<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>Gea-Suan Lin&#039;s BLOG</title>
	<atom:link href="https://blog.gslin.org/feed/" rel="self" type="application/rss+xml" />
	<link>https://blog.gslin.org</link>
	<description>幹壞事是進步最大的原動力</description>
	<lastBuildDate>Fri, 30 Oct 2026 04:35:48 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	<generator>https://wordpress.org/?v=7.1.4</generator>
<atom:link rel="hub" href="https://pubsubhubbub.appspot.com"/>
<atom:link rel="hub" href="https://pubsubhubbub.superfeedr.com"/>
<atom:link rel="hub" href="https://websubhub.com/hub"/>
<atom:link rel="self" href="https://blog.gslin.org/feed/"/>
<site xmlns="com-wordpress:feed-additions:1">21326247</site>	<item>
		<title>OpenAI 對 US$100/mo 以上的方案調高使用額度</title>
		<link>https://blog.gslin.org/archives/2026/10/30/13309/openai-%e5%b0%8d-us100-mo-%e4%bb%a5%e4%b8%8a%e7%9a%84%e6%96%b9%e6%a1%88%e8%aa%bf%e9%ab%98%e4%bd%bf%e7%94%a8%e9%a1%8d%e5%ba%a6/</link>
					<comments>https://blog.gslin.org/archives/2026/10/30/13309/openai-%e5%b0%8d-us100-mo-%e4%bb%a5%e4%b8%8a%e7%9a%84%e6%96%b9%e6%a1%88%e8%aa%bf%e9%ab%98%e4%bd%bf%e7%94%a8%e9%a1%8d%e5%ba%a6/#respond</comments>
		
		<dc:creator><![CDATA[Gea-Suan Lin]]></dc:creator>
		<pubDate>Fri, 30 Oct 2026 04:35:48 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[Murmuring]]></category>
		<category><![CDATA[Network]]></category>
		<category><![CDATA[Service]]></category>
		<category><![CDATA[ai]]></category>
		<category><![CDATA[language]]></category>
		<category><![CDATA[large]]></category>
		<category><![CDATA[llm]]></category>
		<category><![CDATA[model]]></category>
		<category><![CDATA[openai]]></category>
		<category><![CDATA[plan]]></category>
		<category><![CDATA[pro]]></category>
		<category><![CDATA[subscription]]></category>
		<category><![CDATA[tier]]></category>
		<category><![CDATA[usage]]></category>
		<guid isPermaLink="false">https://blog.gslin.org/?p=13309</guid>

					<description><![CDATA[出自 OpenAI 家 tibo 的 https://x.com/thsottiaux/status/2115850175868727621 公告： We are doubling all usage limits for all Pro 100/200/500 tiers and Business Premium, effective today. 看語氣應該是永久性的？所以等於是補貼補更多了...]]></description>
										<content:encoded><![CDATA[<p>出自 <a href="https://en.wikipedia.org/wiki/OpenAI">OpenAI</a> 家 tibo 的 <a href="https://x.com/thsottiaux/status/2115850175868727621">https://x.com/thsottiaux/status/2115850175868727621</a> 公告：</p>
<blockquote><p>We are doubling all usage limits for all Pro 100/200/500 tiers and Business Premium, effective today.</p></blockquote>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1793334694-10f3e27f.webp" /><img decoding="async" src="https://i.gslin.com/s/1793334694-10f3e27f.png" alt="" /></picture>
<p>看語氣應該是永久性的？所以等於是補貼補更多了...</p>
]]></content:encoded>
					
					<wfw:commentRss>https://blog.gslin.org/archives/2026/10/30/13309/openai-%e5%b0%8d-us100-mo-%e4%bb%a5%e4%b8%8a%e7%9a%84%e6%96%b9%e6%a1%88%e8%aa%bf%e9%ab%98%e4%bd%bf%e7%94%a8%e9%a1%8d%e5%ba%a6/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">13309</post-id>	</item>
		<item>
		<title>測了一下 MySQL/MariaDB 的監控軟體 Dolphie</title>
		<link>https://blog.gslin.org/archives/2026/10/30/13308/%e6%b8%ac%e4%ba%86%e4%b8%80%e4%b8%8b-mysql-mariadb-%e7%9a%84%e7%9b%a3%e6%8e%a7%e8%bb%9f%e9%ab%94-dolphie/</link>
					<comments>https://blog.gslin.org/archives/2026/10/30/13308/%e6%b8%ac%e4%ba%86%e4%b8%80%e4%b8%8b-mysql-mariadb-%e7%9a%84%e7%9b%a3%e6%8e%a7%e8%bb%9f%e9%ab%94-dolphie/#respond</comments>
		
		<dc:creator><![CDATA[Gea-Suan Lin]]></dc:creator>
		<pubDate>Fri, 30 Oct 2026 04:30:01 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[Database]]></category>
		<category><![CDATA[MariaDB]]></category>
		<category><![CDATA[Murmuring]]></category>
		<category><![CDATA[MySQL]]></category>
		<category><![CDATA[Software]]></category>
		<category><![CDATA[database]]></category>
		<category><![CDATA[db]]></category>
		<category><![CDATA[dolphie]]></category>
		<category><![CDATA[mariadb]]></category>
		<category><![CDATA[monitor]]></category>
		<category><![CDATA[monitoring]]></category>
		<category><![CDATA[mysql]]></category>
		<category><![CDATA[performance]]></category>
		<category><![CDATA[rdbms]]></category>
		<guid isPermaLink="false">https://blog.gslin.org/?p=13308</guid>

