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Uncovering Design Principles for Lifelong Learning AI Accelerators

Uncovering Design Principles for Lifelong Learning AI Accelerators by Dhireesha Kudithipudi, Anurag Daram, Abdullah M. Zyarah, Fatima Tuz Zohora, James B. Aimone, Angel Yanguas-Gil, Nicholas Soures, Emre Neftci, Matthew Mattina, Vincenzo Lomonaco, Clare D. Thiem, and Benjamin Epstein.

Lifelong learning, an agent’s ability to learn throughout its lifetime, is a hallmark feature of biological learning systems and a central challenge for artificial intelligence (AI). Recent progress in lifelong learning algorithms holds promise for enabling a new generation of applications with such capabilities. As these models continue to mature, hardware requirements become paramount, driving the demand for a paradigm shift in AI accelerator design. We offer a high-level overview of features for lifelong learning accelerators and outline a program for designing custom lifelong learning systems for deployment in untethered environments.

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Each week Tenstorrent will be highlighting a paper that has inspired our product development.