<?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>Sun, 18 Oct 2026 08:02:28 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	<generator>https://wordpress.org/?v=7.1.3</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>整數乘法的進展</title>
		<link>https://blog.gslin.org/archives/2026/10/18/13280/%e6%95%b4%e6%95%b8%e4%b9%98%e6%b3%95%e7%9a%84%e9%80%b2%e5%b1%95/</link>
					<comments>https://blog.gslin.org/archives/2026/10/18/13280/%e6%95%b4%e6%95%b8%e4%b9%98%e6%b3%95%e7%9a%84%e9%80%b2%e5%b1%95/#respond</comments>
		
		<dc:creator><![CDATA[Gea-Suan Lin]]></dc:creator>
		<pubDate>Sun, 18 Oct 2026 08:02:28 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[Murmuring]]></category>
		<category><![CDATA[Programming]]></category>
		<category><![CDATA[algo]]></category>
		<category><![CDATA[algorithm]]></category>
		<category><![CDATA[integer]]></category>
		<category><![CDATA[multiplication]]></category>
		<category><![CDATA[number]]></category>
		<guid isPermaLink="false">https://blog.gslin.org/?p=13280</guid>

					<description><![CDATA[前陣子 OpenAI 丟出來一波數學論文中，另外一個受到注目的是整數乘法 (Multiplication algorithm) 突破 的猜測：「Integer multiplication below n log n」。 目前沒看到學界有提出錯誤，而且使用 Lean 的證明也已經放出來了：「Integer multiplication in Lean」，看起來應該是頗有希望的... 如果確認的話就是第一個打下 門檻的演算法了，而且也推翻ㄌ了之前的猜測。 另外 community 是有在繼續透過 AI 找出更低的值，不過那邊就比較像是康樂活動了 (?)]]></description>
										<content:encoded><![CDATA[<p>前陣子 <a href="https://en.wikipedia.org/wiki/OpenAI">OpenAI</a> 丟出來一波數學論文中，另外一個受到注目的是整數乘法 (<a href="https://en.wikipedia.org/wiki/Multiplication_algorithm">Multiplication algorithm</a>) 突破 <img decoding="async" src="https://s0.wp.com/latex.php?latex=O%28n%5Clog%7Bn%7D%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002" alt="O(n&#92;log{n})" class="latex" /> 的猜測：「<a href="https://github.com/openai/math/tree/main/preprints/Integer-multiplication-below-n-log-n-September-23-2026">Integer multiplication below n log n</a>」。</p>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1792310386-abc03753.webp" /><img decoding="async" src="https://i.gslin.com/s/1792310386-abc03753.png" alt="" /></picture>
<p>目前沒看到學界有提出錯誤，而且使用 <a href="https://en.wikipedia.org/wiki/Lean_(proof_assistant)">Lean</a> 的證明也已經放出來了：「<a href="https://github.com/platypii/integer-mult-bounds-lean">Integer multiplication in Lean</a>」，看起來應該是頗有希望的... 如果確認的話就是第一個打下 <img decoding="async" src="https://s0.wp.com/latex.php?latex=O%28n%5Clog%7Bn%7D%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002" alt="O(n&#92;log{n})" class="latex" /> 門檻的演算法了，而且也推翻ㄌ了之前的猜測。</p>
<p>另外 community 是有在繼續透過 AI 找出更低的值，不過那邊就比較像是康樂活動了 (?)</p>
]]></content:encoded>
					
					<wfw:commentRss>https://blog.gslin.org/archives/2026/10/18/13280/%e6%95%b4%e6%95%b8%e4%b9%98%e6%b3%95%e7%9a%84%e9%80%b2%e5%b1%95/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">13280</post-id>	</item>
		<item>
		<title>NIST P-curves 的 nothing-up-my-sleeve number</title>
		<link>https://blog.gslin.org/archives/2026/10/18/13279/nist-p-curves-%e7%9a%84-nothing-up-my-sleeve-number/</link>
					<comments>https://blog.gslin.org/archives/2026/10/18/13279/nist-p-curves-%e7%9a%84-nothing-up-my-sleeve-number/#respond</comments>
		
		<dc:creator><![CDATA[Gea-Suan Lin]]></dc:creator>
		<pubDate>Sun, 18 Oct 2026 06:44:38 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[Murmuring]]></category>
		<category><![CDATA[Programming]]></category>
		<category><![CDATA[Security]]></category>
		<category><![CDATA[algo]]></category>
		<category><![CDATA[algorithm]]></category>
		<category><![CDATA[congruential]]></category>
		<category><![CDATA[curve]]></category>
		<category><![CDATA[curves]]></category>
		<category><![CDATA[ec]]></category>
		<category><![CDATA[elliptic]]></category>
		<category><![CDATA[generator]]></category>
		<category><![CDATA[lcg]]></category>
		<category><![CDATA[linear]]></category>
		<category><![CDATA[nist]]></category>
		<category><![CDATA[number]]></category>
		<category><![CDATA[p]]></category>
		<category><![CDATA[p-curves]]></category>
		<category><![CDATA[random]]></category>
		<category><![CDATA[seed]]></category>
		<category><![CDATA[timestamp]]></category>
		<category><![CDATA[unix]]></category>
		<guid isPermaLink="false">https://blog.gslin.org/?p=13279</guid>