					<description><![CDATA[最近在 tune 自己架設的 MariaDB，就在想除了以前的工具還有什麼可以用的，問了 AI 後提到 Dolphie： Your single pane of glass for real-time analytics into MySQL/MariaDB &#38; ProxySQL 看起來類似 mytop，但功能更多？但考慮到 mytop 已經很久沒再加功能了，測一下用用看... 從 GitHub 上可以看到是 PyPI 的套件，所以可以直接透過 mise 的 pypi backend 裝起來 (需要在有安裝 Python 以及 pipx 的情況下)： mise use -g pypi:dolphie@latest 在有設定 ~/.my.cnf 的情況下，執行 dolphie 就可以用了，目前比較不習慣的應該是離開用 Ctrl-Q 而無法用 Ctrl-C，不過會跳提示，所以還行...？ 基本預設的資料其實還不錯？一些簡單但重要的資訊都有先帶出來，像是 InnoDB 的 buffer pool &#8230; <a href="https://blog.gslin.org/archives/2026/10/30/13308/%e6%b8%ac%e4%ba%86%e4%b8%80%e4%b8%8b-mysql-mariadb-%e7%9a%84%e7%9b%a3%e6%8e%a7%e8%bb%9f%e9%ab%94-dolphie/" class="more-link">Continue reading<span class="screen-reader-text"> "測了一下 MySQL/MariaDB 的監控軟體 Dolphie"</span></a>]]></description>
										<content:encoded><![CDATA[<p>最近在 tune 自己架設的 <a href="https://en.wikipedia.org/wiki/MariaDB">MariaDB</a>，就在想除了以前的工具還有什麼可以用的，問了 <a href="https://en.wikipedia.org/wiki/Artificial_intelligence">AI</a> 後提到 <a href="https://github.com/charles-001/dolphie">Dolphie</a>：</p>
<blockquote><p>Your single pane of glass for real-time analytics into MySQL/MariaDB &amp; ProxySQL</p></blockquote>
<p>看起來類似 mytop，但功能更多？但考慮到 mytop 已經很久沒再加功能了，測一下用用看...</p>
<p>從 <a href="https://en.wikipedia.org/wiki/GitHub">GitHub</a> 上可以看到是 <a href="https://en.wikipedia.org/wiki/Python_Package_Index">PyPI</a> 的套件，所以可以直接透過 <a href="https://mise.jdx.dev/">mise</a> 的 pypi backend 裝起來 (需要在有安裝 <a href="https://en.wikipedia.org/wiki/Python_(programming_language)">Python</a> 以及 <a href="https://pipx.pypa.io/">pipx</a> 的情況下)：</p>
<pre>mise use -g pypi:dolphie@latest</pre>
<p>在有設定 <code>~/.my.cnf</code> 的情況下，執行 <code>dolphie</code> 就可以用了，目前比較不習慣的應該是離開用 Ctrl-Q 而無法用 Ctrl-C，不過會跳提示，所以還行...？</p>
<p>基本預設的資料其實還不錯？一些簡單但重要的資訊都有先帶出來，像是 <a href="https://en.wikipedia.org/wiki/InnoDB">InnoDB</a> 的 buffer pool 的情況，以及 query 的類型：</p>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1793334483-ccf9d1c2.webp" /><img decoding="async" src="https://i.gslin.com/s/1793334483-ccf9d1c2.png" alt="" /></picture>
<p>應該會用一陣子看看...</p>
]]></content:encoded>
					
					<wfw:commentRss>https://blog.gslin.org/archives/2026/10/30/13308/%e6%b8%ac%e4%ba%86%e4%b8%80%e4%b8%8b-mysql-mariadb-%e7%9a%84%e7%9b%a3%e6%8e%a7%e8%bb%9f%e9%ab%94-dolphie/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">13308</post-id>	</item>
		<item>
		<title>Apple 內購抽成調低 (從 30% 降到 26%)</title>
		<link>https://blog.gslin.org/archives/2026/10/30/13307/apple-%e5%85%a7%e8%b3%bc%e6%8a%bd%e6%88%90%e8%aa%bf%e4%bd%8e-%e5%be%9e-30-%e9%99%8d%e5%88%b0-26/</link>
					<comments>https://blog.gslin.org/archives/2026/10/30/13307/apple-%e5%85%a7%e8%b3%bc%e6%8a%bd%e6%88%90%e8%aa%bf%e4%bd%8e-%e5%be%9e-30-%e9%99%8d%e5%88%b0-26/#respond</comments>
		
		<dc:creator><![CDATA[Gea-Suan Lin]]></dc:creator>
		<pubDate>Fri, 30 Oct 2026 04:17:25 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[Financial]]></category>
		<category><![CDATA[Murmuring]]></category>
		<category><![CDATA[Network]]></category>
		<category><![CDATA[app]]></category>
		<category><![CDATA[apple]]></category>
		<category><![CDATA[cost]]></category>
		<category><![CDATA[iap]]></category>
		<category><![CDATA[in-app]]></category>
		<category><![CDATA[ios]]></category>
		<category><![CDATA[ipados]]></category>
		<category><![CDATA[mobile]]></category>
		<category><![CDATA[pricing]]></category>
		<category><![CDATA[purchase]]></category>
		<category><![CDATA[store]]></category>
		<category><![CDATA[taiwan]]></category>
		<guid isPermaLink="false">https://blog.gslin.org/?p=13307</guid>

