SQL will continue to serve as the lingua franca but the world of data will speak in graphs, vectors, LLMs too– and relational databases will stay but not in the same chair. Here’s why?

Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...

Obsidian is already great, but my local LLM makes it better ...

Macy is a writer on the AI Team. She covers how AI is changing daily life and how to make the most of it. This includes writing about consumer AI products and their real-world impact, from ...

Use the vitals package with ellmer to evaluate and compare the accuracy of LLMs, including writing evals to test local models ...

AI coding tools have enabled a flood of bad code that threatens to overwhelm many projects. Building new features is easier ...

Trillion Parameter run achieved with DeepSeek R1 671B model on 36 Nvidia H100 GPUs We are pleased to offer a Trillion ...

Reasoning large language models (LLMs) are designed to solve complex problems by breaking them down into a series of smaller ...

BEIJING, Feb 5 (Reuters) - China's industry ministry on Thursday warned that the OpenClaw open-source AI agent, which gained global popularity in recent weeks, could pose significant security risks ...

Gensonix AI DB efficiency combined with the power of Meta's Llama 3B model and AMD's Radeon GPU architecture makes LLMs ...

Many of us think of reading as building a mental database we can query later. But we forget most of what we read. A better analogy? Reading trains our internal large language models, reshaping how we ...