The trend toward small language models that can efficiently run on a single device instead of requiring cloud connectivity has emerged as a focus for Big Tech companies involved in artificial intelligence. Apple has released the OpenELM family of open-source models as its entry in that field. OpenELM uses “a layer-wise scaling strategy” to efficiently allocate parameters within each layer of the transformer model, resulting in what Apple claims is “enhanced accuracy.” The “ELM” stands for “Efficient Language Models,” and one media outlet couches it as “the future of AI on the iPhone.” Continue reading Apple Unveils OpenELM Tech Optimized for Local Applications

Apple researchers have gone public with new multimodal methods for training large language models using both text and images. The results are said to enable AI systems that are more powerful and flexible, which could have significant ramifications for future Apple products. These new models, which Apple calls MM1, support up to 30 billion parameters. The researchers identify multimodal large language models (MLLMs) as “the next frontier in foundation models,” which exceed the performance of LLMs and “excel at tasks like image captioning, visual question answering and natural language inference.” Continue reading Apple Unveils Progress in Multimodal Large Language Models

Apple recently announced advances in artificial intelligence research that could introduce more immersive visual experiences and enable sophisticated AI systems to run on the company’s popular mobile devices. Two new research papers highlight techniques for creating 3D avatars from video content and efficiently deploying large language models on devices challenged by limited memory. The real-time ability to create avatars and 3D scenes from an iPhone camera could bring a range of new possibilities for CE devices in areas such as synthetic media, telepresence, social interaction, virtual try-on and more. Continue reading Apple Unveils New Advances in Artificial Intelligence Research