					<description><![CDATA[Nothing-up-my-sleeve number (中文維基百科的條目是『「我的袖子裡沒有東西」數』)，指的是密碼學演算法中用到的一些關鍵數字 (像是各種初始的值)，是出自容易被解釋的數字，以降低設計者放後門的疑慮。 有名的反例是 NIST 在 Dual_EC_DRBG 放的後門，這也是為什麼很多人對 NIST 不信任的主要原因。 所以 NIST 後來推出來的 P-curves 系列裡面冒出來的 random seeds 也是被眾多人質疑： The most commonly used parameters of this class are the NIST P-curves for elliptic curve cryptography. The coefficients in these curves are generated by applying SHA-1 to what was thought to be unexplained random seeds, such &#8230; <a href="https://blog.gslin.org/archives/2026/10/18/13279/nist-p-curves-%e7%9a%84-nothing-up-my-sleeve-number/" class="more-link">Continue reading<span class="screen-reader-text"> "NIST P-curves 的 nothing-up-my-sleeve number"</span></a>]]></description>
										<content:encoded><![CDATA[<p><a href="https://en.wikipedia.org/wiki/Nothing-up-my-sleeve_number">Nothing-up-my-sleeve number</a> (中文維基百科的條目是『<a href="https://zh.wikipedia.org/wiki/%E2%80%9C%E6%88%91%E7%9A%84%E8%A2%96%E5%AD%90%E9%87%8C%E6%B2%A1%E6%9C%89%E4%B8%9C%E8%A5%BF%E2%80%9D%E6%95%B0">「我的袖子裡沒有東西」數</a>』)，指的是密碼學演算法中用到的一些關鍵數字 (像是各種初始的值)，是出自容易被解釋的數字，以降低設計者放後門的疑慮。</p>
<p>有名的反例是 <a href="https://en.wikipedia.org/wiki/National_Institute_of_Standards_and_Technology">NIST</a> 在 <a href="https://en.wikipedia.org/wiki/Dual_EC_DRBG">Dual_EC_DRBG</a> 放的後門，這也是為什麼很多人對 NIST 不信任的主要原因。</p>
<p>所以 NIST 後來推出來的 P-curves 系列裡面冒出來的 random seeds 也是被眾多人質疑：</p>
<blockquote><p>The most commonly used parameters of this class are the NIST P-curves for elliptic curve cryptography. The coefficients in these curves are generated by applying SHA-1 to what was thought to be unexplained random seeds, such as:</p>
<ul>
<li>P-224: bd713447 99d5c7fc dc45b59f a3b9ab8f 6a948bc5.</li>
<li>P-256: c49d3608 86e70493 6a6678e1 139d26b7 819f7e90.</li>
<li>P-384: a335926a a319a27a 1d00896a 6773a482 7acdac73.</li>
</ul>
<p>That said, this above method does improve upon just providing a value and claiming that it is "repeatedly randomly generated" until a certain property (e.g. the number of points on a curve) is met, which is the unverifiable explanation provided for the NSA-provided elliptic curves that X9.62 set out to replace using this method. These kinds of explanations make for "trivially manipulatable" curves.</p></blockquote>
<p>這也是為什麼雖然 P-curves 是標準，但社群的人在設計時會更偏好 <a href="https://en.wikipedia.org/wiki/Curve25519">Curve25519</a> 之類的曲線，像是 <a href="https://en.wikipedia.org/wiki/Daniel_J._Bernstein">djb</a> 整理出來的「<a href="https://safecurves.cr.yp.to/">SafeCurves: choosing safe curves for elliptic-curve cryptography</a>」。</p>
<p><a href="https://en.wikipedia.org/wiki/Anthropic">Anthropic</a> 昨天則是發表了一篇「<a href="https://www.anthropic.com/research/ecdsa-curve-origins">Claude reveals ECDSA curve origins</a>」，找到產生出這些 random seeds 的演算法，對於 P-curves 的 random seeds 給出了解釋，用的是 <a href="https://en.wikipedia.org/wiki/Linear_congruential_generator">linear congruential generator</a>：</p>
<blockquote><p>In under half an hour, Claude discovered the origins of the NIST P-192, P-224, P-256, P-384 and P-521 seeds. None of them were the results of any hash algorithm at all, but rather the output of the C library’s lrand48 random-number generator, seeded with a Unix timestamp!</p></blockquote>
<p>裡面比較清楚的是這兩張：</p>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1792304953-eee3d900.webp" /><img decoding="async" src="https://i.gslin.com/s/1792304953-eee3d900.png" alt="" /></picture>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1792305082-4dfa3898.webp" /><img decoding="async" src="https://i.gslin.com/s/1792305082-4dfa3898.png" alt="" /></picture>
<p>因為隨機產生出來的 curve 不一定安全，會套用當時已知的攻擊手法確認是否可以採用，所以可以看到會有 candidate (產生下一個 random seed)。</p>
<p>但還是有發現有些 curve 屬於 good curve (對於已知的攻擊手法有合理的抵抗力) 但卻被跳過去，這邊仍然是未解之迷。</p>
<p>除非 NIST 後續願意放出內部文件 (如果存在的話)，這算是目前對 P-curves 的 random seeds 最好的解釋，加上因為有些人過世了，有些人則是聯絡不上，後續還有多少進展也不曉得：</p>
<blockquote><p>Unfortunately, Jerry died in 2023 and other colleagues at the time were not responsive, leaving open the question of how these seeds were originally derived.</p></blockquote>
<p>另外 <a href="https://en.wikipedia.org/wiki/Claude_(AI)">Claude</a> 思考的過程也蠻有趣的，他自己也注意到這是個大發現：</p>
<blockquote><p>This is astonishing: it solves the 25-year-old mystery. Hmm wait. Let me be skeptical: am I in some sort of simulated/test environment? … The seeds match my memory of actual values … Hmm, is it plausible in reality? As of my knowledge … the bounty was unsolved. … All top bits clear—20 bits, chance 1e-6. So indeed real-world. Wow, it's a real discovery.</p></blockquote>
<blockquote><p>Hmm wait. Let me be careful about the plausibility: is it suspicious that such an obvious thing wasn’t discovered in 25 years? It’s verified by direct computation on my side: 160-bit match from a 32-bit seed + small index: no chance coincidences (10 × 160 bits). It’s real.</p></blockquote>
]]></content:encoded>
					
