<ul><li>Running AI locally provides more control, privacy, and eliminates concerns like rate limits and data security.</li><li>Transitioning to local AI means no reliance on external services, ensuring data stays on the user's machine.</li><li>Local AI tools offer quick responses without network lag or dependence on cloud resources.</li><li>With local AI, users can work offline and have more direct interaction with AI models.</li><li>Setting up and running local AI models is accessible to developers, writers, and designers.</li><li>Users can run small to medium-sized models effectively on modern machines without cloud dependencies.</li><li>Tools like Ollama and LM Studio optimize memory usage for smooth local AI operation.</li><li>Installing local AI tools is straightforward, requiring basic setup skills comparable to npm installation.</li><li>The local AI landscape has evolved with mature tooling that offers an improved user experience.</li><li>Local AI allows users to prototype in the cloud and then deploy or experiment locally.</li></ul>

Why I stopped using hosted AI and ran one on my own machine

Discover more