VentureBeat

Tenyx aims to fix LLMs’ catastrophic forgetting problem

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Science Daily

Novel memristors to overcome AI's 'catastrophic forgetting'

Memristors consume extremely little power and behave similarly to brain cells. Researchers have now introduced novel memristive that offer significant advantages: they are more robust, function across ...
Rochester Institute of Technology

Fixing the forgetting problem in artificial neural networks

An RIT scientist has been tapped by the National Science Foundation to solve a fundamental problem that plagues artificial neural networks. Christopher Kanan, an assistant professor in the Chester F.

Can We Teach AI to Learn from Mistakes Without Forgetting

Can AI learn without forgetting? Explore five levels of continual learning and the stability-plasticity tradeoff to plan better AI roadmaps.
VentureBeat

Researchers find that retraining only small parts of AI models can cut costs and prevent forgetting

Enterprises often find that when they fine-tune models, one effective approach to making a large language model (LLM) fit for purpose and grounded in data is to have the model lose some of its ...
EurekAlert!

Novel memristors to overcome AI’s "catastrophic forgetting"

They consume extremely little power and behave similarly to brain cells: so-called memristors. Researchers from Jülich, led by Ilia Valov, have now introduced novel memristive components in Nature ...