					<description><![CDATA[掃到這個「Apple Lowers App Store Fees in Taiwan Starting October 31」提到 Apple 內購的抽成調低，應該是「對 App Store 台灣店面的 iOS 及 iPadOS 的調整」這個公告： 自 2026 年 10 月 31 日起，適用於 App Store 台灣店面的 iOS 及 iPadOS 佣金率將進行調整。標準 Apple App 內購買及付費 App 的佣金率將由目前的 30% 改為 26%。 Google 這邊應該還沒看到新消息...]]></description>
										<content:encoded><![CDATA[<p>掃到這個「<a href="https://www.macrumors.com/2026/10/29/app-store-fees-taiwan/">Apple Lowers App Store Fees in Taiwan Starting October 31</a>」提到 <a href="https://en.wikipedia.org/wiki/Apple_Inc.">Apple</a> 內購的抽成調低，應該是「<a href="https://developer.apple.com/tw/support/adjustments-to-the-taiwan-storefront/">對 App Store 台灣店面的 iOS 及 iPadOS 的調整</a>」這個公告：</p>
<blockquote><p>自 2026 年 10 月 31 日起，適用於 App Store 台灣店面的 iOS 及 iPadOS 佣金率將進行調整。標準 Apple App 內購買及付費 App 的佣金率將由目前的 30% 改為 26%。</p></blockquote>
<p><a href="https://en.wikipedia.org/wiki/Google">Google</a> 這邊應該還沒看到新消息...</p>
]]></content:encoded>
					
					<wfw:commentRss>https://blog.gslin.org/archives/2026/10/30/13307/apple-%e5%85%a7%e8%b3%bc%e6%8a%bd%e6%88%90%e8%aa%bf%e4%bd%8e-%e5%be%9e-30-%e9%99%8d%e5%88%b0-26/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">13307</post-id>	</item>
		<item>
		<title>Artificial Analysis 更新 Intelligence Index 指標了</title>
		<link>https://blog.gslin.org/archives/2026/10/30/13305/artificial-analysis-%e6%9b%b4%e6%96%b0-intelligence-index-%e6%8c%87%e6%a8%99%e4%ba%86/</link>
					<comments>https://blog.gslin.org/archives/2026/10/30/13305/artificial-analysis-%e6%9b%b4%e6%96%b0-intelligence-index-%e6%8c%87%e6%a8%99%e4%ba%86/#respond</comments>
		
		<dc:creator><![CDATA[Gea-Suan Lin]]></dc:creator>
		<pubDate>Thu, 29 Oct 2026 20:09:08 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[Murmuring]]></category>
		<category><![CDATA[Network]]></category>
		<category><![CDATA[analysis]]></category>
		<category><![CDATA[artificial]]></category>
		<category><![CDATA[index]]></category>
		<category><![CDATA[intelligence]]></category>
		<category><![CDATA[rank]]></category>
		<category><![CDATA[ranking]]></category>
		<category><![CDATA[score]]></category>
		<guid isPermaLink="false">https://blog.gslin.org/?p=13305</guid>

					<description><![CDATA[Artificial Analysis 在 10/27 更新了 Intelligence Index，這次版號從 v4.3 升到 v5：「Announcing Artificial Analysis Intelligence Index v5」。 目前比較麻煩的是，分數沒有銜接，加上幾個常拿來比較的模型好像沒有全部重測，常拿來分析的錨點就消失了，像是 27B 的 Qwen3.8-27B (xhigh) 有新版的 20 分，舊版可以從 Internet Archive 上看到是 34 分：https://web.archive.org/web/20261021173138/https://artificialanalysis.ai/models/qwen3-8-27b。 但 180B 的 Qwen3.8-Flash-Next 在新版就沒有資料了... 舊版是 40 分：https://web.archive.org/web/20261021015347/https://artificialanalysis.ai/models/qwen3-8-flash-next。 理論上應該會花時間重跑？]]></description>
										<content:encoded><![CDATA[<p><a href="https://artificialanalysis.ai/">Artificial Analysis</a> 在 10/27 更新了 Intelligence Index，這次版號從 v4.3 升到 v5：「<a href="https://artificialanalysis.ai/articles/artificial-analysis-intelligence-index-v5">Announcing Artificial Analysis Intelligence Index v5</a>」。</p>
<p>目前比較麻煩的是，分數沒有銜接，加上幾個常拿來比較的模型好像沒有全部重測，常拿來分析的錨點就消失了，像是 27B 的 <a href="https://artificialanalysis.ai/models/qwen3-8-27b">Qwen3.8-27B (xhigh)</a> 有新版的 20 分，舊版可以從 <a href="https://en.wikipedia.org/wiki/Internet_Archive">Internet Archive</a> 上看到是 34 分：<a href="https://web.archive.org/web/20261021173138/https://artificialanalysis.ai/models/qwen3-8-27b">https://web.archive.org/web/20261021173138/https://artificialanalysis.ai/models/qwen3-8-27b</a>。</p>
<p>但 180B 的 <a href="https://artificialanalysis.ai/models/qwen3-8-flash-next">Qwen3.8-Flash-Next</a> 在新版就沒有資料了... 舊版是 40 分：<a href="https://web.archive.org/web/20261021015347/https://artificialanalysis.ai/models/qwen3-8-flash-next">https://web.archive.org/web/20261021015347/https://artificialanalysis.ai/models/qwen3-8-flash-next</a>。</p>
<p>理論上應該會花時間重跑？</p>
]]></content:encoded>
					
