The rise of large language models (LLMs) has sparked questions about their computational abilities compared to traditional models. While recent research has shown that LLMs can simulate a universal ...

Large language models (LLMs) like GPTs, developed from extensive datasets, have shown remarkable abilities in understanding language, reasoning, and planning. Yet, for AI to reach its full potential, ...

Multimodal Large Language Models (MLLMs) have rapidly become a focal point in AI research. Closed-source models like GPT-4o, GPT-4V, Gemini-1.5, and Claude-3.5 exemplify the impressive capabilities of ...

Cellular automata (CA) have become essential for exploring complex phenomena like emergence and self-organization across fields such as neuroscience, artificial life, and theoretical physics. Yet, the ...

The rise of large language models (LLMs) has equipped AI agents with the ability to interact with users through natural, human-like conversations. As a result, these agents now face dual ...

Building on MM1’s success, Apple’s new paper, MM1.5: Methods, Analysis & Insights from Multimodal LLM Fine-tuning, introduces an improved model family aimed at enhancing capabilities in text-rich ...

Tools designed for rewriting, refactoring, and optimizing code should prioritize both speed and accuracy. Large language models (LLMs), however, often lack these critical attributes. Despite these ...

In a new paper CAX: Cellular Automata Accelerated in JAX, a research team introduces Cellular Automata Accelerated in JAX, a powerful open-source library designed to enhance CA research, which enables ...

In a new paper Don’t Transform the Code, Code the Transforms: Towards Precise Code Rewriting using LLMs, a Meta research team proposes a novel chain-of-thought strategy to efficiently generate code ...

Monocular Depth Estimation, which involves estimating depth from a single image, holds tremendous potential. It can add a third dimension to any image—regardless of when or how it was captured—without ...