Apple says it is changing its macOS privacy settings to stop third-party app developers from misusing them to access message histories.

Apple will add new limits for "full disk access" on Mac in response to risks posed by AI agents, as reported earlier by TechCrunch.

After evolving from an Apple-made, client-side language and years of false starts, Swift could finally make it on the server.

Apple says it s tightening macOS Full Disk Access controls due to new risks from AI agents | TechCrunch Last day to exhibit your breakthrough to 10,000+ tech leaders at Disrupt is on Oct 2 . Book Exhibit Table Now.

PLUS: Telecom giants team up to kill dead zones Good morning, tech enthusiasts. Apple's next big device could be something closer to home: a security camera that never records a frame of video.

Language Discrimination Improves Linguistic Learning in Multilingual Speech Models - Apple Machine Learning Research research area Speech and Natural Language Processing content type paper published October 2026 Language Discrimination Improves Linguistic Learning in Multilingual Speech Models Authors Maureen de Seyssel, Jie Chi*, Zakaria Aldeneh* Multilingual self-supervised speech models can benefit from sharing information across languages, but under a matched total...

Limits of Confidence in Diffusion - Apple Machine Learning Research research area Methods and Algorithms content type paper published October 2026 Authors Russ Webb, Amitis Shidani, Alice Bizeul, Dan Busbridge Discrete diffusion, including remasking and uniform-state samplers, generate a sequence by writing multiple token positions per step, drawing each from a per-position distribution and choosing which positions to write from...

How to install ComfyUI on Mac to generate AI images locally How to install ComfyUI on Mac to generate AI images locally Step by step guide to install ComfyUI on an Apple Silicon Mac and generate AI images with FLUX locally, no subscriptions or cloud needed. 1.

How Much of a Harness Does a Strong Agent Need for Autonomous ML Engineering? - Apple Machine Learning Research research area Methods and Algorithms content type paper published October 2026 How Much of a Harness Does a Strong Agent Need for Autonomous ML Engineering?

The common paradigm of reinforcement learning with verifiable rewards (RLVR) is to let agents make multiple attempts at a task, and optimize towards the…

On the Effectiveness-Fluency Trade-Off in LLM Conditioning: A Systematic Study - Apple Machine Learning Research research area Methods and Algorithms , research area Speech and Natural Language Processing conference EMNLP content type paper published September 2026 On the Effectiveness-Fluency Trade-Off in LLM Conditioning: A Systematic Study Authors Iuri Macocco†, Pau Rodríguez Lopez, Arno Blaas, Luca Zappella, Marco Baroni†*, Xavier Suau...

SCLATE: A Substrate for Continual-Learning Agent Training and Evaluation - Apple Machine Learning Research research area Methods and Algorithms , research area Tools, Platforms, Frameworks content type paper published September 2026 SCLATE: A Substrate for Continual-Learning Agent Training and Evaluation Authors Youngmok Jung, Sirajul Salekin, Henry Tran, Javier Movellan, Zhao Huang, Manjot Bilkhu Continual-learning agents are systems of models, harnesses,...

The Communication Bottleneck: A Round-Trip Study of Tree-Structured Expression Serialization in Language Models - Apple Machine Learning Research research area Methods and Algorithms , research area Speech and Natural Language Processing conference NeurIPS content type paper published September 2026 The Communication Bottleneck: A Round-Trip Study of Tree-Structured Expression Serialization in Language Models Authors Xavier Suau, Alex Ferrando de las Morenas,...

Faster Rates for Federated Variational Inequalities - Apple Machine Learning Research research area Methods and Algorithms conference NeurIPS content type paper published September 2026 Faster Rates for Federated Variational Inequalities In this paper, we study federated optimization for solving stochastic variational inequalities (VIs), a problem that has attracted growing attention in recent years.

A Practical Recipe for Semi-Supervised Federated ASR: Online Pseudo-Labels with Server Update Stabilization - Apple Machine Learning Research research area Methods and Algorithms , research area Speech and Natural Language Processing content type paper published September 2026 A Practical Recipe for Semi-Supervised Federated ASR: Online Pseudo-Labels with Server Update Stabilization Authors Wonho Bae, Zakaria Aldeneh, Martin Pelikan, Jan “Honza” Silovsky,...

Compressing Streaming Neural Audio Encoders via Latent-Space Distillation - Apple Machine Learning Research research area Methods and Algorithms , research area Speech and Natural Language Processing content type paper published September 2026 Compressing Streaming Neural Audio Encoders via Latent-Space Distillation Authors Prasanth Yadla‡, Mohammad Samragh Razlighi‡, Dongseong Hwang, Mingbin Xu, Yuanyuan Zhang, Chung-Cheng Chiu, Yongqiang Wang†**, Yuan Liu§**, Zhen Huang,...

Apple Music has told partners that music materially generated on AI platforms such as Suno will carry a Made With AI label on the service from later this year. At least, that is, if record labels and distributors tag the music with the relevant metadata before it reaches the platform.

Figure 1: CUDA-to-MLX optimization translation map. CUDA optimization knowledge can be translated into architecture-native MLX strategies rather than copied…

Faster Gemma 4 on MLX with multi-token prediction Gemma 4 is now significantly faster in Ollama 0.31. On Apple Silicon, it generates tokens nearly 90% faster on average across a coding-agent benchmark.

Ollama's highest performance on Apple Silicon yet with MLX Ollama's MLX engine has been updated to deliver its highest performance on Apple Silicon yet. By leaning more heavily on Apple's unified memory and the Metal-backed MLX framework, models output higher quality responses, respond faster, and use less memory.

Improved performance and model support with GGUF Ollama 0.30 is now available with improved performance and GGUF model compatibility through llama.cpp . This augments Ollama's MLX engine on Apple silicon, bringing support to more models on a wider range of hardware.

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