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1. Introduction The phrase “generalizing outside its training distribution” is at once both captivating and intimidating to those studying artificial...

Introduction The study by Sun et al. (“Predicting Human Brain States with Transformer”) advances the exploration of whether future human...

Introduction Inference scaling has emerged as a cornerstone in advancing artificial intelligence (AI), particularly within machine learning (ML) and deep...

Inference scaling has emerged as a novel and startling paradigm that stretches the boundaries of conventional AI development. In Ryan...

TLDR; Self-adaptation stands poised to become a transformative force in the evolution of large language models (LLMs). Traditional fine-tuning pipelines...

Agent Laboratory endeavors to reconfigure how machine learning (ML) research is conducted by placing large language model (LLM) agents at...

The paper "MiniMax-01: Scaling Foundation Models with Lightning Attention" presents a groundbreaking framework for large language models (LLMs) capable of...

Table of Contents Abstract Introduction The Concept of Take-Off Speeds 3.1 Slow Take-Off 3.2 Moderate Take-Off 3.3 Fast (Hard) Take-Off...

TLDR; This paper introduces Titans, an architectural framework that combines short-term memory (via an attention mechanism) with a novel long-term...

INTRODUCTION AND FOREWORD OpenAI’s “AI in America: Economic Blueprint” begins with a Foreword that underscores the organization’s overriding mission: ensuring...