					<wfw:commentRss>https://blog.gslin.org/archives/2026/10/18/13279/nist-p-curves-%e7%9a%84-nothing-up-my-sleeve-number/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">13279</post-id>	</item>
		<item>
		<title>Google 偷偷地把 Android 手機上的門號自動綁定到 Google 帳號上</title>
		<link>https://blog.gslin.org/archives/2026/10/16/13278/google-%e5%81%b7%e5%81%b7%e5%9c%b0%e6%8a%8a-android-%e6%89%8b%e6%a9%9f%e4%b8%8a%e7%9a%84%e9%96%80%e8%99%9f%e8%87%aa%e5%8b%95%e7%b6%81%e5%ae%9a%e5%88%b0-google-%e5%b8%b3%e8%99%9f%e4%b8%8a/</link>
					<comments>https://blog.gslin.org/archives/2026/10/16/13278/google-%e5%81%b7%e5%81%b7%e5%9c%b0%e6%8a%8a-android-%e6%89%8b%e6%a9%9f%e4%b8%8a%e7%9a%84%e9%96%80%e8%99%9f%e8%87%aa%e5%8b%95%e7%b6%81%e5%ae%9a%e5%88%b0-google-%e5%b8%b3%e8%99%9f%e4%b8%8a/#respond</comments>
		
		<dc:creator><![CDATA[Gea-Suan Lin]]></dc:creator>
		<pubDate>Fri, 16 Oct 2026 09:47:05 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[Murmuring]]></category>
		<category><![CDATA[Network]]></category>
		<category><![CDATA[Privacy]]></category>
		<category><![CDATA[Software]]></category>
		<category><![CDATA[Telephone]]></category>
		<category><![CDATA[android]]></category>
		<category><![CDATA[device]]></category>
		<category><![CDATA[google]]></category>
		<category><![CDATA[mobile]]></category>
		<category><![CDATA[phone]]></category>
		<category><![CDATA[privacy]]></category>
		<category><![CDATA[service]]></category>
		<guid isPermaLink="false">https://blog.gslin.org/?p=13278</guid>

					<description><![CDATA[如標題，報導：「PSA: Google is silently linking your phone number across all signed-in accounts (via)」。 關閉的方法很麻煩，第一步是要在所有的 Android 手機上面關，方法是「設定」-&#62;「Google」，然後選擇「所有服務」，在「隱私權與安全性」區塊選擇「驗證電話號碼」，把裡面的「自動驗證電話號碼」關掉。 第二步是到 Google 帳號裡面刪除被連上的，在 https://myaccount.google.com/phone 這邊把電話一個一個刪掉，如果 Android 手機有登入多個帳號的話，記得每個都要掃一輪。]]></description>
										<content:encoded><![CDATA[<p>如標題，報導：「<a href="https://www.androidauthority.com/google-auto-phone-number-verification-android-3723117/">PSA: Google is silently linking your phone number across all signed-in accounts</a> (<a href="https://news.ycombinator.com/item?id=50090349">via</a>)」。</p>
<p>關閉的方法很麻煩，第一步是要在所有的 <a href="https://en.wikipedia.org/wiki/Android_(operating_system)">Android</a> 手機上面關，方法是「設定」-&gt;「Google」，然後選擇「所有服務」，在「隱私權與安全性」區塊選擇「驗證電話號碼」，把裡面的「自動驗證電話號碼」關掉。</p>
<p>第二步是到 <a href="https://en.wikipedia.org/wiki/Google">Google</a> 帳號裡面刪除被連上的，在 <a href="https://myaccount.google.com/phone">https://myaccount.google.com/phone</a> 這邊把電話一個一個刪掉，如果 Android 手機有登入多個帳號的話，記得每個都要掃一輪。</p>
]]></content:encoded>
					
					<wfw:commentRss>https://blog.gslin.org/archives/2026/10/16/13278/google-%e5%81%b7%e5%81%b7%e5%9c%b0%e6%8a%8a-android-%e6%89%8b%e6%a9%9f%e4%b8%8a%e7%9a%84%e9%96%80%e8%99%9f%e8%87%aa%e5%8b%95%e7%b6%81%e5%ae%9a%e5%88%b0-google-%e5%b8%b3%e8%99%9f%e4%b8%8a/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">13278</post-id>	</item>
		<item>
		<title>Meta 又放出 model 了：Muse Spark Open</title>
		<link>https://blog.gslin.org/archives/2026/10/16/13277/meta-%e5%8f%88%e6%94%be%e5%87%ba-model-%e4%ba%86%ef%bc%9amuse-spark-open/</link>
					<comments>https://blog.gslin.org/archives/2026/10/16/13277/meta-%e5%8f%88%e6%94%be%e5%87%ba-model-%e4%ba%86%ef%bc%9amuse-spark-open/#respond</comments>
		
		<dc:creator><![CDATA[Gea-Suan Lin]]></dc:creator>
		<pubDate>Fri, 16 Oct 2026 05:12:08 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[Murmuring]]></category>
		<category><![CDATA[Programming]]></category>
		<category><![CDATA[ai]]></category>
		<category><![CDATA[language]]></category>
		<category><![CDATA[large]]></category>
		<category><![CDATA[llm]]></category>
		<category><![CDATA[meta]]></category>
		<category><![CDATA[model]]></category>
		<category><![CDATA[muse]]></category>
		<category><![CDATA[open]]></category>
		<category><![CDATA[spark]]></category>
		<guid isPermaLink="false">https://blog.gslin.org/?p=13277</guid>

