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AI 资讯 Dev.to

Make the Fake Impossible

Every patient in the public tour of my care platform is a computer science pioneer. Ada Lovelace has a pain score. Alan Turing is due for a check-in. And every one of them has a patient ID no real system could ever issue, an ID that is wrong the way a date in month thirteen is wrong. None of this is an accident. It is the most useful compliance idea I have had this year. A good fake is a liability Here is the problem with realistic demo data. Under HIPAA, nobody can tell a well-made fake from the real thing by looking. A screenshot of a fake patient named John Smith with a plausible ID looks exactly like a screenshot of a real one. So when that image turns up in a deck, or a tweet, or a forwarded email, someone has to prove it is clean. And the only way to prove it is to go back to the database and show the record does not exist. That is an audit. Every plausible fake carries a future audit inside it. So a good fake does not reduce your risk. It just moves it. The better the fake looks, the more it costs to prove it is one. The safety of a fake is not in how real it looks. It is in how obviously fake it is. A plausible fake needs an audit to clear it. An impossible fake clears itself. The fix is to stop making fakes plausible and start making them impossible. A patient named Grace Hopper with an ID that breaks the format on sight cannot be a real record. Anyone can check that from the pixels alone. No lookup, no audit trail, no meeting. Zero pixels The public showcase at clearpathcare.ai contains zero pixels from the production console. Every screen is a React recreation, rebuilt by hand to look like the product without ever touching it. What broke: An early draft of the marketing screens started as console screenshots with seeded test patients: realistic names, realistic IDs. Then I asked one question the images could not answer: prove there is no real record in this frame. I could not. So I deleted every screenshot and rebuilt the screens from scratch. The rebuilt

Nabbil Khan 2026-07-19 02:20 6 原文
AI 资讯 Dev.to

How I make ffmpeg hit an exact file size (the bitrate math nobody explains)

Every few weeks I hit the same wall: I have a 300 MB screen recording, and something on the other end wants it under 8 MB . Discord, an email attachment, a bug tracker, a form that silently rejects anything bigger. The usual advice is "just use HandBrake" or "run ffmpeg with a lower CRF." But CRF doesn't take a target size — it takes a quality knob . So you export, check the size, it's 11 MB, nudge the knob, export again, now it's 5 MB and looks like a potato, nudge back… It's a binary search you run by hand, one full encode per guess. The thing is, hitting an exact size isn't a guessing game at all. It's arithmetic you can do before you encode. I ended up wrapping that arithmetic into a little Rust CLI ( DeepShrink ), but the math is the interesting part, and almost nobody writes it down. So here it is. The one insight everything rests on File size is (roughly) bitrate × duration . A bitrate is bits per second. A duration is seconds. Multiply them and the seconds cancel, leaving bits — the size of the file. That's it. That's the whole trick. Normally you treat bitrate as the input and size as whatever falls out. Flip it around: fix the size, measure the duration, and solve for the bitrate. You know the duration (ffprobe will tell you), and you know the size you want (the platform's limit). The only unknown is the bitrate — and now it's a single division away. bitrate = size_in_bits / duration_in_seconds Everything below is just this equation with the real-world messiness added back in. Building the budget, step by step Say I want a 60-second clip to fit Discord's 8 MB limit. 1. Turn the target size into bits. Sizes are in bytes, bitrate is in bits, so multiply by 8. (I'll use 1 MB = 1,000,000 bytes here to keep the mental math clean; if your platform means mebibytes, same method, different constant.) target_bits = 8_000_000 bytes × 8 = 64_000_000 bits (64 Mbit) 2. Reserve a little for container overhead. An .mp4 isn't pure video and audio — there's a container, a m

Alexander Pervushen 2026-07-19 02:18 8 原文
AI 资讯 Dev.to

riding the wave of ai

I remember when coding interviews happened at a whiteboard, no computer, no internet, just a marker and whatever you could hold in your head. When AI tools arrived, using one in an interview was the red flag. Now the red flag is the candidate who doesn't use AI enough. In about two years, the same tool went from forbidden to expected. And it only gets faster. Every few months another wave rolls in, a model out of some lab, a tool that does something it couldn't last year, and it resets what counts as normal. You ride it, or you let it break over you. Plenty of people imagine a third option, waiting on the beach with their arms crossed until the water goes calm, but the water never goes calm, and it was never going to wait for them. all in I've decided to ride it, in the most literal way I have. All of my code is written by AI now (is it mine at this point?), and somewhere along the way I stopped treating that as a threat to be managed and started treating it as leverage to be spent. I know the engineers who went the other way, who made a personality out of dismissing the tools, and the tools got better anyway while they just fell further behind. Going all in wasn't one decision; it's one I make again every few weeks. A better model ships, and I rebuild a working agent on top of it instead of staying on the old version, because the result comes out better and cheaper. Relying on older models would have been easier, and most people do. Riding means doing that over and over, long after the novelty wears off. I get why people stop trying to keep up. The volume is genuinely insane, more launches in a week than you could try in a month, and it isn't only engineers feeling it now, it's anyone whose work runs on a keyboard. People are overwhelmed and often giving up. But you don't have to keep up with everything; you just can't ignore it all. keep the thinking It means handing a lot of work to AI, and I hand over more every month. It writes code, drafts the first version of

Adi 2026-07-19 02:18 7 原文
AI 资讯 The Verge AI

Google is open-sourcing its 3D emoji

Now, if you want to, you can use Google's 3D emoji in your own creations. The company shared some details about how it went about designing the little pictograms and why, as part of World Emoji Day on Friday. Things you might not necessarily worry about in a 2D illustration suddenly become very important when […]

Terrence O’Brien 2026-07-19 00:40 7 原文