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This unpronounceable series of glyphs is an incredible side project from Kieran Hebden (aka Four Tet)

Just why? ʅ͡͡͡͡͡͡͡͡͡͡͡(̸̢̛̼̞̭͋ͅ)̸͚̰͛̔̾̀̿͒͂:̴͓̞̑̌̂̆̊͋̀:̸͎̟̯̂̓̌ ҉ ͡ ͞ ͞ ͞ ҉● ࿀ ● ࿀ ● ҉⃝ ⃝͢ ͞ ͘ ͞⃝̕ ͢ ̛ ⃝ ̸ ̡ ͢⃝̧ ͡ ͡ ̀ ̧ ̢⃝͜ ҉ ͞ ͞ ⃝͞ ͞ ͡⃝ ⃝҉҈҉҈҉҈҉҈҉҈҉ :̶̢͙͙͕̠̩͆(̷̮͍͚̫͚͂̍)̵̳̗̊( ̟̞̝̜̙̘̗̖҉̵̴̨̧̢̡̼̻̺̹̳̲̱̰̯̮̭̬̫̪̩̦̥ What am I supposed to do with this? It's un-Googleable. Unpronounceable. It doesn't even render the same way on various platforms. It looks one way on YouTube Music. Another on Apple Music. And yet another on Bandcamp. Even the artist name ⣎⡇ꉺლ༽இ•̛)ྀ◞ […]

2026-07-20 原文 →
AI 资讯

I hate that I don’t hate this song made with Suno

I would never go so far as to say there's no place for AI in music (I'm a fan of Holly Herndon, after all). But I generally find music made with generative AI to be offensively boring, especially the outputs of Suno. So I'm having a bit of a tough time processing the fact that […]

2026-07-20 原文 →
AI 资讯

The Difference Between a Review and an Advert

The line between editorial content and paid promotion has been eroding for years. On most major retail platforms, in countless lifestyle publications and across the breadth of social media, content that presents itself as independent assessment is frequently underwritten by the very brands being assessed. This is not a new problem, but it is a worsening one. The consequences are practical. Consumers who believe they are reading a review and acting accordingly may be making purchasing decisions on the basis of what is, in effect, an advertisement. The financial cost of that mistake is modest in most individual cases. The cumulative effect on consumer trust is not. Understanding what separates a genuine review from disguised promotional content requires more than checking for a disclosure label. It requires looking at structure, incentive, methodology and language - and recognising that some of the most effective adverts are those that most convincingly resemble reviews. What a Review Is Actually Supposed to Do A review serves one primary function: to help a reader make an informed decision about a product, service or brand. That function is incompatible with advocacy. A reviewer who is trying to help a reader decide cannot simultaneously be trying to persuade that reader to buy. This distinction sounds obvious. In practice, it collapses quickly when the person writing the review has a financial relationship with the brand, when the product was provided free of charge without conditions, or when the publication depends on advertising revenue from the sector it covers. None of those arrangements automatically invalidates the content produced. But each one creates a structural incentive that pushes in a specific direction - and that direction is rarely towards harder scrutiny. The Disclosure Problem Regulatory frameworks in the UK, including guidance from the Advertising Standards Authority and the Competition and Markets Authority, require that paid-for content be clea

2026-07-19 原文 →
AI 资讯

Orchid is a delightfully retro and approachable hipster synth

In 2017, I bought an old Magnus chord organ off Craigslist for $10. It's one of my favorite music gear purchases. Electric chord organs let you play full chords with just a press of a button, making them perfect for aspiring singer-songwriters or fooling around at home. But chord organs largely fell out of favor […]