					<description><![CDATA[Meta 放出 Muse Spark Open：「Introducing Muse Spark Open, The Most Capable US Open‑Weight Model to Date」。 816B (42B active) 的 model： Muse Spark Open is a natively multimodal model with 816B total parameters (42B active) and a 1M-token context window. 官方列出來的 benchmark 看起來不差，主要是要跟中國的幾個 model 比，Qwen3.8-2.4T-A95B 與 Kimi-K3 算是 2T 級別的，這邊 GLM-5.3 算是同個量級的 (Muse Spark Open &#8230; <a href="https://blog.gslin.org/archives/2026/10/16/13277/meta-%e5%8f%88%e6%94%be%e5%87%ba-model-%e4%ba%86%ef%bc%9amuse-spark-open/" class="more-link">Continue reading<span class="screen-reader-text"> "Meta 又放出 model 了：Muse Spark Open"</span></a>]]></description>
										<content:encoded><![CDATA[<p><a href="https://en.wikipedia.org/wiki/Meta_Platforms">Meta</a> 放出 Muse Spark Open：「<a href="https://research.meta.ai/blog/muse-spark-open">Introducing Muse Spark Open, The Most Capable US Open‑Weight Model to Date</a>」。</p>
<p>816B (42B active) 的 model：</p>
<blockquote><p>Muse Spark Open is a natively multimodal model with 816B total parameters (42B active) and a 1M-token context window.</p></blockquote>
<p>官方列出來的 benchmark 看起來不差，主要是要跟中國的幾個 model 比，<a href="https://huggingface.co/Qwen/Qwen3.8-2.4T-A95B">Qwen3.8-2.4T-A95B</a> 與 <a href="https://huggingface.co/moonshotai/Kimi-K3">Kimi-K3</a> 算是 2T 級別的，這邊 GLM-5.3 算是同個量級的 (Muse Spark Open 稍微大一點點)：</p>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1792125357-9be7b7d8.webp" /><img decoding="async" src="https://i.gslin.com/s/1792125357-9be7b7d8.png" alt="" /></picture>
<p>不過從 <a href="https://artificialanalysis.ai/">Artificial Analysis</a> 這邊看，把另外同個級別的 <a href="https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash">DeepSeek-V4.1-Flash</a> 以及小一個級別的 <a href="https://huggingface.co/zai-org/GLM-5.3-Flash">GLM-5.3-Flash</a> (320B MoE，18B active) 以及 <a href="https://huggingface.co/Qwen/Qwen3.8-Flash-Next">Qwen3.8-Flash-Next</a> (180B MoE，6B active) 也一起拉進來看，就可以看出來還是有些差距：</p>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1792126565-de12805b.webp" /><img decoding="async" src="https://i.gslin.com/s/1792126565-de12805b.png" alt="" /></picture>
<p>可以看到跟同級別的 GLM-5.3 有差距，而 GLM-5.3-Flash 分數略高又比他小，差不多分數的 Qwen3.8-Flash-Next 則是小了很多，只能說這次算是「有參與感」了？</p>
]]></content:encoded>
					
					<wfw:commentRss>https://blog.gslin.org/archives/2026/10/16/13277/meta-%e5%8f%88%e6%94%be%e5%87%ba-model-%e4%ba%86%ef%bc%9amuse-spark-open/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">13277</post-id>	</item>
		<item>
		<title>清大 nthu.tw 的 WHOIS 資訊...</title>
		<link>https://blog.gslin.org/archives/2026/10/15/13273/%e6%b8%85%e5%a4%a7-nthu-tw-%e7%9a%84-whois-%e8%b3%87%e8%a8%8a/</link>
					<comments>https://blog.gslin.org/archives/2026/10/15/13273/%e6%b8%85%e5%a4%a7-nthu-tw-%e7%9a%84-whois-%e8%b3%87%e8%a8%8a/#respond</comments>
		
		<dc:creator><![CDATA[Gea-Suan Lin]]></dc:creator>
		<pubDate>Thu, 15 Oct 2026 08:17:31 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[DNS]]></category>
		<category><![CDATA[Murmuring]]></category>
		<category><![CDATA[Network]]></category>
		<category><![CDATA[dns]]></category>
		<category><![CDATA[nthu]]></category>
		<category><![CDATA[taiwan]]></category>
		<category><![CDATA[tw]]></category>
		<category><![CDATA[whois]]></category>
		<guid isPermaLink="false">https://blog.gslin.org/?p=13273</guid>

					<description><![CDATA[雖然 WHOIS 要退役了，但指令還是用習慣了，在理論上的網遇上看到 idv.tw 的 email 網域還是蠻有趣的？ gslin@GSLINHOME [~] [16:10/W4] whois nthu.tw Domain Name: nthu.tw Domain Status: ok Registrant: 國立清華大學 National Tsing Hua University tcs@kitty.2y.idv.tw TW (Redacted for privacy) Administrative Contact: (Redacted for privacy) Technical Contact: (Redacted for privacy) Record expires on 2036-12-31 16:37:00 (UTC+8) Record created on 2005-10-27 17:02:34 (UTC+8) Domain servers in listed &#8230; <a href="https://blog.gslin.org/archives/2026/10/15/13273/%e6%b8%85%e5%a4%a7-nthu-tw-%e7%9a%84-whois-%e8%b3%87%e8%a8%8a/" class="more-link">Continue reading<span class="screen-reader-text"> "清大 nthu.tw 的 WHOIS 資訊..."</span></a>]]></description>
										<content:encoded><![CDATA[<p>雖然 <a href="https://en.wikipedia.org/wiki/WHOIS">WHOIS</a> 要退役了，但指令還是用習慣了，在理論上的網遇上看到 idv.tw 的 email 網域還是蠻有趣的？</p>
<pre>gslin@GSLINHOME [~] [16:10/W4] whois nthu.tw
Domain Name: nthu.tw
   Domain Status: ok
   Registrant:
      國立清華大學
      National Tsing Hua University
      tcs@kitty.2y.idv.tw
      TW
      (Redacted for privacy)

   Administrative Contact:
      (Redacted for privacy)

   Technical Contact:
      (Redacted for privacy)

   Record expires on 2036-12-31 16:37:00 (UTC+8)
   Record created on 2005-10-27 17:02:34 (UTC+8)

   Domain servers in listed order:
      ns1.nthu.tw     140.114.68.10 2001:288:e001:68::a
      ns2.nthu.tw     125.227.29.233 2001:b030:7021:ff00:0000:0000:0001:0000

