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Apple has taken a significant step forward in its efforts to provide developers with advanced AI capabilities on devices. The tech giant recently released twenty new Core ML models and four datasets on Hugging Face, a leading community platform for sharing AI models and code. This move underlines Apple’s commitment to advancing AI while prioritizing user privacy and efficiency.
Clement Delangue, co-founder and CEO of Hugging Face, emphasized the importance of this update in a statement to VentureBeat. “This is a major update by uploading many models to their Hugging Face repository with their Core ML framework,” said Delangue. “The update includes exciting new models focused on text and images, such as image classification or depth segmentation. Imagine an app that can effortlessly remove unwanted backgrounds from photos or instantly identify objects in front of you and give them their names in a foreign language.”
Optimized models for improved performance and privacy
The recently released Core ML models cover a wide range of applications, including FastViT for image classification, DepthAnything for monocular depth estimation, and DETR for semantic segmentation. These models are optimized to run exclusively on users’ devices, eliminating the need for a network connection. This approach not only improves app performance, but also ensures that user data remains secure and private.
Delangue emphasized the importance of on-device AI, stating: “Core ML models run exclusively on the user’s device and eliminate the need for a network connection. This keeps your app lightning fast and user data private.”
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Collaboration with Hugging Face stimulates AI innovation
The publication of these models and datasets on Hugging Face is a testament to Apple’s growing partnership with the AI community platform. In recent months, Apple has been actively working with Hugging Face to power several initiatives, such as the MLX Community and the integration of open-source AI into Apple Intelligence features.
Industry experts believe that Apple’s focus on on-device AI aligns with the broader trend of shifting computing power from the cloud to edge devices. By leveraging the capabilities of Apple Silicon and minimizing memory footprint and power consumption, Core ML enables developers to create intelligent apps that deliver seamless user experiences without compromising privacy or performance.
Empowering developers to build privacy-focused intelligent apps
As demand for privacy-preserving and efficient AI solutions continues to rise, Apple’s latest move is expected to enable developers to build innovative applications in various domains, from image and video processing to natural language understanding and much more. With the availability of these new Core ML models and datasets on Hugging Face, the AI community can further collaborate, iterate, and push the boundaries of what is possible with on-device AI.
Apple’s commitment to advancing AI while prioritizing user privacy sets a strong precedent for the industry. As more tech giants recognize the importance of AI on devices, it’s likely we’ll see a surge in the development of intelligent, privacy-focused applications that leverage the power of local, specialized models to deliver transformative user experiences.