without going through the admin dashboard. Connection details are read automatically from wp-config.php . wp db check — verifying table health wp db check Under the hood, this runs the equivalent of mysqlcheck --check against every table and reports each one's status: wp_posts OK wp_options OK wp_postmeta OK If a table comes back corrupt , SELECT and INSERT queries against it start failing. That can surface as something oddly specific — a single page going blank, one particular post refusing to save — with no obvious connection to a database problem. Running wp db check on a regular schedule catches that kind of issue before it turns into a visible symptom. wp db optimize — defragmenting tables wp db optimize This one runs the equivalent of mysqlcheck --optimize , applying OPTIMIZE TABLE to each table. Tables that see a lot of row deletions and updates tend to become fragmented on disk over time. OPTIMIZE TABLE rebuilds the table and reclaims the space that deleted rows used to occupy. Note: behavior differs by storage engine. WordPress's default engine, InnoDB , handles OPTIMIZE TABLE internally as a table rebuild (roughly equivalent to ALTER TABLE ... FORCE ), which both defragments the table and refreshes its statistics. The older MyISAM engine doesn't reclaim space from deleted rows automatically at all — that disk space only gets released once OPTIMIZE TABLE runs. Some installs set up through a hosting provider's one-click installer still ca

Have you ever had a melody, lyric, or song idea stuck in your head but felt completely unqualified to...

The CDC has tallied nearly 30,000 confirmed and probable cases this summer.

In this post I'll show how to merge PDF files entirely in the browser using PDF.js and pdf-lib — no server, no file upload, no backend. Everything runs on the user's machine, which is great for privacy and for keeping hosting costs at zero (it's just a static site). Why process PDFs on the client? Most "free" PDF websites quietly upload your documents to their server, which: Exposes private/sensitive files to third parties Imposes size limits Often slaps a watermark on the output Requires you to trust their storage If you handle PDFs with client-side JavaScript (WebAssembly / WASM + PDF.js), none of that happens. The user's file never leaves their device, and you don't need a backend at all — so it's cheap and private. Caveats pdf-lib works well with standard PDFs; heavily encrypted or unusual documents may need extra handling. Very large PDFs are memory-hungry since everything is client-side, but for typical documents it's fast and free. Some complex PDFs with unusual fonts can lose fidelity — test on your own files first. Try it I packaged this approach (plus split, compress, rotate, unlock, image-to-PDF) into a free no-upload tool: https://yourutilityhub.com/pdf/merge-pdf The whole project is open source: https://github.com/Jalal-khn/utilityhub- If you have questions about the architecture or want a deeper dive on any part, ask away. The basic idea Read the input file with FileReader Parse it with pdf-lib (a pure-JS PDF library) Copy the source pages into a new document Save the merged PDF and trigger a download Here's the core function: js import { PDFDocument } from "pdf-lib"; async function mergePdfs(files) { const merged = await PDFDocument.create(); for (const file of files) { const bytes = await file.arrayBuffer(); const src = await PDFDocument.load(bytes, { ignoreEncryption: true }); const pages = await merged.copyPages(src, src.getPageIndices()); pages.forEach((page) => merged.addPage(page)); } const out = await merged.save(); return new Blob([out], { typ

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As frustration over AI influencers has been growing, Instagram is limiting the reach of undisclosed AI profiles.

Every developer writes code that "just works" thousands of times without thinking about what happens between hitting save and seeing output on screen. This article pulls back that curtain. We're going to walk through, in real depth, how source code — plain text you typed — becomes a running program, covering lexing, parsing, abstract syntax trees, semantic analysis, and the actual difference between interpretation and compilation (including why that difference is far blurrier than most explanations make it sound). This is one of those topics where understanding the fundamentals pays off across your entire career — it changes how you read error messages, how you reason about performance, and how you evaluate new languages and tools. 1. The Big Picture: Two Broad Strategies At the highest level, there are two strategies for running code: Compilation — translate the entire source program into another form (often machine code, but not always) before running it. The translation and the execution are separate steps. Interpretation — read and execute the source program directly, translating and running it (roughly) simultaneously, statement by statement. In practice, almost no real system is purely one or the other. Python "compiles" your source to bytecode before interpreting the bytecode. Java compiles to bytecode, then a JIT (Just-In-Time) compiler compiles hot paths of that bytecode to native machine code while the program runs . JavaScript engines like V8 do something similar. The clean binary of "compiled vs. interpreted" that gets taught early on is really a spectrum, and most production language runtimes today live somewhere in the middle. But to understand any point on that spectrum, you need to understand the pipeline every one of these systems shares. Let's build it up stage by stage. 2. Stage One: Lexical Analysis (Lexing / Tokenizing) The first thing that has to happen to your source code is the least glamorous: it gets chopped into pieces. Source code, to a c

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. By now you’ve probably heard about last month’s major AI security incident, in which OpenAI agents escaped their sandbox and hacked into the AI platform Hugging Face while trying to cheat on…

In exchange for free stuff, devices make home connections part of a proxy network.

