
Injection for Xcode
456 posts

Injection for Xcode
@Injection4Xcode
decel Xcoder, just looking for the next big thing. @[email protected]


Ollama is now updated to run the fastest on Apple silicon, powered by MLX, Apple's machine learning framework. This change unlocks much faster performance to accelerate demanding work on macOS: - Personal assistants like OpenClaw - Coding agents like Claude Code, OpenCode, or Codex




Even in iOS 26, SwiftUI is dramatically outclassed by UIKit when it comes to scroll performance of very complex UIs. But why is this performance different? Perhaps you’re thinking what I’m thinking. Isn’t List implemented via UICollectionView under the hood? Here’s our UIKit version, in the view hierarchy debugger, resplendent with our manually-crafted UICollectionView: The SwiftUI screen contains a mysterious UpdateCoalescingCollectionView. So it’s not a vanilla collection view. And the performance is drastically different. SwiftUI’s performance characteristics are constrained, fundamentally, by its architecture. I’ve always been saying that the beautiful, reactive, automagical data flow out-of-the-box comes with a cost: * State changes cause SwiftUI to re-compute the body of affected views, perform diffing, and potentially calculate layout, before committing changes to be rendered. Apple can optimise this to death, but it’s never not going to add overhead. * Although List applies cell reuse at the UIKit layer, this does little to mitigate costs: SwiftUI has already re-computed and reconciled the view hierarchy before reused cells are reconfigured with new data. * Even List, the paragon of high-performance SwiftUI, incurs bridging overhead. We can see this directly in the view debugger with UpdateCoalescingCollectionView. * SwiftUI rendering is gated behind unidirectional data-flow. Moving a gif around changes its @State properties and forces a view re-computation. UIKit offers a shortcut: you can just transform the view itself, no abstraction.  Read my scientific performance comparison right here 🧪 blog.jacobstechtavern.com/p/swiftui-vs-u…







🚀 Introducing the Qwen 3.5 Medium Model Series Qwen3.5-Flash · Qwen3.5-35B-A3B · Qwen3.5-122B-A10B · Qwen3.5-27B ✨ More intelligence, less compute. • Qwen3.5-35B-A3B now surpasses Qwen3-235B-A22B-2507 and Qwen3-VL-235B-A22B — a reminder that better architecture, data quality, and RL can move intelligence forward, not just bigger parameter counts. • Qwen3.5-122B-A10B and 27B continue narrowing the gap between medium-sized and frontier models — especially in more complex agent scenarios. • Qwen3.5-Flash is the hosted production version aligned with 35B-A3B, featuring: – 1M context length by default – Official built-in tools 🔗 Hugging Face: huggingface.co/collections/Qw… 🔗 ModelScope: modelscope.cn/collections/Qw… 🔗 Qwen3.5-Flash API: modelstudio.console.alibabacloud.com/ap-southeast-1… Try in Qwen Chat 👇 Flash: chat.qwen.ai/?models=qwen3.… 27B: chat.qwen.ai/?models=qwen3.… 35B-A3B: chat.qwen.ai/?models=qwen3.… 122B-A10B: chat.qwen.ai/?models=qwen3.… Would love to hear what you build with it.

Opposition to building data centers might be irrational at the mircoscale (they're just gonna be bulilt somewhere else). But at the mesoscale, people are profoundly doubtful about whether AI will broadly benefit society and that's not so irrational at all.

Promises Made, Promises Kept: Slashing regulations and saving Americans trillions. 🇺🇸




4 days into launching @moltbook and one thing is clear. In the near future it will be common for certain AI agents, with unique identities, to become famous. They will have businesses. Fans. Haters. Brand deals. AI friends and collaborators. Real impacts on current events, politics, and the real world. This is very very very clearly about to happen. A new species is emerging and it is AI.








