Edge 416: Inside Apple's 4M-21 Model that Could be the Foundation of its On-Device Multimodal Experience
Was this email forwarded to you? Sign up here Edge 416: Inside Apple's 4M-21 Model that Could be the Foundation of its On-Device Multimodal ExperienceThe model was trained simultaneously across 21 different modalities.
Apple has been late to the generative AI game, but lately, it has been pushing the research agenda quite hard. Apple has an ideal playground for innovating in one of the hottest areas of the next wave of generative AI: on-device multimodal models. The idea of powering mobile AI through API integrations with massively large foundation models seems highly impractical and insecure, and Apple is in a unique position to power alternatives to this paradigm. However, most of Apple’s efforts in small on-device models have been somewhat underwhelming. This is starting to change. Recently, Apple released what I consider its most impressive work in small, on-device foundation models with the publication and open source release of 4M-21, a multimodal model that work seamlessly across 21 modalities! The work definitely signals the path for Apple on-device model strategy and the large number of modalities is quite shocking. However, this work builds on a previous research work that Apple published months ago with the release of its 4M model. Let’s start there... Subscribe to TheSequence to unlock the rest.Become a paying subscriber of TheSequence to get access to this post and other subscriber-only content. A subscription gets you:
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Edge 415: Agents that Remember Actions with Procedural Memory
Tuesday, July 23, 2024
One of the most unique forms of memory in autonomous agents. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
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Apple, HuggingFace, OpenAI, Mistral, Groq all released innovative models in the same week. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
📽 [Virtual Talk] Supercharge Production AI with Features as Code
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Data is essential for AI/ML systems but often becomes a development bottleneck. Data scientists and engineers face challenges in building and maintaining feature pipelines, ensuring data consistency
Edge 414: Inside Meta AI's HUSKY: A New Agent Optimized for Multi-Step Reasoning
Thursday, July 18, 2024
New research from Meta AI, Allen AI, and the University of Washington tackles one of the most important problems in LLM reasoning. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
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