the-decoder

Anthropic co-founder maps out how recursive AI improvement could outpace the humans meant to supervise it

Jack Clark argues in a long essay that the building blocks for AI systems training their own successors are largely in place. He puts the odds at 60 percent by the end of 2028. In his newsletter ...
unite

Recursive Superintelligence Raises $650 Million to Pursue Self-Improving AI

A new frontier AI company called Recursive Superintelligence has emerged from stealth with $650 million in funding and an unusually ambitious goal: building AI systems capable of improving themselves ...
IEEE

An Ensemble Convolutional Recursive Neural Network Based on Deep Reinforcement Learning for Traffic Volume Forecasting

Abstract: Intelligent transportation systems are of great significance to urban sustainable development and management. As a crucial element of an intelligent transportation system, traffic volume ...
IEEE

Design of an Approximate Recursive Multiplier Based on Probability-Driven Intercolumn Error Cancellation and Its Application in Deep Neural Networks

Abstract: This article proposes a probability-driven intercolumn error cancellation mechanism for approximate multiplier design, enabling an improved tradeoff between ...
GitHub

Mixture-of-Recursions: Learning Dynamic Recursive Depths for Adaptive Token-Level Computation (NeurIPS 2025)

Missing Key-Value (KV) cache problem: When tokens exit early, they skip computing the KV pairs for remained deeper layers. But these missing values are essential for decoding future tokens, and trying ...