Experimental new browser engine. Parses HTML/CSS, computes styles, performs layout, and paints pixels. Includes a desktop browser shell and JavaScript execution via an embedded JS engine.
This project shows you how to set up the BirdNET-Pi software on your Raspberry Pi to detect and classify birds in real-time based on their bird calls.
Israeli tech CEO Shlomo Kramer argues the US government should restrict freedom of speech and control social media platforms to combat the spread of misinformation, particularly in the age of AI.
An analysis of the current LLM landscape in 2026, focusing on the shift from 'vibe coding' to more efficient and controlled workflows for software development and data analysis. The author advocates for tools like AI Studio and OpenCode, and discusses the strengths of models like Gemini 2.5 Pro and Claude Sonnet.
A review of the SearchResearch blog's 2025 posts, highlighting a shift towards AI-augmented research methods, testing AI tools, and emphasizing the importance of verification and critical thinking in online research.
Nemo Agent Toolkit simplifies building production-ready LLM applications by providing tools for creating, managing, and deploying agents. It offers features like memory management, tool usage, and observability, making it easier to integrate LLMs into real-world applications.
Orange Pi has announced the Orange Pi AI Station, a compact edge computing platform featuring the Ascend 310 processor, offering up to 176 TOPS of AI compute performance with options for up to 96GB of LPDDR4X memory and NVMe storage.
A data-driven computational framework for deriving low-dimensional linear models for nonlinear dynamical systems from experimental data, enabling global stability analysis and accurate predictions.
Amazon S3 Vectors is now generally available with increased scale and production-grade performance capabilities. It offers native support to store and query vector data, potentially reducing costs by up to 90% compared to specialized vector databases.
A comprehensive overview of the current state of Multi-Concept Prompting (MCP), including advancements, challenges, and future directions.
