HomeApple Responds to iOS 27 AI Controversy: Foundation Models Entirely Developed In-House
At the Worldwide Developers Conference (WWDC 26), Apple officially unveiled iOS 27, putting its deeply integrated AI system — Apple Foundation Models (AFM) — in the spotlight. Addressing speculation that AFM is merely a rebranded version of Google Gemini, several Apple executives gave clear and firm responses in recent media interviews: AFM is not a simple rebranding of Gemini; it is a fully self-controlled achievement by Apple.
Apple acknowledged that some Gemini technology was referenced during model training and distillation, but the final product delivered to users incorporates core architecture, underlying code logic, technical implementation paths, and supporting data systems entirely built by the Apple team. This statement is intended to address user and developer concerns, underscoring Apple’s core control and ecological independence in the AI domain.
Apple's AFM system now features a clear hierarchical structure designed to handle tasks of varying complexity:
On-device, AFM Core handles basic local AI operations, while the more advanced AFM Core Advanced introduces a sparse architecture that supports native multimodal capabilities and handles more complex computing needs on local devices.
Cloud-based models are divided by workload: AFM Cloud manages high-load requests that devices cannot handle; AFM Cloud Image specializes in high-precision image generation and editing; and AFM Cloud Pro, the most advanced, is dedicated to agent tools and the heaviest computing tasks.
To ensure optimal performance on every Apple Silicon device, these models are deeply customized for the chip. Apple emphasizes that the system architecture prevents users from directly accessing Google's code, Gemini agents, or Google Search when using related services, thereby maximizing user experience purity and privacy security.
Even in cloud infrastructure deployment, Apple maintains high security standards. Although AFM Cloud Pro's infrastructure uses Google Cloud servers and NVIDIA GPU resources, the entire processing workflow strictly follows Apple's "Private Cloud Compute" certification system. This ensures that even when tasks are completed in the cloud, Apple maintains strict control over privacy protection.
As iOS 27 rolls out gradually, this AI matrix powered by Apple's self-developed underlying technology seeks a new balance between "edge-cloud collaboration" and "privacy compliance," showcasing Apple's distinctive approach to building an AI ecosystem for global users.
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At the Worldwide Developers Conference (WWDC 26), Apple officially unveiled iOS 27, putting its deeply integrated AI system — Apple Foundation Models (AFM) — in the spotlight. Addressing speculation that AFM is merely a rebranded version of Google Gemini, several Apple executives gave clear and firm responses in recent media interviews: AFM is not a simple rebranding of Gemini; it is a fully self-controlled achievement by Apple.
Apple acknowledged that some Gemini technology was referenced during model training and distillation, but the final product delivered to users incorporates core architecture, underlying code logic, technical implementation paths, and supporting data systems entirely built by the Apple team. This statement is intended to address user and developer concerns, underscoring Apple’s core control and ecological independence in the AI domain.
Apple's AFM system now features a clear hierarchical structure designed to handle tasks of varying complexity:
On-device, AFM Core handles basic local AI operations, while the more advanced AFM Core Advanced introduces a sparse architecture that supports native multimodal capabilities and handles more complex computing needs on local devices.
Cloud-based models are divided by workload: AFM Cloud manages high-load requests that devices cannot handle; AFM Cloud Image specializes in high-precision image generation and editing; and AFM Cloud Pro, the most advanced, is dedicated to agent tools and the heaviest computing tasks.
To ensure optimal performance on every Apple Silicon device, these models are deeply customized for the chip. Apple emphasizes that the system architecture prevents users from directly accessing Google's code, Gemini agents, or Google Search when using related services, thereby maximizing user experience purity and privacy security.
Even in cloud infrastructure deployment, Apple maintains high security standards. Although AFM Cloud Pro's infrastructure uses Google Cloud servers and NVIDIA GPU resources, the entire processing workflow strictly follows Apple's "Private Cloud Compute" certification system. This ensures that even when tasks are completed in the cloud, Apple maintains strict control over privacy protection.
As iOS 27 rolls out gradually, this AI matrix powered by Apple's self-developed underlying technology seeks a new balance between "edge-cloud collaboration" and "privacy compliance," showcasing Apple's distinctive approach to building an AI ecosystem for global users.
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As artificial intelligence advances rapidly in code generation and logical reasoning, the cybersecurity landscape faces unprecedented challenges. Recently, the prominent AI startup Anthropic officially launched a cross-industry collaboration called *
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