					<wfw:commentRss>https://blog.gslin.org/archives/2026/10/30/13305/artificial-analysis-%e6%9b%b4%e6%96%b0-intelligence-index-%e6%8c%87%e6%a8%99%e4%ba%86/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">13305</post-id>	</item>
		<item>
		<title>Google 放出 Gemini 4 Carbon</title>
		<link>https://blog.gslin.org/archives/2026/10/29/13304/google-%e6%94%be%e5%87%ba-gemini-4-carbon/</link>
					<comments>https://blog.gslin.org/archives/2026/10/29/13304/google-%e6%94%be%e5%87%ba-gemini-4-carbon/#respond</comments>
		
		<dc:creator><![CDATA[Gea-Suan Lin]]></dc:creator>
		<pubDate>Wed, 28 Oct 2026 19:21:10 +0000</pubDate>
				<category><![CDATA[API]]></category>
		<category><![CDATA[Computer]]></category>
		<category><![CDATA[Murmuring]]></category>
		<category><![CDATA[Network]]></category>
		<category><![CDATA[Service]]></category>
		<category><![CDATA[4]]></category>
		<category><![CDATA[ai]]></category>
		<category><![CDATA[carbon]]></category>
		<category><![CDATA[gemini]]></category>
		<category><![CDATA[google]]></category>
		<category><![CDATA[language]]></category>
		<category><![CDATA[large]]></category>
		<category><![CDATA[llm]]></category>
		<category><![CDATA[model]]></category>
		<guid isPermaLink="false">https://blog.gslin.org/?p=13304</guid>

					<description><![CDATA[Google 丟出目前最強的模型 Gemini 4 Carbon：「Gemini 4 Carbon: our next frontier model」，用到碳了... 在現在 Artifical Analysis 上的跑分直接攻頂： 這次即使考慮到誤差值，可以看到跟 OpenAI 以及 Anthropic 的旗艦產品線都站上領先群了，相比月初時推出的 Gemini 4 Argon 只是稍微跟上的感覺 (參考「Gemini 4」)，現在看起來是放大招了... API 報價是 $4/$20/$0.2，跟 Claude 的 Opus 5.5 相同，但 OpenAI 的 GPT-6.1-Sol 是剛好一半 $2/$10/$0.1。 實際看 cost per task 相關的話，就沒有太吸引人了，目前還是 OpenAI 家的模型明顯比較強： 但算是端出能打的東西了... 話說隔壁棚正在忙 IPO，有打算在這個時間點再端出其他東西來打嗎？]]></description>
										<content:encoded><![CDATA[<p><a href="https://en.wikipedia.org/wiki/Google">Google</a> 丟出目前最強的模型 Gemini 4 Carbon：「<a href="https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-carbon/">Gemini 4 Carbon: our next frontier model</a>」，用到碳了...</p>
<p>在現在 <a href="https://artificialanalysis.ai/">Artifical Analysis</a> 上的跑分直接攻頂：</p>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1793214499-d7ee72d1.webp" /><img decoding="async" src="https://i.gslin.com/s/1793214499-d7ee72d1.png" alt="" /></picture>
<p>這次即使考慮到誤差值，可以看到跟 <a href="https://en.wikipedia.org/wiki/OpenAI">OpenAI</a> 以及 <a href="https://en.wikipedia.org/wiki/Anthropic">Anthropic</a> 的旗艦產品線都站上領先群了，相比月初時推出的 Gemini 4 Argon 只是稍微跟上的感覺 (參考「<a href="https://blog.gslin.org/archives/2026/10/01/13236/gemini-4/">Gemini 4</a>」)，現在看起來是放大招了...</p>
<p>API 報價是 $4/$20/$0.2，跟 Claude 的 Opus 5.5 相同，但 OpenAI 的 GPT-6.1-Sol 是剛好一半 $2/$10/$0.1。</p>
<p>實際看 cost per task 相關的話，就沒有太吸引人了，目前還是 OpenAI 家的模型明顯比較強：</p>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1793214557-aa4edda6.webp" /><img decoding="async" src="https://i.gslin.com/s/1793214557-aa4edda6.png" alt="" /></picture>
<p>但算是端出能打的東西了... 話說隔壁棚正在忙 <a href="https://en.wikipedia.org/wiki/Initial_public_offering">IPO</a>，有打算在這個時間點再端出其他東西來打嗎？</p>
]]></content:encoded>
					
					<wfw:commentRss>https://blog.gslin.org/archives/2026/10/29/13304/google-%e6%94%be%e5%87%ba-gemini-4-carbon/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">13304</post-id>	</item>
		<item>
		<title>OpenAI 放出 GPT-6.1 Terra</title>
		<link>https://blog.gslin.org/archives/2026/10/27/13303/openai-%e6%94%be%e5%87%ba-gpt-6-1-terra/</link>
					<comments>https://blog.gslin.org/archives/2026/10/27/13303/openai-%e6%94%be%e5%87%ba-gpt-6-1-terra/#comments</comments>
		
		<dc:creator><![CDATA[Gea-Suan Lin]]></dc:creator>
		<pubDate>Mon, 26 Oct 2026 23:04:39 +0000</pubDate>
				<category><![CDATA[API]]></category>
		<category><![CDATA[Computer]]></category>
		<category><![CDATA[Murmuring]]></category>
		<category><![CDATA[Network]]></category>
		<category><![CDATA[Service]]></category>
		<category><![CDATA[ai]]></category>
		<category><![CDATA[cost]]></category>
		<category><![CDATA[gpt-6.1]]></category>
		<category><![CDATA[language]]></category>
		<category><![CDATA[large]]></category>
		<category><![CDATA[llm]]></category>
		<category><![CDATA[model]]></category>
		<category><![CDATA[openai]]></category>
		<category><![CDATA[performance]]></category>
		<category><![CDATA[pricing]]></category>
		<category><![CDATA[terra]]></category>
		<guid isPermaLink="false">https://blog.gslin.org/?p=13303</guid>

