Opinion

How do different data preprocessing techniques affect performance of machine learning models on prediction tasks?

Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...
The New York Times

Silicon Valley Wants to Build A.I. That Can Improve A.I. on Its Own

Ricursive Intelligence, founded by two former Google researchers and valued at $4 billion, is among several efforts to automate the creation of artificial intelligence. Anna Goldie and Azalia ...
InfoQ

MIT's Recursive Language Models Improve Performance on Long-Context Tasks

Researchers at MIT's CSAIL published a design for Recursive Language Models (RLM), a technique for improving LLM performance on long-context tasks. RLMs use a programming environment to recursively ...
VentureBeat

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

Recursive language models (RLMs) are an inference technique developed by researchers at MIT CSAIL that treat long prompts as an external environment to the model. Instead of forcing the entire prompt ...
STAT

Recursion CEO Chris Gibson out as company head after 12 years

After 12 years leading Utah-based techbio company Recursion, CEO Chris Gibson is stepping down. Recursion’s R&D head and Chief Commercial Officer Najat Khan will become CEO effective Jan. 1. Gibson co ...
GitHub

Expand Selection Obsidian Plugin

An Obsidian plugin to expand your editor selection to lines, sections (recursive), or the entire note. This plugin is primarily designed for mobile convenience. "Expand to Section" is useful on ...
IEEE

Feature Selection for Battery Lifetime Prediction Using Explainable Machine Learning

Abstract: Accurate battery lifetime estimation is crucial for health management and system safety. Data-driven research yields extensive feature sets, yet optimal feature selection is often impeded by ...
Frontiers

An explainable machine learning model for predicting chronic coronary disease and identifying valuable text features

Chronic Coronary Disease (CCD) is a leading global cause of morbidity and mortality. Existing Pre-test Probability (PTP) models mainly rely on in-hospital data and clinician judgment. This study aims ...
IEEE

Recursive Statistical Invariants Elimination for High-Risk Disease Diagnosis with Feature Selection

Abstract: Feature selection for high-risk disease diagnosis is critical for accurate risk assessment, yet existing methods fail to incorporate medical domain knowledge, potentially leading to ...