Hacker News - Newest: ""Swift" "SwiftUI" "Xcode" "iOS""

I've spent the last 10 months building Beauty: a local, powerful greco-roman Markdown editor where the page looks finished while you type. It runs on the Mac, iPhone and in the browser, and the browser version opens without an account: https://app.markdown.beauty

I was frustrated with writing apps, and like most I used Apple Notes. After 2+ years immersed in Cursor, Codex and CC, I wished some interactions existed in a text editor.

The Markdown renders in place as you write it, including tables (which you can drag and resize without lining up pipes), KaTeX math and Mermaid diagrams. A lot of thought went into typography and the writing experience.

Your notes on the Mac are plain .md files in a folder with images next to them, so they open in anything else too. Each note keeps 200 versions. If you share a note with a link it syncs peer to peer over WebRTC while someone has it open, and the server that connects you only ever sees a random room id.

Most of the ~1,000 commits went into the editor itself. It's a contenteditable, and I don't let the browser restructure the document at all, which was a lot more work than I expected. Building this to be performant and cross-platform required some novel approaches, which I'll later open source. The editor is free with no account or ads, and there's an optional subscription for sync through your own iCloud.

https://www.markdown.beauty

Comments URL: https://news.ycombinator.com/item?id=49866597

Points: 69

# Comments: 53

Apple has added persistent 'ads' to iOS, and it's driving users crazy

MC995 — Tue, 22 Sep 2026 14:30:12 +0000

Article URL: https://www.techradar.com/phones/iphone/i-wish-apple-would-just-stop-that-crap-apple-has-added-persistent-ads-to-ios-and-its-driving-users-crazy

Comments URL: https://news.ycombinator.com/item?id=49801939

Points: 822

# Comments: 601

Xcode 27.1 Beta Release Notes

CameronBanga — Fri, 18 Sep 2026 18:39:31 +0000

Article URL: https://developer.apple.com/documentation/xcode-release-notes/xcode-27_1-release-notes

Comments URL: https://news.ycombinator.com/item?id=49758419

Points: 154

# Comments: 116

Show HN: Swift-Qwen3.8-27B, -58.3% thinking, x1.95 speed, accuracy of xhigh

kisjovan — Wed, 16 Sep 2026 14:24:05 +0000

Hi everybody, we post-trained Qwen 3.8 27B to be more efficient by figuring out which tokens were linked to overthinking and penalizing them without "attacking" the reasoning length directly then fixed the accuracy with a bit of secret sauce (hint On-Policy Distillation) and achieved great results (-58% length, 1.95x speed up, <1% accuracy loss) so we wanted to open-source it and hear the feedback of the community.

This is the link to the model: https://huggingface.co/ukisai/Swift-Qwen3.8-27b / It's at 80k downloads in 3 days with independent evals here: https://www.reddit.com/r/LocalLLaMA/comments/1wg7dd5/ukisai_...

We are also providing a Free Research Purpose API (OpenAI compatible), courtesy of Nvidia who were kind enough to provide us with the GPUs. It's limited at 5RPM. https://ukisai.com/api/swift/v1/models

We also made a GGUF (Q1-Q8): https://huggingface.co/ukisai/Swift-Qwen3.8-27B-GGUF and there's also a few nice community quants with even lower/higher precision (Bartowski: https://huggingface.co/bartowski/ukisai_Swift-Qwen3.8-27b-GG...). The community also created amazing MLX, NVFP4, W4A16 and Uncensored versions you can find on Huggingface.

IMPORTANT: Our training approach is not a replacement for the reasoning effort settings, chat templates or token caps but is complementary and targets a completely separate issue (overthinking and "anxiety-like" reasoning loops prior seen in PTQ, but as far as we identified also prominent in BF16 of this size class LLMs as well). Contrary to popular belief, these specific patterns do not contribute to answer quality when properly targeted. (our thesis being: reasoning length IS extremely important and should NOT be shortened by force, but rather optimized). This is also demonstrated bellow in our xhigh vs medium effort benchmark. The goal is to keep xhigh accuracy while reducing only the unnecessary part of thinking.

