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 ...
EurekAlert!

Deterministic streaming algorithms for non-monotone submodular maximization

Submodular maximization is a significant area of interest in combinatorial optimization, with numerous real-world applications. A research team led by Xiaoming SUN from the State Key Lab of Processors ...
blockchain

Samsung’s Tiny Recursive Model (TRM) Outperforms Leading LLMs in Grid Puzzle AI Benchmarks

According to DeepLearning.AI, Samsung’s Tiny Recursive Model (TRM) utilizes iterative answer refinement and maintains a context of previous changes to tackle complex grid puzzles such as Sudoku, Mazes ...
IEEE

Robust Diffusion Recursive Algorithm for Distributed Widely-Linear Exponential Functional Link Network

Abstract: Distributed adaptive filtering has emerged as a critical methodology across diverse application domains, including wireless sensor networks, distributed signal processing, and intelligent ...
Frontiers

Visual recursion without recursive language? a case study of a minimally verbal autistic child

The human faculty to generate an infinite set of structured expressions in language, present in most cultures and normal ontogeny, is the most substantial evidence of the human capacity for recursion.
Frontiers

Enhancing tool condition monitoring in friction stir welding with probabilistic neural network algorithm

1 School of Mechanical Engineering, Vellore Institute of Technology, Chennai, India 2 Centre for e-Automation Technologies, Vellore Institute of Technology, Chennai, India Introduction: Friction Stir ...
Forbes

Changing The World One Algorithm At A Time With AI In Non-Profits

We often think about the impact AI is making on profitable businesses and even governmental organizations, but AI is also making significant contributions to the operations and success of non-profit ...
Science Daily

Deep learning algorithm used to pinpoint potential disease-causing variants in non-coding regions of the human genome

Researchers have successfully employed an algorithm to identify potential mutations which increase disease risk in the noncoding regions our DNA, which make up the vast majority of the human genome.