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Apple has made significant progress in its efforts to empower developers with cutting-edge AI capabilities on the device. The tech giant recently released 20 new Core ML models and 4 datasets on Hugging Face, a leading community platform for sharing AI models and code. The move underscores Apple’s commitment to advancing AI while prioritizing user privacy and efficiency.
Clement Delange, co-founder and CEO of Hugging Face, emphasized the importance of this update in a statement sent to VentureBeat. “This is a big update by uploading a lot of models to their Hugging Face repo 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 provide their names in a foreign language.”
Optimized models for improved performance and privacy
The newly 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 consumer devices, eliminating the need for a network connection. This approach not only improves application performance, but also ensures that user data remains secure and confidential.
Delangue emphasized the importance of on-device AI, stating, “Core ML models run strictly on the user’s device and remove any need for a network connection. This keeps your app blazing fast and ensures that user data remains private.”
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Collaboration with Hugging Face fuels AI innovation
The release of these Hugging Face models and datasets is a testament to Apple’s growing partnership with the AI community platform. In recent months, Apple has been actively collaborating with Hugging Face to power various initiatives, such as the MLX community and the integration of open source AI into Apple Intelligence features.
Industry experts believe Apple’s focus on on-device AI is in line with a broader trend of shifting computing power from the cloud to end devices. By leveraging the capabilities of Apple Silicon and minimizing memory footprint and power consumption, Core ML enables developers to build intelligent applications that deliver a seamless user experience without compromising privacy or performance.
Empowering developers to build smart, privacy-focused apps
As the demand for privacy-preserving and effective AI solutions continues to grow, Apple’s latest move is expected to enable developers to create innovative applications in a variety of fields, from image and video processing to natural language understanding and beyond. With these new Core ML models and Hugging Face datasets available, the AI community can continue to collaborate, iterate, and push the boundaries of what’s 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 on-device AI, we’re likely to see a surge in the development of privacy-focused smart apps that leverage the power of local, specialized models to deliver transformative user experiences.