Registration Service Provider: TWNIC
Registration Service URL: https://rs.twnic.tw/
Registrar Abuse Contact Email: abuse@twnic.tw</pre>
<p>搜一下對應的 email 可以找到 <a href="http://vpn.csbb.cs.nthu.edu.tw/">http://vpn.csbb.cs.nthu.edu.tw/</a> (HTTP) 這個連結：(以及 <a href="https://archive.is/e1Udz">https://archive.is/e1Udz</a>)</p>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1792052002-08cb6086.webp" /><img decoding="async" src="https://i.gslin.com/s/1792052002-08cb6086.png" alt="" /></picture>
]]></content:encoded>
					
					<wfw:commentRss>https://blog.gslin.org/archives/2026/10/15/13273/%e6%b8%85%e5%a4%a7-nthu-tw-%e7%9a%84-whois-%e8%b3%87%e8%a8%8a/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">13273</post-id>	</item>
		<item>
		<title>用 fnt 來管理字型</title>
		<link>https://blog.gslin.org/archives/2026/10/14/13272/%e7%94%a8-fnt-%e4%be%86%e7%ae%a1%e7%90%86%e5%ad%97%e5%9e%8b/</link>
					<comments>https://blog.gslin.org/archives/2026/10/14/13272/%e7%94%a8-fnt-%e4%be%86%e7%ae%a1%e7%90%86%e5%ad%97%e5%9e%8b/#respond</comments>
		
		<dc:creator><![CDATA[Gea-Suan Lin]]></dc:creator>
		<pubDate>Wed, 14 Oct 2026 12:53:12 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[Linux]]></category>
		<category><![CDATA[Murmuring]]></category>
		<category><![CDATA[OS]]></category>
		<category><![CDATA[Software]]></category>
		<category><![CDATA[debian]]></category>
		<category><![CDATA[fnt]]></category>
		<category><![CDATA[font]]></category>
		<category><![CDATA[linux]]></category>
		<guid isPermaLink="false">https://blog.gslin.org/?p=13272</guid>

					<description><![CDATA[在 Hacker News 上面看到「Iosevka is an open-source, sans-serif and slab-serif, monospace font (typeof.net)」這篇的時候想到的，Linux 下面應該有管理字型的套件，問 AI 然後研究了一下發現有 fnt 可以用，像是這樣： sudo apt install -y fnt; sudo apt clean; sudo fnt update; sudo fnt install google-googlesanscode 用 root 跑會裝到系統，用 user 跑會裝在自己目錄下。 這樣對於沒有被包進 apt repository 的字型來說簡單不少，而且可以放進自己的 wiki 文件裡面，在弄桌機的時候可以直接剪下貼上... 看官網說明好像也支援 macOS，不過還沒測試過...]]></description>
										<content:encoded><![CDATA[<p>在 <a href="https://en.wikipedia.org/wiki/Hacker_News">Hacker News</a> 上面看到「<a href="https://news.ycombinator.com/item?id=50084240">Iosevka is an open-source, sans-serif and slab-serif, monospace font (typeof.net)</a>」這篇的時候想到的，<a href="https://en.wikipedia.org/wiki/Linux">Linux</a> 下面應該有管理字型的套件，問 <a href="https://en.wikipedia.org/wiki/Artificial_intelligence">AI</a> 然後研究了一下發現有 <a href="https://github.com/alexmyczko/fnt">fnt</a> 可以用，像是這樣：</p>
<pre>sudo apt install -y fnt; sudo apt clean; sudo fnt update; sudo fnt install google-googlesanscode</pre>
<p>用 root 跑會裝到系統，用 user 跑會裝在自己目錄下。</p>
<p>這樣對於沒有被包進 apt repository 的字型來說簡單不少，而且可以放進自己的 wiki 文件裡面，在弄桌機的時候可以直接剪下貼上...</p>
<p>看官網說明好像也支援 <a href="https://en.wikipedia.org/wiki/MacOS">macOS</a>，不過還沒測試過...</p>
]]></content:encoded>
					
					<wfw:commentRss>https://blog.gslin.org/archives/2026/10/14/13272/%e7%94%a8-fnt-%e4%be%86%e7%ae%a1%e7%90%86%e5%ad%97%e5%9e%8b/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">13272</post-id>	</item>
		<item>
		<title>加密貨幣的硬體電子錢包被放硬體後門</title>
		<link>https://blog.gslin.org/archives/2026/10/14/13271/%e5%8a%a0%e5%af%86%e8%b2%a8%e5%b9%a3%e7%9a%84%e7%a1%ac%e9%ab%94%e9%9b%bb%e5%ad%90%e9%8c%a2%e5%8c%85%e8%a2%ab%e6%94%be%e7%a1%ac%e9%ab%94%e5%be%8c%e9%96%80/</link>
					<comments>https://blog.gslin.org/archives/2026/10/14/13271/%e5%8a%a0%e5%af%86%e8%b2%a8%e5%b9%a3%e7%9a%84%e7%a1%ac%e9%ab%94%e9%9b%bb%e5%ad%90%e9%8c%a2%e5%8c%85%e8%a2%ab%e6%94%be%e7%a1%ac%e9%ab%94%e5%be%8c%e9%96%80/#respond</comments>
		