2026-07-19 原文 →
AI 资讯

The AI hype is a mass psychosis echo chamber of incompetent individuals

I don’t log in to my LinkedIn account anymore, haven’t done so in years. “AI first this, AI driven that,” alright, alright, I get it! You guys absolutely love AI, and I can’t stand the fact that after almost 5(!!!) years, people still talk about it like it’s the best thing since chicken nuggets. Back when LLMs have started showing somewhat positive results when it came to generating less-than-average code, I came to a devastating conclusion: My friends and colleagues might not actually enjoy coding at all. Maybe they just didn’t enjoy coding the way I do—but either way, I was extremely sad and actively burnt out to find that everybody around me jumped on the prompting bandwagon without giving it much of a critical second thought. I could argue that it was partially because of their employers, but it was definitely because they chose and wanted to. They pressed me “It’s the future, aob2f, we don’t need to write code anymore.” “I just tell Claude to do it, and it’s done.” “I don’t write a single line of code anymore, don’t be left behind.” Some even outrageously claimed “Yeah I reviewed Claude’s 40k lines PR in two days, it was good.” I was baffled. Was I in this sick, absent-minded Truman show spinoff? Were these the same smart, even genius individuals that have built and driven the world’s innovation in the past 30 years with their own hands and minds? It got to a point where I started doubting myself. Maybe it’s really that good? I genuinely gave it a thought. Eventually, I reluctantly gave in and tried vibe coding for the first time… You see, up until then I exclusively used AI as a sophisticated search engine. I asked a technical question—got an answer. More than 50% of the times it was inaccurate or a full-on hallucination, and then I validated the result through trial and error. Admittedly it was better than blindly googling niche bugs and finding nothing but a lonely and vague question from 8 years ago on Stack Overflow. But matter of fact—vibe coding was a mi

2026-07-19 原文 →
AI 资讯

My Solana Program Launch Checklist (Written the Day After I Actually Did It)

Three weeks from now I will open a terminal, ready to ship another program to mainnet-beta, and I will pause. What was the order again? Did the IDL go up before or after the authority transfer? Was there a flag that saved me from a stalled deploy last time? This checklist exists because I just walked the entire path devnet to mainnet, deploy to IDL to frontend to error handling, and I wrote it down while the details are still fresh. It is the document I wish I had on day one of that process. Run it top to bottom before every mainnet launch. Why a checklist at all? A Solana mainnet deploy is full of irreversible steps. The wallet that signs the deploy quietly becomes the program's upgrade authority. A buffer account left mid-deploy can strand real SOL. A plain anchor build after a verifiable build can produce a different hash and break verification later. None of these are complicated. They are all easy to forget under pressure. A checklist is not a crutch; it is the habit that lets you ship calmly instead of improvising each time. Phase 1: Pre-flight on devnet Do all of this while mistakes are still free. [ ] Every test passes against the final build. Run anchor build && cargo test --package <your-program> one last time. The binary you test must be the binary you ship. [ ] End-to-end run on devnet. Call every instruction through the actual frontend, not just the test suite. The frontend is a different caller than LiteSVM and will surface different failure modes. [ ] Produce a verifiable build. Run anchor build --verifiable . This pins the build environment so the on-chain bytecode can later be matched to your source code. Once you have this artifact, do not touch it with a plain anchor build or cargo build-sbf ; those can produce a different hash and silently break verification. [ ] Measure rent before you spend it. Run: solana rent $( wc -c < target/deploy/.so ) Your deploy wallet must hold this amount plus a margin for transaction fees. There is no airdrop on the

2026-07-19 原文 →
AI 资讯

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

2026-07-19 原文 →
AI 资讯

Clear the Lineup — Chasing a Stack Overflow in Typst's `#eval` Down to One Wrong Word

This is a submission for DEV's Summer Bug Smash: Clear the Lineup . Project Overview Typst is the Rust-based markup typesetting system that's been quietly eating LaTeX's lunch for the last couple of years — you write plain-text markup, Typst compiles it to PDF (or HTML) with a real incremental compiler underneath instead of a multi-pass macro soup. Part of what makes it pleasant is that it exposes its own evaluator to itself: a document can call #eval("some typst code") and get back whatever that code produces, at runtime, inside the document being compiled. It's a small feature, but it opens up a surprisingly deep rabbit hole, which is exactly where this bug was hiding. Bug Fix or Performance Improvement The problem: typst/typst#8632 reports that Typst crashes instead of erroring when #eval is used to recursively re-import the file it's running in. The repro is one line. Save this as overflow.typ : #eval("import \"overflow.typ\"") Then: $ ./target/debug/typst compile overflow.typ overflow.pdf thread 'main' (750833) has overflowed its stack fatal runtime error: stack overflow, aborting No PDF, no diagnostic, no exit code you can act on — just a native stack overflow and a SIGABRT. Typst has had cyclic-import detection since forever; a normal top-level import "overflow.typ" inside itself gets caught cleanly with an error: cyclic import message. Something about routing the import through #eval specifically was bypassing that check. The hunt I'll be upfront about how this investigation actually went: I worked through it with Claude (Anthropic's coding agent) rather than solo. The triage pass it did before I sat down with the code had already narrowed the search to one function — eval_string in crates/typst-eval/src/lib.rs — and named the suspect line. That's a big head start, but a named suspect isn't a confirmed root cause, so the actual work was reading that function next to its sibling, the file-level eval() a few lines above it, and checking the claim against the s

2026-07-18 原文 →