The article discusses the increasing usefulness of running AI models locally, highlighting benefits like latency, privacy, cost, and control. It explores practical applications such as data processing, note-taking, voice assistance, and self-sufficiency, while acknowledging the limitations compared to cloud-based models.
The article discusses the growing trend of running Large Language Models (LLMs) locally on personal machines, exploring the motivations behind this shift โ including privacy concerns, cost savings, and a desire for technological sovereignty โ as well as the hardware and software advancements making it increasingly feasible.