New model frames human reinforcement learning in the context of memory and habits

Humans and most other animals are known to be strongly driven by expected rewards or adverse consequences. The process of ...
Forbes

Generative AI Becomes Domain Savvy Via In-Context Learning And Advanced Prompt Engineering

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. You would be hard-pressed to say that one or the other is ...
Morning Overview on MSN

Your brain has a learning shortcut that AI still can’t copy

Human brains can turn a single messy experience into a lasting skill, while even the most advanced artificial intelligence ...
VentureBeat

Google’s ‘Nested Learning’ paradigm could solve AI's memory and continual learning problem

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 ...
VentureBeat

ACE prevents context collapse with ‘evolving playbooks’ for self-improving AI agents

A new framework from Stanford University and SambaNova addresses a critical challenge in building robust AI agents: context engineering. Called Agentic Context Engineering (ACE), the framework ...
Search Engine Roundtable

Jeff Dean: Combining Google Search With LLM In-Context Learning

Dwarkesh Patel interviewed Jeff Dean and Noam Shazeer of Google and one topic he asked about what would it be like to merge or combine Google Search with in-context learning. It resulted in a ...
technologynetworks

Humans and AI Blend Two Types of Learning

Brown University researchers found that humans and AI integrate two types of learning – fast, flexible learning and slower, incremental learning – in surprisingly similar ways. The study revealed ...