MIT’s new ‘recursive’ framework lets LLMs process 10 million tokens without context rot

While standard models suffer from context rot as data grows, MIT’s new Recursive Language Model (RLM) framework treats ...
Unite.AI

When AI Agents Start Building AI: The Recursive Intelligence Explosion Nobody’s Prepared For

For decades, artificial intelligence advanced in careful, mostly linear steps. Researchers built models. Engineers improved performance. Organizations deployed systems to automate specific tasks. Each ...
IEEE

Outlier-Aware Recursive Instantaneous Minimum Error Entropy Algorithm

Abstract: The minimum error entropy (MEE) criterion closely relies on the quadratic information potential (QIP) estimates of Renyi’s entropy. Nevertheless, the ...
IEEE

A Nonparametric Variable Forgetting Factor Recursive Least-Squares Algorithm

Abstract: The forgetting factor is the main control parameter of the recursive least-squares (RLS) algorithm, which is set to balance between the estimate accuracy and the tracking capability.
GitHub

Add Flowcharts for Algorithm Understanding

What would you like to Propose? I propose adding flowcharts for selected algorithms to make it easier for beginners to understand the logic visually. Flowcharts will complement the existing code ...
Nasdaq

MicroAlgo Inc. Unveils Quantum Information Recursive Optimization (QIRO) Algorithm for Enhanced Combinatorial Optimization Solutions

MicroAlgo Inc. announced its research on the Quantum Information Recursive Optimization (QIRO) algorithm, which aims to address complex combinatorial optimization problems using quantum computing.
pv magazine International

Recursive least squares algorithms to detect abnormal operation in PV systems

Scientists in Spain have implemented recursive least squares (RLS) algorithms for anomaly detection in PV systems and have found they can provide “more realistic and meaningful assessment” than ...
Frontiers

Feature elimination and stacking framework for accurate heart disease detection in IoT healthcare systems using clinical data

Introduction: Heart disease remains a complex and critical health issue, necessitating accurate and timely detection methods. Methods: In this research, we present an advanced machine learning system ...