Sign inGet started
Paper · arXiv

LIFE -- an energy efficient advanced continual learning agentic AI framework for frontier systems

The rapid advancement of AI has changed the character of HPC usage such as dimensioning, provisioning, and execution. Not only has energy demand been amplified, but existing rudimentary continual learning capabilities limit ability of AI to effectively manage HPCs. This paper reviews emerging directions beyond monolithic transformers, emphasizing agentic AI and brain inspired architectures as complementary paths toward sustainable, adaptive systems. We propose LIFE, a reasoning and Learning framework that is Incremental, Flexible, and Energy efficient that is implemented as an agent centric system rather than a single monolithic model. LIFE uniquely combines four components to realize sel...

AuthorsAnne Lee, Gurudutt Hosangadi
Primary categorycs.AI
Published14 April 2026
Last updated at source14 April 2026
cs.AI
Embed this entry
<iframe src="https://silytics.si/embed/item/aa6ec92a-734d-4864-b457-6171fd42a416" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.