The TLDR of our thought process, research, training and a link to the Meta paper that inspired us is in the first comment.

The benchmarks:

Swift-27B vs Qwen3.8-27B (BF16, all benchmarks ran x5, thinking effort xhigh)

GPQA-Diamond: 88.4% -> 88.3%, 58% fewer median tokens

LiveCodeBench v6: 76.8% -> 81.6% (+4.8pp, due to default truncation in LCB it is not performance gain), 46% fewer median thinking tokens

Terminal-Bench 2.1: 66.7% -> 65.8%, 39% fewer median tokens

MMLU-Pro: 85.5% -> 85.0%, 28% fewer median tokens

C-Eval: 90.0% -> 90.6%, 19% fewer median tokens

IFBench: 73.5% -> 71.8%, 51% fewer median tokens

AIME 2026: 98.7% -> 94.0%, 50% fewer median tokens

HMMT (Nov 2025): 99.3% -> 96.0%, 46% fewer median tokens

ERQA (vision): 67.5% -> 66.3%, 55% fewer median tokens

Token savings hold at every reasoning effort (mean thinking reduction): xhigh 41%, medium 23%, low 26% (albeit with accuracy loses of 1-4% on medium and 1-2% on low which we need further testing for)

Swift at xhigh vs the base's own effort settings on GPQA-Diamond (198 questions x 5 seeds):

Base xhigh: 88.4%, 6,642 median tokens

Swift xhigh: 88.3%, 2,771 median tokens

Base medium: 84.1%, 1,753 median tokens

So Swift keeps xhigh accuracy at under half the tokens, and beats base-medium by 4pp at roughly 1.6x its tokens.

End note:

While we are keen on complete open-source, we still need to keep a part of our training and data private, being a new lab. The license is not Apache 2.0, but it only affects companies >$1M. We hope this does not pose a problem for the community and are open to feedback on it.

We want to contribute as much as possible to the community and would really appreciate feedback on our work, quantization or Swift model requests. We are working on Swift 3.8 Flash Next and have so far gotten up to -53% thinking token usage. We have strong indicators our methodology is reproducible on other model families as well and are asking the community which ones you want us to optimize next.

Comments URL: https://news.ycombinator.com/item?id=49727511

Points: 33

# Comments: 17

Ask HN: Lesser known features of macOS/iPadOS/iOS/etc. 27

lucasoshiro — Tue, 15 Sep 2026 16:06:01 +0000

Hi there!

I've just upgraded my Mac and iPad OSes to 27 and found some interesting features that I haven't seen listed elsewhere:

- Screen mirroring to iPad now accepts touchscreen inputs

- iPad menu bar can now be always turned on

- The sidebars aren't floating, just like before Tahoe

- Decreased window border radius

- Increased resize window area

Comments URL: https://news.ycombinator.com/item?id=49714644

Points: 16

# Comments: 8

Swift 6.4 Released

timsneath — Tue, 15 Sep 2026 15:40:14 +0000

Article URL: https://www.swift.org/blog/swift-6.4-released/

Comments URL: https://news.ycombinator.com/item?id=49714239

Points: 128

# Comments: 63

Tell HN: iOS 27 does not allow Apple Intelligence to be disabled

nunez — Mon, 14 Sep 2026 21:21:58 +0000

I'm surprised that this didn't get more attention during the Beta period.

iOS 26 had a toggle you could select to disable all Apple Intelligence features.

That toggle was removed for iOS 27. Every AI feature has to be turned off individually: https://archive.ph/AE72I

There is a way of turning it off through Content Restrictions in Screen Time, but one Redditor reported that doing this disables CarPlay for some reason.

This is pretty disappointing.

Comments URL: https://news.ycombinator.com/item?id=49704226

Points: 77

# Comments: 29