					<description><![CDATA[隔壁 Anthropic 在 IPO，這邊 OpenAI 先繼續放 model：「Introducing GPT-6.1 Terra (via)」。 剛好上次在「OpenAI 也推出了 GPT-6 Sol 與 Luna：也跟著降價了」有提到沒有 Terra 的問題，這次直接在 GPT-6.1 上推出 Terra 了。 看到圖的時候才突然注意到，剛好把 model 代表的星體拿來當 icon 用 (太陽/地球/月亮)： 文章裡面所有的圖表都是以 cost 為主，就可以看出來這個 model 是主打價錢了，所以主要就是交叉分析能力競爭者在同一個區間的 model 的價錢。 拿 Artifical Analysis 上的資料當基準，max 是 48 分，xhigh 是 45 分，1M 的 input 與 output 價錢分別是 $1 與 $5，然後 cache input &#8230; <a href="https://blog.gslin.org/archives/2026/10/27/13303/openai-%e6%94%be%e5%87%ba-gpt-6-1-terra/" class="more-link">Continue reading<span class="screen-reader-text"> "OpenAI 放出 GPT-6.1 Terra"</span></a>]]></description>
										<content:encoded><![CDATA[<p>隔壁 <a href="https://en.wikipedia.org/wiki/Anthropic">Anthropic</a> 在 <a href="https://en.wikipedia.org/wiki/Initial_public_offering">IPO</a>，這邊 <a href="https://en.wikipedia.org/wiki/OpenAI">OpenAI</a> 先繼續放 model：「<a href="https://openai.com/index/introducing-gpt-6-1-terra/">Introducing GPT-6.1 Terra</a> (<a href="https://news.ycombinator.com/item?id=50248124">via</a>)」。</p>
<p>剛好上次在「<a href="https://blog.gslin.org/archives/2026/09/23/13222/openai-%E4%B9%9F%E6%8E%A8%E5%87%BA%E4%BA%86-gpt-6-sol-%E8%88%87-luna%EF%BC%9A%E4%B9%9F%E8%B7%9F%E8%91%97%E9%99%8D%E5%83%B9%E4%BA%86/">OpenAI 也推出了 GPT-6 Sol 與 Luna：也跟著降價了</a>」有提到沒有 Terra 的問題，這次直接在 GPT-6.1 上推出 Terra 了。</p>
<p>看到圖的時候才突然注意到，剛好把 model 代表的星體拿來當 icon 用 (太陽/地球/月亮)：</p>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1793054439-74e48a37.webp" /><img decoding="async" src="https://i.gslin.com/s/1793054439-74e48a37.png" alt="" /></picture>
<p>文章裡面所有的圖表都是以 cost 為主，就可以看出來這個 model 是主打價錢了，所以主要就是交叉分析能力競爭者在同一個區間的 model 的價錢。</p>
<p>拿 <a href="https://artificialanalysis.ai/">Artifical Analysis</a> 上的資料當基準，max 是 48 分，xhigh 是 45 分，1M 的 input 與 output 價錢分別是 $1 與 $5，然後 cache input 是 $0.05 (都是美金)。</p>
<p>先看主要對手 Anthropic 的 model，<a href="https://en.wikipedia.org/wiki/Claude_(AI)">Claude</a> 這邊可以看到大約是 Sonnet 5.5 與 Sonnet 5 中間，不過 Sonnet 這邊價錢貴了一倍，是 $2/$10 與 $0.1：</p>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1793055016-2965187b.webp" /><img decoding="async" src="https://i.gslin.com/s/1793055016-2965187b.png" alt="" /></picture>
<p>但如果拿 Haiku 5.5 來比的話是明顯有贏一些，不過 Haiku 5.5 這邊是誇張低的 $0.1/$0.5 與 $0.01：</p>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1793055187-f7fec59f.webp" /><img decoding="async" src="https://i.gslin.com/s/1793055187-f7fec59f.png" alt="" /></picture>
<p>跟 Grok 4.7 差不多，但 Grok 4.7 這邊的 input 貴不少 (output 算是同個區間)，是 $2/$6 與 $0.5：</p>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1793055129-a1724c18.webp" /><img decoding="async" src="https://i.gslin.com/s/1793055129-a1724c18.png" alt="" /></picture>
<p>分析起來算是補中階產品線的概念，但如果有價錢上的條件需要考慮的話，可以先看看 Haiku 5.5 的能力夠不夠解？</p>
]]></content:encoded>
					
					<wfw:commentRss>https://blog.gslin.org/archives/2026/10/27/13303/openai-%e6%94%be%e5%87%ba-gpt-6-1-terra/feed/</wfw:commentRss>
			<slash:comments>1</slash:comments>
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">13303</post-id>	</item>
		<item>
		<title>Anthropic 送出 Form S-1</title>
		<link>https://blog.gslin.org/archives/2026/10/27/13302/anthropic-%e9%80%81%e5%87%ba-form-s-1/</link>
					<comments>https://blog.gslin.org/archives/2026/10/27/13302/anthropic-%e9%80%81%e5%87%ba-form-s-1/#respond</comments>
		
