why is apple so weak at AI compared to other big tech

Apple's approach to AI and machine learning is distinct in several ways, which might lead to the perception that it is weaker compared to other big tech companies. However, Apple has been making significant strides in this area, particularly focusing on on-device AI to enhance privacy and user experience. Here are some key points from the WWDC sessions that highlight Apple's AI strategy:

1. On-Device AI: Apple emphasizes running AI models on-device to ensure low latency and enhanced privacy. This approach is evident in features like gesture recognition, portrait mode, and health monitoring, which are powered by machine learning models running entirely on Apple devices (Explore machine learning on Apple platforms).

2. Unified Memory Architecture: Apple Silicon's unified memory architecture allows for efficient operations across CPU and GPU, which is beneficial for machine learning tasks. This architecture supports parallel operations and reduces the need for data copying between different memory pools (Discover machine learning & AI frameworks on Apple platforms).

3. Collaboration and Research: Apple collaborates with the research community and has published numerous papers on AI models and on-device optimizations. They also provide open-source tools and sample code to facilitate further exploration and development (Platforms State of the Union).

4. Generative Intelligence: Apple is integrating generative intelligence into its platforms, which includes new capabilities for understanding and generating language and images. This is part of their broader strategy to bring powerful generative models to iOS, iPadOS, and macOS (Platforms State of the Union).

5. Privacy-Centric AI: Apple's AI strategy is deeply integrated with privacy, ensuring that user data remains secure and private. This is a core principle in their AI development, differentiating them from other companies that may prioritize cloud-based AI solutions (Platforms State of the Union).

While Apple may not be as vocal or visible in the AI space as some other tech giants, their focus on privacy, on-device processing, and integration with their hardware ecosystem represents a unique approach to AI development.