<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Jansen Ang on foojay.io - Friends of OpenJDK</title><link>https://foojayio.github.io/website/today/author/jansen-ang/</link><description>Articles written by Jansen Ang on foojay.io - Friends of OpenJDK</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sun, 12 May 2024 05:31:16 +0000</lastBuildDate><atom:link href="https://foojayio.github.io/website/today/author/jansen-ang/index.xml" rel="self" type="application/rss+xml"/><item><title>Building a Simple Home Assistant using Langchain4j and Raspberry Pi</title><link>https://foojayio.github.io/website/today/building-simple-home-assistant-langchain4j-raspberry-pi/</link><pubDate>Sun, 12 May 2024 05:31:16 +0000</pubDate><guid>https://foojayio.github.io/website/today/building-simple-home-assistant-langchain4j-raspberry-pi/</guid><description>&lt;p&gt;&lt;strong&gt;Many believe that the future of IoT is AI. Building a Smart Home Assistant is less complex today than ever before. AI has become so accessible that you only need an internet connection and a computer to connect to an API.&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;While training specialized deep learning models or using commercial APIs to harness machine learning for specific deterministic use cases is still an option, it is now more common and accessible to use LLMs. Today, you can effortlessly utilize numerous LLMs from various providers through an LLM orchestration framework like &lt;a href="https://github.com/langchain4j/langchain4j" target="_blank" rel="noopener noreferrer"&gt;Langchain4j&lt;/a&gt;
. This framework not only allows the use of LLMs but also provides components that simplify the creation of AI applications such as chatbots and question-answering systems. With these tools, anyone can assemble a Generative AI-powered app in minutes.&lt;/p&gt;</description></item></channel></rss>