<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Local &amp; On-device AI — The Latent Daily</title><description>Running models locally and on the edge.</description><link>https://thelatentdaily.com/</link><language>en-us</language><atom:link href="https://thelatentdaily.com/rss/local-ai.xml" rel="self" type="application/rss+xml"/><item><title>How to transcribe audio on your own computer with Whisper</title><link>https://thelatentdaily.com/guides/transcribe-audio-locally-with-whisper/</link><guid isPermaLink="true">https://thelatentdaily.com/guides/transcribe-audio-locally-with-whisper/</guid><description>Install OpenAI&apos;s open-source Whisper speech recognition model, transcribe recordings offline, choose the right model size and export subtitles in minutes.</description><pubDate>Sun, 18 Oct 2026 05:47:00 GMT</pubDate><category>Guides &amp; Tutorials</category><category>guides</category><category>speech</category><category>local-ai</category><category>open-source</category><category>whisper</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>How to run a local LLM with Ollama: installation to first chat</title><link>https://thelatentdaily.com/guides/run-local-llm-with-ollama-guide/</link><guid isPermaLink="true">https://thelatentdaily.com/guides/run-local-llm-with-ollama-guide/</guid><description>Install Ollama, download an open model, chat in the terminal or a web interface, pick a model that fits your memory and use the local API from your own code.</description><pubDate>Sun, 18 Oct 2026 04:47:00 GMT</pubDate><category>Local &amp; On-device AI</category><category>local-ai</category><category>ollama</category><category>open-weights</category><category>privacy</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Quantization explained: how big AI models run on small hardware</title><link>https://thelatentdaily.com/guides/quantization-explained-running-big-models/</link><guid isPermaLink="true">https://thelatentdaily.com/guides/quantization-explained-running-big-models/</guid><description>Quantization shrinks AI models by storing weights with fewer bits. How 8-bit and 4-bit formats work, GGUF, GPTQ and AWQ, and the quality trade-offs to expect.</description><pubDate>Sun, 18 Oct 2026 04:46:00 GMT</pubDate><category>Local &amp; On-device AI</category><category>quantization</category><category>local-ai</category><category>inference</category><category>explainer</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>What is an NPU? AI PCs and on-device AI explained</title><link>https://thelatentdaily.com/articles/what-is-an-npu-ai-pcs-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/articles/what-is-an-npu-ai-pcs-explained/</guid><description>Neural processing units let laptops and phones run AI locally. What NPUs do, what &quot;40 TOPS&quot; means, which features use them and whether you need an AI PC.</description><pubDate>Sun, 18 Oct 2026 04:35:00 GMT</pubDate><category>AI PCs, Phones &amp; Devices</category><category>npu</category><category>ai-pc</category><category>devices</category><category>on-device-ai</category><author>dario_admin@resolvia-crm.tech</author></item></channel></rss>