Machine Learning
Research at Apple

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…
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Towards Cross-Cultural Machine Translation with Retrieval-Augmented Generation from Multilingual Knowledge Graphs

content type paperresearch area Knowledge Bases and Search, research area Methods and Algorithms, research area Speech and Natural Language Processingconference EMNLPPublished year 2024
AuthorsSimone Conia, Daniel Lee, Min Li, Umar Farooq Minhas, Saloni Potdar, Yunyao Li
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ConvKGYarn: Spinning Configurable and Scalable Conversational Knowledge Graph QA Datasets with Large Language Models

content type paperresearch area Knowledge Bases and Search, research area Speech and Natural Language Processingconference EMNLPPublished year 2024
AuthorsRonak Pradeep, Daniel Lee, Ali Mousavi, Jeff Pound, Yisi Sang, Jimmy Lin, Ihab Ilyas, Saloni Potdar, Mostafa Arefiyan, Yunyao Li
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Improving How Machine Translations Handle Grammatical Gender Ambiguity

Machine Translation (MT) enables people to connect with others and engage with content across language barriers. Grammatical gender presents a difficult challenge for these systems, as some languages require specificity for terms that can be ambiguous or neutral in other languages. For example, when translating the English word "nurse" into Spanish, one must decide whether the feminine "enfermera" or the masculine "enfermero" is appropriate…
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Introducing Apple’s On-Device and Server Foundation Models

At the 2024 Worldwide Developers Conference, we introduced Apple Intelligence, a personal intelligence system integrated deeply into iOS 18, iPadOS 18, and macOS Sequoia.

Apple Intelligence is comprised of multiple highly-capable generative models that are specialized for our users’ everyday tasks, and can adapt on the fly for their current activity. The foundation models built into Apple Intelligence have been fine-tuned for user experiences such as writing and refining text, prioritizing and summarizing notifications, creating playful images for conversations with family and friends, and taking in-app actions to simplify interactions across apps.

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European Conference on Computer Vision (ECCV) 2024

Apple is presenting new research at the European Conference on Computer Vision (ECCV), which takes place in person in Milan, Italy, from September 29 - October 4. We are proud to again sponsor the biennial conference, which brings together the scientific and industrial research communities around ML and computer vision. Below is an overview of Apple’s participation at ECCV 2024.

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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 — for example, what users type on their keyboards and the websites they visit — can compromise user privacy. We develop system…
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