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Apple machine learning teams are engaged in state of the art research in machine learning and artificial intelligence. Learn about the latest advancements.
2024年6月10日 · The Apple foundation models and adapters introduced at WWDC24 underlie Apple Intelligence, the new personal intelligence system that is integrated deeply into iPhone, iPad, and Mac, and enables powerful capabilities across language, images, actions, and
Reinforcement Learning from AI Feedback (RLAIF) has demonstrated significant potential across various domains, including mitigating harm in LLM outputs, enhancing text summarization, and mathematical reasoning.
We present a foundation model for zero-shot metric monocular depth estimation. Our model, Depth Pro, synthesizes high-resolution depth maps with unparalleled sharpness and high-frequency details. The predictions are metric, with absolute scale, without relying on the availability of metadata such as camera intrinsics.
2022年6月6日 · This year at WWDC 2022, Apple is making available an open-source reference PyTorch implementation of the Transformer architecture, giving developers worldwide a way to seamlessly deploy their state-of-the-art Transformer models on Apple devices.
We present foundation language models developed to power Apple Intelligence features, including a ∼3 billion parameter model designed to run efficiently on devices and a large server-based language model designed for Private Cloud Compute.
The reproducibility and transparency of large language models are crucial for advancing open research, ensuring the trustworthiness of results, and enabling investigations into data and model biases, as well as potential risks. To this end, we release OpenELM, a state-of-the-art open language model.
2024年3月11日 · Apple is proud to announce the 2024 recipients of the Apple Scholars in AIML PhD fellowship. We are committed to supporting the academic research community by amplifying emerging leaders in their field and their cutting-edge machine learning research.
2024年10月24日 · At Apple, we use HE in conjunction with other privacy-preserving technologies to enable a variety of features, including private database lookups and ML. We also use a number of optimizations and techniques to balance the computational overhead of HE with the latency and efficiency demands of production applications at scale.
2021年7月28日 · Photos (on iOS, iPad OS, and Mac OS) is an integral way for people to browse, search, and relive life's moments with their friends and family. Photos uses a number of machine learning algorithms, running privately on-device, to help curate and organize images, Live Photos, and videos. An algorithm foundational to this goal recognizes ...
