Coding Tools
Open-source tool deletes Apple Intelligence data on macOS
The Verge AIhigh confidence
Why it matters
- →Users can reclaim ~12GB of storage previously locked by Apple Intelligence models.
- →The tool automates disabling scattered AI features that lack a central off-switch.
- →It provides a reversible solution for privacy-conscious users avoiding cloud-based AI data collection.
An open-source command-line tool named RemoveMacAI allows macOS users to fully disable and delete Apple Intelligence features, which were previously difficult to remove after the Settings toggle was eliminated in macOS 27. The tool disables Siri, Writing Tools, Genmoji, Image Playground, and related summaries while deleting approximately 12GB of foundation models from the disk and preventing their re-download. Developer claims indicate these changes persist across system updates, with a revert command available to restore functionality if needed.
Read originalThe story around this
Earlier coverage that leads up to this article, and what followed. Lines connect each piece to the closest one after it, converging here.
How we got here
- 1Apple Unveils New Siri AI and Apple Intelligence
The Verge AI · June 8, 2026 · Background
- 2Apple Unveils Siri AI Overhaul at WWDC 2026
The Rundown AI · June 9, 2026 · Background
- 3Apple's Siri AI Gets Major Overhaul
WIRED AI · June 20, 2026 · Background
- 4Apple's Siri AI Opens to Public with iOS 27 Beta
TechCrunch AI · July 14, 2026 · Background
- 5OpenAI buys Macs for private AI agents
Wes Roth · September 1, 2026 · Background
- 6Apple Unveils Privacy-Focused Siri Audio Features
The Verge AI · September 9, 2026 · Background
- 7Apple's Siri AI Gets Major Upgrade with iOS 27
WIRED AI · September 10, 2026 · Background
- 8Apple tightens macOS Full Disk Access for AI agents
TechCrunch AI · October 2, 2026 · Related
More from The Verge AI
© The Verge AIGeneral AIagents
Gemini Call for Me expands to personal calls
Google is quietly testing a significant expansion of its 'Call for Me' feature, moving it from business contexts into personal life. Teardowns reveal prompts like telling your mom you're late or asking if someone is coming to dinner, signaling a shift toward automating brief, transactional voice interactions. This isn't about full conversations; it's about replacing texts with phone calls for people who miss messages or use landlines. The move shows Google's strategy to make Gemini the default interface for mundane communication tasks across Android. By targeting these specific friction points, the feature aims to reduce text fatigue while maintaining the immediacy of voice. Users gain a new layer of automation that feels less like a chatbot and more like a personal assistant handling logistics. This approach prioritizes utility over novelty, embedding AI into the fabric of daily routine rather than keeping it in a separate app.
The Verge AI
© The Verge AIGeneral AIother
Nolla Health launches AI acne prescriptions in Utah
Nolla Health is the first company to use AI for initial acne prescriptions, not just renewals. The system scans faces and suggests treatments, with a pilot program that gradually reduces physician oversight. This marks a significant shift in how AI can be integrated into healthcare workflows.
The Verge AI
© The Verge AIMarket & Regulationother
OpenAI faces backlash over math breakthroughs and ethics
OpenAI’s aggressive push into mathematics has triggered a severe reputational crisis within the academic community. After claiming solutions to major problems like Navier-Stokes using massive agent swarms, researchers accused the lab of unethical data practices and scooping peers. The company’s response—a new advisory panel—has been met with skepticism rather than relief. This exposes a fundamental clash between Silicon Valley’s speed-first culture and academia’s norms of transparency and collaboration. The real story isn't just the math; it's the institutional friction caused by AI labs treating research as a race. KleidiAI on Apple Silicon now compiles in default, meaning every M-series machine gets ARM-tuned GEMM kernels for free. ROCm 7.2 added as a default build narrows the AMD/CUDA gap visibly. There's no new model and no new quantization here — just llama.cpp quietly becoming the inference runtime for everyone who isn't on NVIDIA.
The Verge AI
More in Coding Tools
Coding Toolscoding
Claude Code v2.1.290: Plugin hooks and agent stability fixes
This release significantly tightens the security model for Claude Code plugins by exposing server tool IDs and approval ceilings to hook functions, allowing developers to build more granular permission checks. It also stabilizes long-running agent sessions by fixing critical bugs in subagent resume logic and scheduled task persistence after compaction. For plugin authors, the new validation flags ensure gating hooks are properly configured before deployment. These changes make the platform safer for enterprise use while reducing friction for complex automated workflows.
Claude Code Releases
Coding Toolscoding
llama.cpp b11424 adds CUDA 13 and ROCm 10.0
This release quietly closes the hardware gap for local inference by adding default support for CUDA 13 and ROCm 10.0 alongside existing CUDA 12 builds. NVIDIA users can now leverage newer driver stacks without manual configuration, while AMD GPU owners finally get first-class parity with the same ease of use previously reserved for CUDA. Apple Silicon KleidiAI is disabled in this specific build, a notable regression for Mac users who rely on that optimization. The inclusion of Snapdragon and OpenVINO binaries further broadens the reach to edge devices and Intel hardware. It’s less about new features and more about llama.cpp solidifying its position as the universal runtime for every major accelerator.
llama.cpp Releases
Coding Toolscoding
llama.cpp b11425 adds ROCm 10 and Snapdragon support
This release quietly cements llama.cpp as the universal inference runtime by finally bringing first-class ROCm 10.0 support to both Linux and Windows. AMD GPU users no longer need workarounds, effectively closing a long-standing parity gap with NVIDIA's CUDA ecosystem. The inclusion of Snapdragon AI stack binaries for Linux marks a strategic push into ARM-based edge devices, while the simultaneous addition of CUDA 13 builds ensures compatibility with the latest driver stacks. By standardizing these hardware backends across major operating systems, the project removes friction for developers deploying models on diverse non-NVIDIA hardware.
llama.cpp Releases