		<dc:creator><![CDATA[Gea-Suan Lin]]></dc:creator>
		<pubDate>Mon, 26 Oct 2026 19:27:29 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[Financial]]></category>
		<category><![CDATA[Murmuring]]></category>
		<category><![CDATA[ai]]></category>
		<category><![CDATA[anthropic]]></category>
		<category><![CDATA[form]]></category>
		<category><![CDATA[initial]]></category>
		<category><![CDATA[ipo]]></category>
		<category><![CDATA[language]]></category>
		<category><![CDATA[large]]></category>
		<category><![CDATA[llm]]></category>
		<category><![CDATA[model]]></category>
		<category><![CDATA[offer]]></category>
		<category><![CDATA[public]]></category>
		<category><![CDATA[s-1]]></category>
		<guid isPermaLink="false">https://blog.gslin.org/?p=13302</guid>

					<description><![CDATA[SEC 上面出現 Anthropic 的 Form S-1 了：「anthropicpbc-sx1.htm (via)」，早 OpenAI 一步，而且應該會是整個市場都超級關注的消息？ 最後一輪 Series H 的估值是 US$965B (當時他們自己發的新聞稿：「Anthropic raises $65B in Series H funding at $965B post-money valuation」)，然後外部報導預期現在是 US$1.5T～US$2T？ 接下來為了避免麻煩，在 quiet period 中可能不會發新的模型，雖然應該是允許？]]></description>
										<content:encoded><![CDATA[<p><a href="https://en.wikipedia.org/wiki/United_States_Securities_and_Exchange_Commission">SEC</a> 上面出現 <a href="https://en.wikipedia.org/wiki/Anthropic">Anthropic</a> 的 <a href="https://en.wikipedia.org/wiki/Form_S-1">Form S-1</a> 了：「<a href="https://www.sec.gov/Archives/edgar/data/2130357/000162828026067168/anthropicpbc-sx1.htm">anthropicpbc-sx1.htm</a> (<a href="https://news.ycombinator.com/item?id=50242939">via</a>)」，早 <a href="https://en.wikipedia.org/wiki/OpenAI">OpenAI</a> 一步，而且應該會是整個市場都超級關注的消息？</p>
<p>最後一輪 Series H 的估值是 US$965B (當時他們自己發的新聞稿：「<a href="https://www.anthropic.com/news/series-h">Anthropic raises $65B in Series H funding at $965B post-money valuation</a>」)，然後外部報導預期現在是 US$1.5T～US$2T？</p>
<p>接下來為了避免麻煩，在 <a href="https://en.wikipedia.org/wiki/Quiet_period">quiet period</a> 中可能不會發新的模型，雖然應該是允許？</p>
]]></content:encoded>
					
					<wfw:commentRss>https://blog.gslin.org/archives/2026/10/27/13302/anthropic-%e9%80%81%e5%87%ba-form-s-1/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">13302</post-id>	</item>
		<item>
		<title>Amazon 的人說他們在 10/17 就有看到這次 PHP 的攻擊了</title>
		<link>https://blog.gslin.org/archives/2026/10/23/13301/amazon-%e7%9a%84%e4%ba%ba%e8%aa%aa%e4%bb%96%e5%80%91%e5%9c%a8-10-17-%e5%b0%b1%e6%9c%89%e7%9c%8b%e5%88%b0%e9%80%99%e6%ac%a1-php-%e7%9a%84%e6%94%bb%e6%93%8a%e4%ba%86/</link>
					<comments>https://blog.gslin.org/archives/2026/10/23/13301/amazon-%e7%9a%84%e4%ba%ba%e8%aa%aa%e4%bb%96%e5%80%91%e5%9c%a8-10-17-%e5%b0%b1%e6%9c%89%e7%9c%8b%e5%88%b0%e9%80%99%e6%ac%a1-php-%e7%9a%84%e6%94%bb%e6%93%8a%e4%ba%86/#respond</comments>
		
		<dc:creator><![CDATA[Gea-Suan Lin]]></dc:creator>
		<pubDate>Fri, 23 Oct 2026 01:31:12 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[Murmuring]]></category>
		<category><![CDATA[Network]]></category>
		<category><![CDATA[Programming]]></category>
		<category><![CDATA[Security]]></category>
		<category><![CDATA[WWW]]></category>
		<category><![CDATA[ace]]></category>
		<category><![CDATA[advisory]]></category>
		<category><![CDATA[amazon]]></category>
		<category><![CDATA[arbitrary]]></category>
		<category><![CDATA[code]]></category>
		<category><![CDATA[execution]]></category>
		<category><![CDATA[exploit]]></category>
		<category><![CDATA[intelligence]]></category>
		<category><![CDATA[internet]]></category>
		<category><![CDATA[network]]></category>
		<category><![CDATA[php]]></category>
		<category><![CDATA[php2shell]]></category>
		<category><![CDATA[public]]></category>
		<category><![CDATA[rce]]></category>
		<category><![CDATA[remote]]></category>
		<category><![CDATA[security]]></category>
		<category><![CDATA[threat]]></category>
		<category><![CDATA[vulnerability]]></category>
		<guid isPermaLink="false">https://blog.gslin.org/?p=13301</guid>

