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Trump’s dumb border wall

About 22 miles south of the former mining town of Patagonia, Arizona, down a winding, unpaved mountain road that passes cows grazing on open range, stands a cottonwood tree believed to be at least 200 years old. The "grandmother" tree, as some locals call it, is imperiled and already showing signs of stress, almost as […]

2026-08-18 原文 →
AI 资讯

Uber partners with Zipline on Eats drone deliveries

Uber is teaming up with drone company Zipline to start airborne takeout deliveries later this year, with the goal of reaching one million daily drone deliveries by 2029. Uber also said it was making a strategic investment in Zipline, a California-based company that has been orchestrating drone deliveries in Texas since 2025. The news comes […]

2026-08-17 原文 →
AI 资讯

Anthropic explains how Claude’s invisible text watermarks will work

Anthropic has clarified how it's planning to apply invisible watermarks to Claude-generated text in order to comply with Europe's AI transparency rules. On Friday, Anthropic announced that Claude's text marking system is "a version of the SynthID-Text approach" - an open-source watermarking technology developed by Google DeepMind that creates detectable patterns using wording probabilities. This […]

2026-08-17 原文 →
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I’m hooked on Peak Design’s new City bags

It's just a hook, sewn into a bag, but I really, really like it. Peak Design is so proud of its clever integration that the San Francisco-based maker of camera gear gave it a name: BagLev, for its ability to keep its new City Line of bags levitated above the dirty ground. How many of […]

2026-08-17 原文 →
AI 资讯

OpenAI reportedly disbanded its preparedness team

According to the Financial Times, OpenAI disbanded its preparedness team at the end of last month. The job of the preparedness team was to assess if models posed serious risks and develop ways to mitigate those risks. (You know, like the possibility that it could go rogue and hack another company.) According to FT, responsibility […]

2026-08-17 原文 →
AI 资讯

Rogue AI aren’t science fiction anymore

This is The Stepback, a weekly newsletter breaking down one essential story from the tech world. For more on AI safety, follow Robert Hart. The Stepback arrives in our subscribers' inboxes at 8AM ET. Opt in for The Stepback here. How it started It all started in July, when one of OpenAI's autonomous AI agents […]

2026-08-16 原文 →
AI 资讯

Tenant-Aware Speech-to-Text Explained — MP3/WAV File Uploads Across US/EU in 2026

Short answer: for a small fintech product that turns reviewer voice notes into structured code findings, start with one synchronous speech-to-text file-upload adapter for MP3 and WAV, but write every upload to a tenant ledger before making the transcription request. That is usually the fastest integration because it keeps the first release small while preserving per-tenant cost visibility and a clean path to regional routing. Choice Shipping effort Tenant attribution Best fit Main constraint Direct file upload Lowest Clear with an internal ledger Short reviewer notes Bound by the selected API's request and duration limits Object storage plus async worker Medium Clear with job records Long or bursty recordings More states to operate Self-hosted transcription Highest Fully internal Strict control requirements or sustained workloads Model serving becomes your job My recommendation is the first row for the initial release. Keep the adapter replaceable, measure billed units rather than guessing from file size, and promote work to a queue only after real upload patterns justify it. The point isn't to find a universally fastest model. It is to ship weekly without losing the tenant-level evidence needed to understand margin. How should a simple speech-to-text API handle MP3 and WAV file uploads? Treat the upload as a business event, not as an anonymous call to an AI endpoint. Before sending any audio, create an internal record with tenantId , changeId , uploadId , media type, byte count, selected processing region, and a start timestamp. After transcription, add the external request identifier when one exists, the terminal status, and the billable unit reported by the selected service. A byte count is useful for capacity planning; it is not a substitute for actual billing data. That distinction matters in a multi-tenant SaaS. One tenant may submit many short WAV notes, while another submits compressed MP3 files with longer conversations. Charging, margin analysis, and abuse

2026-08-16 原文 →
AI 资讯

Claude Impact Lab LA: Community Changed the Code

Eighty minutes into building with three people I had met that morning, I renamed the idea I brought with me. 21:05 Rename the product to Civiq and credit the team I wrote that commit message myself. By then the idea had four authors. Some context on the room. The Claude Impact Lab is part of Claude Community, the run of local events where people who use Claude get together in person. This one followed a Claude Conversation held earlier in Los Angeles, where people talked through what AI is doing to their jobs. The Impact Lab takes what came out of that conversation and turns it into a build day. You get the problem brief, you form a team, you have the day, you demo at the end. Travis Johnson, a Claude community ambassador, hosted with Evan Grenda at Intersections LA. Developers and non-developers both, and they meant it. What I brought was not a project. It was an idea and a spec for it. No code, nothing built, nothing running. The idea comes out of something that is true in most cities. Your city government publishes what it intends to do before it does it. Agendas go up ahead of the meeting, and any resident can read them, show up, and speak on an item before the vote. That right exists. Using it takes work, which is probably why every time I used it I would give up on what I was looking for. In Ventura it means 21 separate boards and commissions, each with its own page, posting PDFs that run long and read like they were written for the people already familiar with the subject matter. Because they were. So if you want to know whether anyone is voting on something a block from your house, you go looking, board by board, document by document. And you have to already know the words the city uses for the thing you would call a pothole. Agenda Watch was going to make all of that searchable in plain language, with every answer carrying a receipt back to the page it came from, so nobody has to take the tool's word for anything. In use that is a small thing. You ask a que

2026-08-16 原文 →