Abstract: To address the problem of passive knowledge forgetting in real-time training of Radial Basis Function Neural Networks (RBFNNs), the Selective Memory Recursive Least Squares (SMRLS) algorithm ...

A major problem with quantum computers is memory, as the information they contain can be quickly lost. Quantum computers are not yet fully reliable—they are far too unstable. However, all around the ...

The compression algorithm works by shrinking the data stored by large language models, with Google’s research finding that it can reduce memory usage by at least six times “with zero accuracy loss.” ...

If Google’s AI researchers had a sense of humor, they would have called TurboQuant, the new, ultra-efficient AI memory compression algorithm announced Tuesday, “Pied Piper” — or, at least that’s what ...

Google (GOOG)(GOOGL) revealed a set of new algorithms today designed to reduce the amount of memory needed to run large language models and vector search engines. The algorithms introduced by Google ...

Qualcomm and Arm Holdings were sinking early Thursday as the surging memory-chip prices that are hurting the smartphone market threaten their prospects.

Qualcomm Inc disappoints with Q2 guidance citing global memory shortage. Here's why QCOM shares are well positioned to weather the supply constraints. Qualcomm stock is currently down more than 25% ...

If we want to avoid making AI agents a huge new attack surface, we’ve got to treat agent memory the way we treat databases: with firewalls, audits, and access privileges. The pace at which large ...

Among high school students and adults, girls and women are much more likely to use traditional, step-by-step algorithms to solve basic math problems – such as lining up numbers to add, starting with ...

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 ...