					<description><![CDATA[這次 PHP 的事情的前情提要： PHP 的安全性漏洞，預告今天晚上十點 (2026/10/21 14:00 UTC) 更新 PHP 的兩包 RCE PHP 這兩包 RCE 的一些其他事情... 在「Amazon Threat Intelligence identifies PHP2Shell exploitation prior to public disclosure in MadPot (via)」這邊 Amazon 的人提到他們在更早的 10/17 就看到攻擊了： Amazon Threat Intelligence identified a PHP2Shell exploitation attempt dating to Oct. 17, 2026, in MadPot telemetry, four days before public disclosure of &#8230; <a href="https://blog.gslin.org/archives/2026/10/23/13301/amazon-%e7%9a%84%e4%ba%ba%e8%aa%aa%e4%bb%96%e5%80%91%e5%9c%a8-10-17-%e5%b0%b1%e6%9c%89%e7%9c%8b%e5%88%b0%e9%80%99%e6%ac%a1-php-%e7%9a%84%e6%94%bb%e6%93%8a%e4%ba%86/" class="more-link">Continue reading<span class="screen-reader-text"> "Amazon 的人說他們在 10/17 就有看到這次 PHP 的攻擊了"</span></a>]]></description>
										<content:encoded><![CDATA[<p>這次 <a href="https://en.wikipedia.org/wiki/PHP">PHP</a> 的事情的前情提要：</p>
<ul>
<li><a href="https://blog.gslin.org/archives/2026/10/21/13288/php-%e7%9a%84%e5%ae%89%e5%85%a8%e6%80%a7%e6%bc%8f%e6%b4%9e%ef%bc%8c%e9%a0%90%e5%91%8a%e4%bb%8a%e5%a4%a9%e6%99%9a%e4%b8%8a%e5%8d%81%e9%bb%9e-2026-10-21-1400-utc-%e6%9b%b4%e6%96%b0/">PHP 的安全性漏洞，預告今天晚上十點 (2026/10/21 14:00 UTC) 更新</a></li>
<li><a href="https://blog.gslin.org/archives/2026/10/21/13293/php-%e7%9a%84%e5%85%a9%e5%8c%85-rce/">PHP 的兩包 RCE</a></li>
<li><a href="https://blog.gslin.org/archives/2026/10/22/13294/php-%e9%80%99%e5%85%a9%e5%8c%85-rce-%e7%9a%84%e4%b8%80%e4%ba%9b%e5%85%b6%e4%bb%96%e4%ba%8b%e6%83%85/">PHP 這兩包 RCE 的一些其他事情...</a></li>
</ul>
<p>在「<a href="https://aws.amazon.com/blogs/security/amazon-threat-intelligence-identifies-php2shell-exploitation-prior-to-public-disclosure-in-madpot/">Amazon Threat Intelligence identifies PHP2Shell exploitation prior to public disclosure in MadPot</a> (<a href="https://news.ycombinator.com/item?id=50194070">via</a>)」這邊 <a href="https://en.wikipedia.org/wiki/Amazon_(company)">Amazon</a> 的人提到他們在更早的 10/17 就看到攻擊了：</p>
<blockquote><p>Amazon Threat Intelligence identified a PHP2Shell exploitation attempt dating to Oct. 17, 2026, in MadPot telemetry, four days before public disclosure of CVE-2026-109618 and CVE-2026-109619. The exploit attempt originated from an IP address associated with a commercial anonymization network. While the vulnerability was under embargo, the targeting of a honeypot from an anonymized IP address suggests the activity was conducted by a threat actor, though it remains unclear how the actor acquired exploit information prior to disclosure.</p></blockquote>
<p>直接有給出 IP：</p>
<blockquote><p>103.216.220.92 10/17/2026</p></blockquote>
<p>對應的資訊：</p>
<pre>route:          103.216.220.0/24
origin:         AS136557
descr:          Host Universal Pty Ltd
                Host Universal Pty Ltd
                c/o Brentnalls SA
                255 Port Road, Hindmarsh SA 5007, Australia
mnt-by:         MAINT-HOST-AU
last-modified:  2020-02-03T00:47:52Z
source:         APNIC</pre>
]]></content:encoded>
					
					<wfw:commentRss>https://blog.gslin.org/archives/2026/10/23/13301/amazon-%e7%9a%84%e4%ba%ba%e8%aa%aa%e4%bb%96%e5%80%91%e5%9c%a8-10-17-%e5%b0%b1%e6%9c%89%e7%9c%8b%e5%88%b0%e9%80%99%e6%ac%a1-php-%e7%9a%84%e6%94%bb%e6%93%8a%e4%ba%86/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">13301</post-id>	</item>
		<item>
		<title>新墨西哥州對於 Meta (當時還是 Facebook) 的 Cambridge Analytica 醜聞判決 250 億美金的處罰</title>
		<link>https://blog.gslin.org/archives/2026/10/23/13300/%e6%96%b0%e5%a2%a8%e8%a5%bf%e5%93%a5%e5%b7%9e%e5%b0%8d%e6%96%bc-meta-%e7%95%b6%e6%99%82%e9%82%84%e6%98%af-facebook-%e7%9a%84-cambridge-analytica-%e9%86%9c%e8%81%9e%e5%88%a4%e6%b1%ba-250-%e5%84%84/</link>
					<comments>https://blog.gslin.org/archives/2026/10/23/13300/%e6%96%b0%e5%a2%a8%e8%a5%bf%e5%93%a5%e5%b7%9e%e5%b0%8d%e6%96%bc-meta-%e7%95%b6%e6%99%82%e9%82%84%e6%98%af-facebook-%e7%9a%84-cambridge-analytica-%e9%86%9c%e8%81%9e%e5%88%a4%e6%b1%ba-250-%e5%84%84/#respond</comments>
		
		<dc:creator><![CDATA[Gea-Suan Lin]]></dc:creator>
		<pubDate>Fri, 23 Oct 2026 01:21:18 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[Murmuring]]></category>
		<category><![CDATA[Network]]></category>
		<category><![CDATA[Privacy]]></category>
		<category><![CDATA[analytica]]></category>
		<category><![CDATA[breach]]></category>
		<category><![CDATA[cambridge]]></category>
		<category><![CDATA[data]]></category>
		<category><![CDATA[facebook]]></category>
		<category><![CDATA[law]]></category>
		<category><![CDATA[media]]></category>
		<category><![CDATA[meta]]></category>
		<category><![CDATA[mexico]]></category>
		<category><![CDATA[network]]></category>
		<category><![CDATA[new]]></category>
		<category><![CDATA[privacy]]></category>
		<category><![CDATA[social]]></category>
		<guid isPermaLink="false">https://blog.gslin.org/?p=13300</guid>

