标签：#c

If you have ever stared at a misbehaving circuit at two in the morning, muttering about the "bug" you cannot find, you are part of a lineage that runs back to a very literal insect. On September 9, 1947, engineers working on Harvard's Mark II computer opened up the machine, found a moth wedged inside a relay, and taped it into their logbook. The note beside it reads: "First actual case of bug being found." It is one of the most charming artifacts in the history of computing, and it carries a surprisingly practical lesson for anyone who builds connected hardware today. What actually happened in 1947 The Mark II was an electromechanical monster: a room-sized calculator built from thousands of relays, switches that physically clacked open and closed to represent ones and zeros. On that September day the machine was producing errors, and the operators -- part of the U.S. Navy computing effort that Grace Hopper worked in -- traced the fault to Relay #70 in Panel F. Inside was a moth, its wings shorting across the contacts. They removed it, taped it into the logbook at 15:45, and recorded the now-famous line. That page, moth still attached, lives today in the Smithsonian's National Museum of American History. Hopper loved telling the story for the rest of her career, which is why her name is forever attached to it. She is often credited with coining "bug" and "debugging" because of that moth, but the honest history is a little different, and the difference is the interesting part. The word "bug" was already old Engineers had been calling faults "bugs" for decades before 1947. Thomas Edison used the term in an 1878 letter to describe the little glitches and "difficulties" that show up when a new invention meets the real world. By the early twentieth century "bug" was common shop-floor slang among electrical and telephone engineers. So the moth did not invent the word. What made the logbook entry so memorable is the joke buried in it: "first actual case of bug being found"

A few weeks ago I wrote about describing your site once so any AI can use it. Since then the thing I was hand-waving at ("agents will check out for users") stopped being hypothetical. OpenAI shipped ACP and Google shipped AP2, and they solve the same problem in almost opposite ways. I implemented the merchant side of both. Here are the field notes, because the differences aren't obvious until you're in them. The 30-second version ACP (Agentic Commerce Protocol, OpenAI + Stripe) is session-based. The agent drives a live checkout session on your server, like a headless cart. It powers ChatGPT's Instant Checkout. AP2 (Agent Payments Protocol, Google) is mandate-based. Your store signs a "here is the cart and the price" object; the buyer's agent signs a "I authorize this" object. It leans on verifiable credentials and now the FIDO Alliance. Same goal. Completely different shape. ACP: a checkout session you don't own the UI for ACP is five REST endpoints and a state machine. The agent creates a session, updates it (address, shipping, coupon), and completes it: POST /checkout_sessions create from line items POST /checkout_sessions/:id update (address, shipping, discounts) POST /checkout_sessions/:id/complete pay What you return is a CheckoutSession: line items, live shipping options, and totals broken out (subtotal, discount, fulfillment, tax, total). Money is integer minor units (330 = $3.30). Payment completes when the agent hands you a Shared Payment Token and you charge it through Stripe. The card never touches the agent. The mental model: it's your existing checkout, minus the browser. AP2: sign the cart, don't run the session AP2 has no session. The agent sends you an Intent Mandate ("a red basketball shoe, under $120"). You price it and return a Cart Mandate you have cryptographically signed: { "contents" : { /* a W 3 C PaymentRequest: items , total , currency */ }, "merchant_authorization" : "<RS256 JWT>" // iss , sub , aud , exp , jti , cart_hash } That JWT is a

We’re open-sourcing Browser Tools SDK: a small TypeScript package to give any AI agent a reliable way to control a real browser. With just a few lines of code, you can give any agent a production-ready browser harness import { createAiSdkBrowserTools } from "libretto-browser-tools/ai-sdk"; import { LocalBrowserProvider } from "libretto-browser-tools"; const { tools } = createAiSdkBrowserTools(new LocalBrowserProvider()); const result = await generateText({ model: anthropic("claude-sonnet-4-5"),

Australia was the first country to issue a ban in late 2025, aiming to reduce the pressures and risks that young users may face on social media, including cyberbullying, social media addiction, and exposure to predators.

OpenAI has come forward to claim responsibility for the Hugging Face breach, saying it was the result of internal testing gone awry.

OpenAI has come forward to claim responsibility for the Hugging Face breach, saying it was the result of internal testing gone awry.

Hey friends! Brad here - long time HN user, founder, engineer (Coinbase, Soothe, Jeevz, Release, Hired, GrowthX, etc)... I have been struggling recently with too many tabs, emails, articles, etc sitting unread while I swap between Claude code sessions all day. So I decided to build Orate to help me work through the backlog by listening to it all like I would a podcast. Orate allows you to select any text on your screen and keyboard shortcut it to a listening queue where it gets processed using t

Fine-tune and Deploy Open-weight Models in TypeScript Discussion | Link

Your database, safe for agents to query Discussion | Link