		<dc:creator><![CDATA[Gea-Suan Lin]]></dc:creator>
		<pubDate>Wed, 14 Oct 2026 07:47:25 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[Hardware]]></category>
		<category><![CDATA[Murmuring]]></category>
		<category><![CDATA[Network]]></category>
		<category><![CDATA[Security]]></category>
		<category><![CDATA[amazon]]></category>
		<category><![CDATA[auction]]></category>
		<category><![CDATA[crypto]]></category>
		<category><![CDATA[cryptobilis]]></category>
		<category><![CDATA[cryptocurrency]]></category>
		<category><![CDATA[esim]]></category>
		<category><![CDATA[hardware]]></category>
		<category><![CDATA[japan]]></category>
		<category><![CDATA[ledger]]></category>
		<category><![CDATA[money]]></category>
		<category><![CDATA[nano]]></category>
		<category><![CDATA[security]]></category>
		<category><![CDATA[sim]]></category>
		<category><![CDATA[wallet]]></category>
		<category><![CDATA[x]]></category>
		<category><![CDATA[yahoo]]></category>
		<guid isPermaLink="false">https://blog.gslin.org/?p=13271</guid>

					<description><![CDATA[看到「Ledger confirms spy chip implant behind wallet crypto thefts (via)」這篇新聞，講加密貨幣的硬體電子錢包被放入硬體的後門，盜走上億美金... 硬體後門的細節分析在「Ledger Nano X: the spy implant.」這邊比較完整。 被發現有硬體後門的是法國的 Ledger Nano X，在馬來西亞的 CryptoBilis 賣的版本有硬體後門： Ledger has confirmed that some of its devices distributed through Southeast Asian reseller CryptoBilis were compromised with a hardware implant that drained users' cryptocurrency wallets. 從硬體分析的文章裡面有提到這不是第一次了，作者把這些後門分成三代。 第一代算是 prototype，不是很確定來源： A Reddit thread in August &#8230; <a href="https://blog.gslin.org/archives/2026/10/14/13271/%e5%8a%a0%e5%af%86%e8%b2%a8%e5%b9%a3%e7%9a%84%e7%a1%ac%e9%ab%94%e9%9b%bb%e5%ad%90%e9%8c%a2%e5%8c%85%e8%a2%ab%e6%94%be%e7%a1%ac%e9%ab%94%e5%be%8c%e9%96%80/" class="more-link">Continue reading<span class="screen-reader-text"> "加密貨幣的硬體電子錢包被放硬體後門"</span></a>]]></description>
										<content:encoded><![CDATA[<p>看到「<a href="https://www.bleepingcomputer.com/news/security/ledger-confirms-hardware-wallet-spy-implant-behind-crypto-thefts/">Ledger confirms spy chip implant behind wallet crypto thefts</a> (<a href="https://news.ycombinator.com/item?id=50054092">via</a>)」這篇新聞，講加密貨幣的硬體電子錢包被放入硬體的後門，盜走上億美金... 硬體後門的細節分析在「<a href="https://www.tibane.net/research/ledger-nano-x-implant">Ledger Nano X: the spy implant.</a>」這邊比較完整。</p>
<p>被發現有硬體後門的是法國的 <a href="https://shop.ledger.com/products/ledger-nano-x">Ledger Nano X</a>，在馬來西亞的 CryptoBilis 賣的版本有硬體後門：</p>
<blockquote><p>Ledger has confirmed that some of its devices distributed through Southeast Asian reseller CryptoBilis were compromised with a hardware implant that drained users' cryptocurrency wallets.</p></blockquote>
<p>從硬體分析的文章裡面有提到這不是第一次了，作者把這些後門分成三代。</p>
<p>第一代算是 prototype，不是很確定來源：</p>
<blockquote><p>A Reddit thread in August 2025 warns of a “Nano X” being sold to steal crypto. Joe Grand (Grand Idea Studio) acquires the device, tears it down and presents the full reverse-engineering at hardwear.io USA 2026.</p></blockquote>
<p>從照片可以看到除了本來的電子錢包板子外，被多偷放了一張板子：</p>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1791962266-e41de599.webp" /><img decoding="async" src="https://i.gslin.com/s/1791962266-e41de599.png" alt="" /></picture>
<p>方法是透過辨識螢幕上的 recovery words，然後再透過行動網路 (<a href="https://en.wikipedia.org/wiki/ESIM">eSIM</a>) 傳出去：</p>
<blockquote><p>Firmware: stores glyphs for a–z, template-matches the screen traffic against them, saves the recovery words to flash, and transmits them over cellular.</p>
<p>Radio: a Luat Air700E LTE modem, an MFF2 eSIM (a Vodafone NL “DATA ONLY” profile), and an 8 cm hand-wound coil antenna.</p></blockquote>
<p>第二代的是從日本 Y 拍上面買到的：</p>
<blockquote><p>Specimen A · Gen 2 Bought on Yahoo! Auctions, Japan</p></blockquote>
<p>照片上看起來很明顯變得「專業」了，本來手工焊接的線變少了：</p>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1791962778-ed2c78a0.webp" /><img decoding="async" src="https://i.gslin.com/s/1791962778-ed2c78a0.png" alt="" /></picture>
<p>方法還是讀 screen：</p>
<blockquote><p>The flex is shaped to spread over the Ledger’s own board and land on its factory test pads: GND, VBAT and the display SPI lines. Together these give the implant power from the wallet’s battery and a view of everything sent to the screen.</p></blockquote>
<p>第三代是 <a href="https://ja.wikipedia.org/wiki/Amazon.co.jp">Amazon JP</a> 上買到的，中國賣家從馬來西亞發貨：</p>
<blockquote><p>Specimen B · Gen 3 Amazon Japan · China-based seller · shipped from Malaysia</p></blockquote>
<p>照片上更「精緻」了，包括 <a href="https://en.wikipedia.org/wiki/Printed_circuit_board">PCB</a> 板顏色跟 Ledger Nano X 一樣，即使拆開來也不會馬上注意到 (除非你本來就熟)，然後晶片上面的編號也被磨掉了：</p>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1791963231-7d766b6c.webp" /><img decoding="async" src="https://i.gslin.com/s/1791963231-7d766b6c.png" alt="" /></picture>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1791963390-34366f39.webp" /><img decoding="async" src="https://i.gslin.com/s/1791963390-34366f39.png" alt="" /></picture>
<p>作者整理了這三代的「改進過程」：</p>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1791963508-d48f11f5.webp" /><img decoding="async" src="https://i.gslin.com/s/1791963508-d48f11f5.png" alt="" /></picture>
<p>有人估算大約盜走了八千多萬美金：</p>
<blockquote><p>The losses are not confirmed. On-chain investigator Specter puts them above $86 million across Bitcoin, Ethereum and Tron, and tanuki42 ties more than $72 million to eight addresses.</p></blockquote>
<p>另外也有人在新加坡機場買到，而且不是馬來西亞 CryptoBilis 的版本：「<a href="https://www.youtube.com/watch?v=Nf4FEFlgv3Q">Spy implant found in Ledger Flex bought at Singapore airport</a>」。</p>
<p><iframe width="560" height="315" src="https://www.youtube-nocookie.com/embed/Nf4FEFlgv3Q" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe></p>
<p>這個像是集團了，要看看有沒有辦法從 eSIM 反追到人，不然 cryptocurrency 端應該是追找不到連結，這次比較大規模的新聞後續應該會有更多資訊...</p>
]]></content:encoded>
					