					<description><![CDATA[沒想到 Facebook–Cambridge Analytica data scandal 的後續判決還在進行？看到「Meta ordered to pay $25 billion penalty in New Mexico Cambridge Analytica case (via)」這邊，單一州的處罰就 US$25B... 看起來是新墨西哥州沒有參與其他州的和解，而是獨立開了戰線： Meta previously resolved various Cambridge Analytica-derived data privacy lawsuits across the nation as part of an overarching August settlement of nearly $17 billion with a coalition of state attorneys general in a separate federal &#8230; <a href="https://blog.gslin.org/archives/2026/10/23/13300/%e6%96%b0%e5%a2%a8%e8%a5%bf%e5%93%a5%e5%b7%9e%e5%b0%8d%e6%96%bc-meta-%e7%95%b6%e6%99%82%e9%82%84%e6%98%af-facebook-%e7%9a%84-cambridge-analytica-%e9%86%9c%e8%81%9e%e5%88%a4%e6%b1%ba-250-%e5%84%84/" class="more-link">Continue reading<span class="screen-reader-text"> "新墨西哥州對於 Meta (當時還是 Facebook) 的 Cambridge Analytica 醜聞判決 250 億美金的處罰"</span></a>]]></description>
										<content:encoded><![CDATA[<p>沒想到 <a href="https://en.wikipedia.org/wiki/Facebook%E2%80%93Cambridge_Analytica_data_scandal">Facebook–Cambridge Analytica data scandal</a> 的後續判決還在進行？看到「<a href="https://www.cnbc.com/2026/10/21/meta-new-mexico-cambridge-analytica-penalty.html">Meta ordered to pay $25 billion penalty in New Mexico Cambridge Analytica case</a> (<a href="https://news.ycombinator.com/item?id=50184820">via</a>)」這邊，單一州的處罰就 US$25B...</p>
<p>看起來是新墨西哥州沒有參與其他州的和解，而是獨立開了戰線：</p>
<blockquote><p>Meta previously resolved various Cambridge Analytica-derived data privacy lawsuits across the nation as part of an overarching August settlement of nearly $17 billion with a coalition of state attorneys general in a separate federal case related to child safety and mental health. But because New Mexico was not part of the settlement, the state’s data privacy case that arose from Meta’s Cambridge Analytica scandal proceeded to trial in September.</p></blockquote>
<p>目前還沒到最終判決，看起來還會繼續打... 沒注意到原來還在打。</p>
]]></content:encoded>
					
					<wfw:commentRss>https://blog.gslin.org/archives/2026/10/23/13300/%e6%96%b0%e5%a2%a8%e8%a5%bf%e5%93%a5%e5%b7%9e%e5%b0%8d%e6%96%bc-meta-%e7%95%b6%e6%99%82%e9%82%84%e6%98%af-facebook-%e7%9a%84-cambridge-analytica-%e9%86%9c%e8%81%9e%e5%88%a4%e6%b1%ba-250-%e5%84%84/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">13300</post-id>	</item>
		<item>
		<title>日本的 PHP 文藝文庫...</title>
		<link>https://blog.gslin.org/archives/2026/10/23/13299/%e6%97%a5%e6%9c%ac%e7%9a%84-php-%e6%96%87%e8%97%9d%e6%96%87%e5%ba%ab/</link>
					<comments>https://blog.gslin.org/archives/2026/10/23/13299/%e6%97%a5%e6%9c%ac%e7%9a%84-php-%e6%96%87%e8%97%9d%e6%96%87%e5%ba%ab/#respond</comments>
		
		<dc:creator><![CDATA[Gea-Suan Lin]]></dc:creator>
		<pubDate>Thu, 22 Oct 2026 17:21:11 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[Murmuring]]></category>
		<category><![CDATA[book]]></category>
		<category><![CDATA[japan]]></category>
		<category><![CDATA[php]]></category>
		<guid isPermaLink="false">https://blog.gslin.org/?p=13299</guid>

					<description><![CDATA[這篇讓我只想貼圖：(https://x.com/php_bungei/status/2112896234197520797)]]></description>
										<content:encoded><![CDATA[<p>這篇讓我只想貼圖：(<a href="https://x.com/php_bungei/status/2112896234197520797">https://x.com/php_bungei/status/2112896234197520797</a>)</p>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1792689579-5260f5a5.webp" /><img decoding="async" src="https://i.gslin.com/s/1792689579-5260f5a5.png" alt="" /></picture>
]]></content:encoded>
					
					<wfw:commentRss>https://blog.gslin.org/archives/2026/10/23/13299/%e6%97%a5%e6%9c%ac%e7%9a%84-php-%e6%96%87%e8%97%9d%e6%96%87%e5%ba%ab/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">13299</post-id>	</item>
	</channel>
</rss>

<!--
Performance optimized by W3 Total Cache. Learn more: https://www.boldgrid.com/w3-total-cache/?utm_source=w3tc&utm_medium=footer_comment&utm_campaign=free_plugin

Object Caching 37/45 objects using APC
Page Caching using APC (Page is feed) 
Minified using APC
Database Caching using APC

Served from: blog.gslin.org @ 2026-10-30 13:42:21 by W3 Total Cache
-->