Abstract: In the context of Electroencephalography (EEG) research, how is Working Memory (WM) leveraged in Human-Computer Interaction (HCI)? To address this question, this paper explores how WM is ...
Instructed Retriever leverages contextual memory for system-level specifications while using retrieval to access the broader ...
Loosh launches a cognitive engine giving AI memory, ethics, and decentralized intelligence for real-world autonomy.
AI's memory capacity is still limited. Solving that may be the key to unlocking superintelligence.
As digital complexity outpaces human capacity, a new role is emerging: the AI CTO. Here's how autonomous AI systems are ...
Abstract: Human action understanding serves as a foundational pillar in the field of intelligent motion perception.Skeletons serve as a modality- and device-agnostic representation for human modeling, ...
Shared memory is a state where every AI agent in a system draws from the same evolving understanding of a task, issue, or ...
In 2026, here's what you can expect from the AI industry: new architectures, smaller models, world models, reliable agents, ...
Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.
Here is the AI research roadmap for 2026: how agents that learn, self-correct, and simulate the real world will redefine ...
Researchers from the University of Edinburgh and NVIDIA have introduced a new method that helps large language models reason more deeply without increasing their size or energy use. The work, ...
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