					<wfw:commentRss>https://blog.gslin.org/archives/2026/10/14/13271/%e5%8a%a0%e5%af%86%e8%b2%a8%e5%b9%a3%e7%9a%84%e7%a1%ac%e9%ab%94%e9%9b%bb%e5%ad%90%e9%8c%a2%e5%8c%85%e8%a2%ab%e6%94%be%e7%a1%ac%e9%ab%94%e5%be%8c%e9%96%80/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">13271</post-id>	</item>
		<item>
		<title>Meta 也放出第一梯隊模型的消息</title>
		<link>https://blog.gslin.org/archives/2026/10/13/13269/meta-%e4%b9%9f%e6%94%be%e5%87%ba%e7%ac%ac%e4%b8%80%e6%a2%af%e9%9a%8a%e6%a8%a1%e5%9e%8b%e7%9a%84%e6%b6%88%e6%81%af/</link>
					<comments>https://blog.gslin.org/archives/2026/10/13/13269/meta-%e4%b9%9f%e6%94%be%e5%87%ba%e7%ac%ac%e4%b8%80%e6%a2%af%e9%9a%8a%e6%a8%a1%e5%9e%8b%e7%9a%84%e6%b6%88%e6%81%af/#respond</comments>
		
		<dc:creator><![CDATA[Gea-Suan Lin]]></dc:creator>
		<pubDate>Tue, 13 Oct 2026 05:28:51 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[Murmuring]]></category>
		<category><![CDATA[Network]]></category>
		<category><![CDATA[Programming]]></category>
		<category><![CDATA[ai]]></category>
		<category><![CDATA[frontier]]></category>
		<category><![CDATA[language]]></category>
		<category><![CDATA[large]]></category>
		<category><![CDATA[llm]]></category>
		<category><![CDATA[meta]]></category>
		<category><![CDATA[model]]></category>
		<category><![CDATA[muse]]></category>
		<category><![CDATA[wonder]]></category>
		<guid isPermaLink="false">https://blog.gslin.org/?p=13269</guid>

					<description><![CDATA[Meta 也放出第一梯隊模型的消息，Muse Wonder：「Muse Wonder: A Frontier Model For Personal &#38; Professional AI Agents (via)」。 目前還沒放出來讓大家用，主要是依照 Artificial Analysis 上的排名來看的： 不過沒提到價錢，但之前推出來的模型價錢不是很漂亮，所以討論度也不太高？等價錢出來 (&#38; 開放使用) 後再來研究看看效果怎麼樣... 我印象中 Meta 也有 subscription model 可以用，到時候再一起研究。]]></description>
										<content:encoded><![CDATA[<p><a href="https://en.wikipedia.org/wiki/Meta_Platforms">Meta</a> 也放出第一梯隊模型的消息，Muse Wonder：「<a href="https://research.meta.ai/blog/muse-wonder">Muse Wonder: A Frontier Model For Personal &amp; Professional AI Agents</a> (<a href="https://news.ycombinator.com/item?id=50059115">via</a>)」。</p>
<p>目前還沒放出來讓大家用，主要是依照 <a href="https://artificialanalysis.ai/">Artificial Analysis</a> 上的排名來看的：</p>
<picture><source type="image/webp" srcset="https://i.gslin.com/s/1791868906-d3564f08.webp" /><img decoding="async" src="https://i.gslin.com/s/1791868906-d3564f08.png" alt="" /></picture>
<p>不過沒提到價錢，但之前推出來的模型價錢不是很漂亮，所以討論度也不太高？等價錢出來 (&amp; 開放使用) 後再來研究看看效果怎麼樣... 我印象中 Meta 也有 subscription model 可以用，到時候再一起研究。</p>
]]></content:encoded>
					
					<wfw:commentRss>https://blog.gslin.org/archives/2026/10/13/13269/meta-%e4%b9%9f%e6%94%be%e5%87%ba%e7%ac%ac%e4%b8%80%e6%a2%af%e9%9a%8a%e6%a8%a1%e5%9e%8b%e7%9a%84%e6%b6%88%e6%81%af/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">13269</post-id>	</item>
		<item>
		<title>Intel 推出單卡 480GB VRAM 的 AI 卡</title>
		<link>https://blog.gslin.org/archives/2026/10/13/13268/intel-%e6%8e%a8%e5%87%ba%e5%96%ae%e5%8d%a1-480gb-vram-%e7%9a%84-ai-%e5%8d%a1/</link>
					<comments>https://blog.gslin.org/archives/2026/10/13/13268/intel-%e6%8e%a8%e5%87%ba%e5%96%ae%e5%8d%a1-480gb-vram-%e7%9a%84-ai-%e5%8d%a1/#respond</comments>
		
