The key in agentic AI is establishing clear "expertise directories" and communication protocols using transactive memory ...

A context-driven memory model simulates a wide range of characteristics of waking and sleeping hippocampal replay, providing ...

The next major evolution will come from multi-agent systems—networks of smaller, specialized AI models that coordinate across ...

Through systematic experiments DeepSeek found the optimal balance between computation and memory with 75% of sparse model ...

Abstract: Short-term time series forecasting is pivotal in various scientific and industrial fields. Recent advancements in deep learning-based technologies have significantly improved the efficiency ...

Apple ( AAPL) has chosen Google's ( GOOG) ( GOOGL) Gemini artificial intelligence models to run its next version of Siri.

Artificial intelligence systems can now write code, summarize legal contracts, and help design new drugs, yet the people ...

For most people, the future of artificial intelligence still looks like a single assistant that can handle anything. In ...

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.

Abstract: The endeavor of stock trend forecasting is principally focused on predicting the future trajectory of the stock market, utilizing either manual or technical methodologies to optimize ...

We introduce LEGOMem, a modular procedural memory framework for multi-agent large language model (LLM) systems in workflow automation. LEGOMem decomposes past task trajectories into reusable memory ...

Memory shortage could delay AI projects, productivity gains SK Hynix predicts memory shortage to last through late 2027 Smartphone makers warn of price rises due to soaring memory costs Dec 3 (Reuters ...