Search Results: Ollama

Learn how to build Retrieval-Augmented Generation (RAG) systems that query proprietary documents using locally hosted LLMs. James Briggs' new tutorial demonstrates integrating Ollama for open-source model execution and LangChain for pipeline orchestration, empowering developers to create private, cost-efficient AI assistants without cloud dependencies.

Cisco researchers uncovered widespread security lapses in large language model deployments, identifying over 1,100 publicly accessible Ollama servers vulnerable to unauthorized access and prompt injection. The study leverages Shodan scanning to reveal how default configurations enable risks like model theft and resource hijacking, demanding urgent industry-wide security reforms.

Open-source AI just got more accessible with a straightforward guide to installing and running GPT-OSS models using Ollama on your local machine. This approach empowers developers to experiment with large language models without cloud dependencies, offering insights into performance on hardware like Apple's M-series chips. Dive into the implications for open-source innovation and personal AI development.

NativeMind launches a browser extension that leverages Ollama to run large language models entirely on-device, eliminating cloud dependencies. This open-source tool enables private webpage summarization, cross-tab chat, and local web searches while ensuring zero data leaves users' machines.

Ollama's latest release enables developers to run state-of-the-art large language models like DeepSeek-R1 and Llama 3.3 locally on macOS, Linux, and Windows. This shift reduces cloud dependencies, lowers costs, and unlocks new possibilities for private, low-latency AI applications.