In our world of expensive streaming platforms, the very free and offline VLC media player has crossed 7 billion downloads.

What actually changed You built a custom n8n node with its own credential type. The node works in a workflow. You open the credential in the n8n UI, click Test , and instead of a green checkmark you get: No testing function found for this credential. You double-check the node — credentialTest is defined in methods , testedBy is set on the credential declaration, everything compiles. n8n just refuses to see it. This is one of the most-reported custom-node issues in n8n's history — the original report is Stack Overflow q/75109822 and the underlying bug is tracked in n8n-io/n8n#8188 , with users still reproducing it on 1.58+ and 1.94 well after the original fix landed. The fix The root cause is not a missing function. It is in LoadNodesAndCredentials.ts : n8n generates nodesToTestWith in dist/known/credentials.json but only reads supportedNodes when linking a credential to its test function. For custom and community nodes the two keys never match, so the linkage is dropped and the UI shows the "no testing function" message. The fix that survives across n8n versions is to stop relying on credentialTest on the node and instead define the test directly on the credential class as an ICredentialTestRequest . Before — the linkage that breaks // credentials/MyApi.credentials.ts import { ICredentialType , INodeProperties } from ' n8n-workflow ' ; export class MyApi implements ICredentialType { name = ' myApi ' ; displayName = ' My API ' ; // ❌ testedBy points at the node's credentialTest, which the loader // never resolves for custom/community nodes. testedBy = ' MyApiNode ' ; properties : INodeProperties [] = [ { displayName : ' API Key ' , name : ' apiKey ' , type : ' string ' , typeOptions : { password : true }, default : '' , }, ]; } // nodes/MyApi.node.ts export class MyApiNode implements INodeType { methods : INodeTypeMethods = { credentialTest : async ( credentials ) => { // n8n never calls this for a custom node. const res = await fetch ( ' https://api.example.com/me '

Nvidia invests $3.5 billion into Taiwanese chipmaker MediaTek. The deal shows how Nvidia plans to stay essential to AI infrastructure as Big Tech begins to build its own AI chips.

The app isn't cracking down on other kinds of AI slop, though.

Instagram is finally taking steps to address the rise of fake AI-influencer accounts that have gotten harder to spot. It's also renaming the "AI creator" label to "AI-generated profile" to make it clear when a profile features an AI-generated person that's not a real human being. "We've heard that people don't like seeing a profile […]

In eleven days, on 11 September 2026, the reporting obligations of the EU Cyber Resilience Act start applying to anyone who puts a product with digital elements on the European market. Not the full regulation. Just the part where, if you find out an actively exploited vulnerability is in your product, you have 24 hours to tell ENISA about it. I have watched a lot of engineering teams meet this class of deadline for the first time. It usually goes the same way. Somebody in sales gets a security questionnaire. Somebody in engineering gets forwarded the questionnaire. Three weeks later there is a shared folder called evidence-final-v3 with 200 screenshots in it, and nobody can tell you which screenshot answers which question. I have spent the last several months building a tool whose entire job is that folder, so I read the instruments properly. This is what I found out. It is written for engineers, not for a compliance team, and I try to be specific about what the text says rather than what a vendor blog says it says. Where SOC 2 came from, and why that still shapes it SOC 2 exists because of a misuse. In 1992 the AICPA published SAS 70, an auditing standard for service organisations. Its purpose was narrow: if you outsourced your payroll, your auditor needed some assurance that your payroll provider's internal controls did not corrupt your financial statements. It was an accounting instrument, for accountants, about financial reporting. Then the industry outsourced everything else. By the mid-2000s companies were sending their customer data to service providers, and they wanted assurance about that , not about financial reporting. There was nothing designed for it, so they asked for the thing that existed. Vendors started waving SAS 70 reports around as proof they were secure. They were not proof of that. SAS 70 had no defined control set at all: the service organisation wrote its own control objectives, and the auditor tested against whatever had been written. Two S