Categories: FAANG

Combining Machine Learning and Homomorphic Encryption in the Apple Ecosystem

At Apple, we believe privacy is a fundamental human right. Our work to protect user privacy is informed by a set of privacy principles, and one of those principles is to prioritize using on-device processing. By performing computations locally on a user’s device, we help minimize the amount of data that is shared with Apple or other entities. Of course, a user may request on-device experiences powered by machine learning (ML) that can be enriched by looking up global knowledge hosted on servers. To uphold our commitment to privacy while delivering these experiences, we have implemented a…

Understanding Aggregate Trends for Apple Intelligence Using Differential Privacy

At Apple, we believe privacy is a fundamental human right. And we believe in giving our users a great experience while protecting their privacy. For years, we’ve used techniques like differential privacy as part of our opt-in device analytics program. This lets us gain insights into how our products are…

April 15, 2025

In "FAANG"

Apple Workshop on Privacy-Preserving Machine Learning 2024

At Apple, we believe privacy is a fundamental human right. It’s also one of our core values, influencing both our research and the design of Apple’s products and services. Understanding how people use their devices often helps in improving the user experience. However, accessing the data that provides such insights…

August 30, 2024

In "FAANG"

On Device Llama 3.1 with Core ML

Many app developers are interested in building on device experiences that integrate increasingly capable large language models (LLMs). Running these models locally on Apple silicon enables developers to leverage the capabilities of the user's device for cost-effective inference, without sending data to and from third party servers, which also helps…

November 2, 2024

In "FAANG"

AI Generated Robotic Content