<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Latent Space</title><description>Towards observable, reliable, scalable AI</description><link>https://jaesolshingithub-pd62u3eme-ysys143s-projects.vercel.app</link><language>en</language><managingEditor>Jaesol Shin</managingEditor><webMaster>Jaesol Shin</webMaster><category>Research</category><category>Artificial Life</category><category>Complexity Science</category><category>Computational Neuroscience</category><docs>https://www.rssboard.org/rss-specification</docs><generator>Astro + @astrojs/rss</generator><copyright>Copyright 2026 Jaesol Shin</copyright><lastBuildDate>Fri, 15 May 2026 18:40:19 GMT</lastBuildDate><item><title>Life As It Could Be</title><link>https://jaesolshingithub-pd62u3eme-ysys143s-projects.vercel.app/posts/alife_summary</link><guid isPermaLink="true">https://jaesolshingithub-pd62u3eme-ysys143s-projects.vercel.app/posts/alife_summary</guid><description>A guide to the field of Artificial Life, introduced at the ALife 2025 conference exhibition &apos;Life As It Could Be&apos;.</description><pubDate>Thu, 16 Oct 2025 00:00:00 GMT</pubDate><category>Research</category><tags>artificial life, alife, complexity science, emergence, conference</tags><wordCount>7877</wordCount><language>en</language><author>Jaesol Shin</author></item><item><title>GitHub Models Inference API로 무료 AI 모델 사용하기</title><link>https://jaesolshingithub-pd62u3eme-ysys143s-projects.vercel.app/posts/github-inference-api</link><guid isPermaLink="true">https://jaesolshingithub-pd62u3eme-ysys143s-projects.vercel.app/posts/github-inference-api</guid><description>GitHub의 무료 AI 모델 추론 API를 활용하여 GPT-4.1, DeepSeek R1 등 다양한 최신 AI 모델을 손쉽게 사용하는 방법</description><pubDate>Thu, 16 Oct 2025 00:00:00 GMT</pubDate><category>Development</category><tags>GitHub, Inference API, AI, API, machine learning, GPT-4, DeepSeek, OpenAI</tags><wordCount>1340</wordCount><language>en</language><author>Jaesol Shin</author></item><item><title>GPT-5 Responses API 웹 검색 도구 실험</title><link>https://jaesolshingithub-pd62u3eme-ysys143s-projects.vercel.app/posts/gpt5-web-search-api</link><guid isPermaLink="true">https://jaesolshingithub-pd62u3eme-ysys143s-projects.vercel.app/posts/gpt5-web-search-api</guid><description>OpenAI GPT-5 Responses API의 웹 검색 기능 구현 과정에서 발견한 모델별 도구 지원 차이와 파라미터 구성 방식에 대한 실험 기록. gpt-5와 gpt-5-chat-latest 모델 간 웹 검색 도구 호환성 차이를 중심으로 API 호출 실험 결과를 분석한다.</description><pubDate>Thu, 16 Oct 2025 00:00:00 GMT</pubDate><category>AI</category><tags>AI, GPT-5, API, web search, OpenAI, tutorial</tags><wordCount>933</wordCount><language>en</language><author>Jaesol Shin</author></item><item><title>OpenAI 모델 비교 분석 - GPT부터 o-시리즈까지</title><link>https://jaesolshingithub-pd62u3eme-ysys143s-projects.vercel.app/posts/openai-models-comparison</link><guid isPermaLink="true">https://jaesolshingithub-pd62u3eme-ysys143s-projects.vercel.app/posts/openai-models-comparison</guid><description>GPT-4, GPT-5, o1, o3, o4 등 OpenAI 언어 모델들에 대한 추론 능력, 응답 시간, 정확도의 정량적 성능 측정 실험 기록</description><pubDate>Thu, 16 Oct 2025 00:00:00 GMT</pubDate><category>Research</category><tags>OpenAI, GPT, model comparison, AI, language models, 추론 모델, 성능 분석</tags><wordCount>2096</wordCount><language>en</language><author>Jaesol Shin</author></item></channel></rss>