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Adobe researchers have created a breakthrough AI system that processes documents directly on smartphones without internet connectivity, potentially transforming how businesses handle sensitive information and how consumers interact with their devices.
The system, called SlimLM, represents a major shift in artificial intelligence deployment — away from massive cloud computing centers and onto the phones in users’ pockets. In tests on Samsung’s latest Galaxy S24, SlimLM demonstrated it could analyze documents, generate summaries, and answer complex questions while running entirely on the device’s hardware.
“While large language models have attracted significant attention, the practical implementation and performance of small language models on real mobile devices remain understudied, despite their growing importance in consumer technology,” explained the research team, led by scientists from Adobe Research, Auburn University, and Georgia Tech.
How small language models are disrupting the cloud computing status quo
SlimLM enters the scene at a pivotal moment in the tech industry’s shift toward edge computing — a model in which data is processed where it’s created, rather than in distant data centers. Major players like Google, Apple, and Meta have been racing to push AI onto mobile devices, with Google unveiling Gemini Nano for Android and Meta working on LLaMA-3.2, both aimed at bringing advanced language capabilities to smartphones.
What sets SlimLM apart is its precise optimization for real-world use. The research team tested various configurations, finding that their smallest model — at just 125 million parameters, compared to models like GPT-4o, which contain hundreds of billions — could efficiently process documents up to 800 words long on a smartphone. Larger SlimLM variants, scaling up to 1 billion parameters, were also able to approach the performance of more resource-intensive models, while still maintaining smooth operation on mobile hardware.
This ability to run sophisticated AI models on-device without sacrificing too much performance could be a game-changer. “Our smallest model demonstrates efficient performance on [the Samsung Galaxy S24], while larger variants offer enhanced capabilities within mobile constraints,” the researchers wrote.
Why on-device AI could reshape enterprise computing and data privacy
The business implications of SlimLM extend far beyond technical achievement. Enterprises currently spend millions on cloud-based AI solutions, paying for API calls to services like OpenAI or Anthropic to …