This tutorial guides you through installing and using an inference snap, specifically Qwen 2.5 VL, a multi-modal large language model. It covers installation, status checks, basic chat, and configuring Open WebUI for image-based prompts.
Canonical today announced optimized inference snaps, a new way to deploy AI models on Ubuntu devices, with automatic selection of optimized engines, quantizations and architectures based on the specific silicon of the device.
On October 23rd, we announced the beta availability of silicon-optimized AI models in Ubuntu. Developers can locally install DeepSeek R1 and Qwen 2.5 VL with a single command, benefiting from maximized hardware performance and automated dependency management.
Answering end user security questions is challenging. While large language models (LLMs) like GPT, LLAMA, and Gemini are far from error-free, they have shown promise in answering a variety of questions outside of security. We studied LLM performance in the area of end user security by qualitatively evaluating 3 popular LLMs on 900 systematically collected end user security questions. While LLMs demonstrate broad generalist ``knowledge'' of end user security information, there are patterns of errors and limitations across LLMs consisting of stale and inaccurate answers, and indirect or unresponsive communication styles, all of which impacts the quality of information received. Based on these patterns, we suggest directions for model improvement and recommend user strategies for interacting with LLMs when seeking assistance with security.
Grammarly is rebranding as "Superhuman" after acquiring Superhuman, while keeping current product names. They're launching "Superhuman Go," an AI assistant integrating with apps like Gmail and Jira to enhance writing and automate tasks. Features include logging tickets, scheduling, and data fetching from CRMs.
LLMII uses a local LLM to label metadata and index images. It does not rely on a cloud service or database. A visual language model runs on your computer and is used to create captions and keywords for images in a directory tree. The generated information is then added to each image file's metadata.
Superhuman Go is a proactive AI assistant that integrates with 100+ apps to help you write better, schedule meetings, prepare for discussions, and handle admin tasks. It's available for free during early access via Grammarly for Chrome and Edge.
This paper addresses the misalignment between traditional IR evaluation metrics and the requirements of modern Retrieval-Augmented Generation (RAG) systems. It proposes a novel annotation schema and the UDCG metric to better evaluate retrieval quality for LLM consumers.
This blog post details how to build a natural language Bash agent using NVIDIA Nemotron Nano v2, requiring roughly 200 lines of Python code. It covers the core components, safety considerations, and offers both a from-scratch implementation and a simplified approach using LangGraph.
Tips for setting up a codebase to be more productive with AI coding tools, including automated tests, interactive testing, issue tracking, documentation, and linters/formatters.
