By allowing models to actively update their weights during inference, Test-Time Training (TTT) creates a "compressed memory" ...

A new computational model of the brain based closely on its biology and physiology has not only learned a simple visual ...

Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...

Discover research on memorization techniques for studying. Learn how repetition learning theory and spaced repetition boost ...

A biologically grounded computational model built to mimic real neural circuits, not trained on animal data, learned a visual categorization task just as actual lab animals do, matching their accuracy ...

Anti-forgetting representation learning method reduces the weight aggregation interference on model memory and augments the ...

One of the most actively debated questions about human and non-human culture is this: under what circumstances might we expect culture, in particular the ability to learn from one another, to be ...

In our age of information overload, remembering things can be a daunting task. But as a memory researcher and college professor, I’ve found some hope in that challenge. In January 2021, like millions ...

Since no one ever does anything worthwhile on their own, who you know is important. But what you know — and what you do with what you know — is crucial. Learning, memory, and cognitive skills are a ...

In modern CPU device operation, 80% to 90% of energy consumption and timing delays are caused by the movement of data between the CPU and off-chip memory. To alleviate this performance concern, ...