Author: Samuel Alejandro

The Shirley Jackson Award-winning book from Victor LaValle is an anti-racist take on Lovecraft.

The newly launched Mozilla AI Guide serves as a comprehensive resource for developers exploring AI, with an initial focus on language models. This guide demonstrates practical text summarization using open-source models, highlighting the importance of model evaluation, responsible AI practices, and community collaboration in the evolving AI landscape.

OpenAI commits $50M in funding and tools to leading institutions.

Linux offers significant advantages for PC gaming, yet Windows remains the dominant operating system, with no immediate threat to its market position.

This motion-tracking game console has become a hot ticket item this holiday season, despite its quirks.

Georgian prosecutors have arrested the country’s former security service head, Grigol Liluashvili, on bribery charges. He is accused of protecting fraudulent call centers that defrauded victims globally, with investigators alleging he received approximately $1.4 million in bribes.

A new chapter for TNW begins, focusing on practical innovation, responsible scaling, and community-driven intelligence. Following a recent acquisition, TNW continues its mission as a global tech media platform, emphasizing editorial independence and curated events across Europe, with a strong focus on AI and future technologies.

GitHub Issues search has been enhanced with powerful new capabilities, including support for nested queries and boolean operators. This update allows users to construct more precise and complex search queries, significantly improving the ability to find specific issues and pull requests within repositories.

Spending too much time on repetitive tasks? These Python scripts will help you automate the mundane stuff that drains your productivity.

As AI agents engage more extensively with users, their memory systems gather vast amounts of data. However, not all stored memories hold the same significance. The presence of duplicate, low-quality, or outdated information can hinder retrieval efficiency, escalate storage expenses, and negatively impact decision-making precision. This article explores the intelligent memory optimization engine within Cortex Memory, explaining how Large Language Models (LLMs) are utilized for automated detection, deduplication, merging, and overall optimization of memory quality, thereby ensuring a consistently high signal-to-noise ratio in the memory repository.