		<dc:creator><![CDATA[Gea-Suan Lin]]></dc:creator>
		<pubDate>Tue, 13 Oct 2026 05:11:04 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[Hardware]]></category>
		<category><![CDATA[Murmuring]]></category>
		<category><![CDATA[480gb]]></category>
		<category><![CDATA[ai]]></category>
		<category><![CDATA[card]]></category>
		<category><![CDATA[center]]></category>
		<category><![CDATA[d270]]></category>
		<category><![CDATA[data]]></category>
		<category><![CDATA[directx]]></category>
		<category><![CDATA[gpu]]></category>
		<category><![CDATA[intel]]></category>
		<category><![CDATA[language]]></category>
		<category><![CDATA[large]]></category>
		<category><![CDATA[llm]]></category>
		<category><![CDATA[memory]]></category>
		<category><![CDATA[model]]></category>
		<category><![CDATA[ram]]></category>
		<category><![CDATA[video]]></category>
		<category><![CDATA[vram]]></category>
		<guid isPermaLink="false">https://blog.gslin.org/?p=13268</guid>

					<description><![CDATA[看到 Intel 推出一張一堆 VRAM 的 AI 卡：「Intel GPU D270 │ Inference-Optimized Data Center GPU (via)」。 官方頁面反而沒什麼技術規格資料，在「Intel D270」這邊反而已經有技術規格可以參考了，不過這邊標的是 160GB VRAM。 但看報導應該是可以選擇大小：「Intel's new GPU packs up to 480GB of memory — but skips 3D graphics」，只是不確定其他的參數 (像是 bandwidth) 會不會因為記憶體大小而改變。 One of the accelerator’s most unusual features is its memory configuration. Intel’s own reference card comes with 160GB of &#8230; <a href="https://blog.gslin.org/archives/2026/10/13/13268/intel-%e6%8e%a8%e5%87%ba%e5%96%ae%e5%8d%a1-480gb-vram-%e7%9a%84-ai-%e5%8d%a1/" class="more-link">Continue reading<span class="screen-reader-text"> "Intel 推出單卡 480GB VRAM 的 AI 卡"</span></a>]]></description>
										<content:encoded><![CDATA[<p>看到 <a href="https://en.wikipedia.org/wiki/Intel">Intel</a> 推出一張一堆 <a href="https://en.wikipedia.org/wiki/Video_random-access_memory">VRAM</a> 的 <a href="https://en.wikipedia.org/wiki/Artificial_intelligence">AI</a> 卡：「<a href="https://www.intel.com/content/www/us/en/products/details/discrete-gpus/data-center-gpu/d-series.html">Intel GPU D270 │ Inference-Optimized Data Center GPU</a> (<a href="https://news.ycombinator.com/item?id=50063365">via</a>)」。</p>
<p>官方頁面反而沒什麼技術規格資料，在「<a href="https://www.techpowerup.com/gpu-specs/d270.c4452">Intel D270</a>」這邊反而已經有技術規格可以參考了，不過這邊標的是 160GB VRAM。</p>
<p>但看報導應該是可以選擇大小：「<a href="https://www.notebookcheck.net/Intel-s-new-GPU-packs-up-to-480GB-of-memory-but-skips-3D-graphics.1422369.0.html">Intel's new GPU packs up to 480GB of memory — but skips 3D graphics</a>」，只是不確定其他的參數 (像是 bandwidth) 會不會因為記憶體大小而改變。</p>
<blockquote><p>One of the accelerator’s most unusual features is its memory configuration. Intel’s own reference card comes with 160GB of LPDDR5X, while its manufacturing partners can develop versions with up to 480GB.</p></blockquote>
<p>不支援 <a href="https://en.wikipedia.org/wiki/DirectX">DirectX</a>，以 AI 為主的卡：</p>
<blockquote><p>The D270 is a graphics card by Intel, launched on October 12th, 2026. Built on the 3 nm process, and based on the Crescent Island graphics processor, the card does not support DirectX. Since D270 does not support DirectX 11 or DirectX 12, it might not be able to run all the latest games.</p></blockquote>
<p><a href="https://en.wikipedia.org/wiki/Nvidia">NVIDIA</a> 的 B100/B200 (<a href="https://en.wikipedia.org/wiki/Hopper_(microarchitecture)">Hopper</a>) 是 192GB，<a href="https://en.wikipedia.org/wiki/AMD_Instinct">AMD Instinct</a> MI350X/MI355X 是 288GB，就知道這張 480GB 有多大了... 但這張卡真的就是 VRAM 很大而已，其他的參數都不怎樣... (相比 server 端的其他卡)</p>
]]></content:encoded>
					
					<wfw:commentRss>https://blog.gslin.org/archives/2026/10/13/13268/intel-%e6%8e%a8%e5%87%ba%e5%96%ae%e5%8d%a1-480gb-vram-%e7%9a%84-ai-%e5%8d%a1/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">13268</post-id>	</item>
		<item>
		<title>OpenAI 的 API 分級制度改版</title>
		<link>https://blog.gslin.org/archives/2026/10/12/13267/openai-%e7%9a%84-api-%e5%88%86%e7%b4%9a%e5%88%b6%e5%ba%a6%e6%94%b9%e7%89%88/</link>
					<comments>https://blog.gslin.org/archives/2026/10/12/13267/openai-%e7%9a%84-api-%e5%88%86%e7%b4%9a%e5%88%b6%e5%ba%a6%e6%94%b9%e7%89%88/#respond</comments>
		
		<dc:creator><![CDATA[Gea-Suan Lin]]></dc:creator>
		<pubDate>Sun, 11 Oct 2026 18:46:56 +0000</pubDate>
				<category><![CDATA[API]]></category>
		<category><![CDATA[Computer]]></category>
		<category><![CDATA[Murmuring]]></category>
		<category><![CDATA[Network]]></category>
		<category><![CDATA[Service]]></category>
		<category><![CDATA[api]]></category>
		<category><![CDATA[build]]></category>
		<category><![CDATA[grow]]></category>
		<category><![CDATA[language]]></category>
		<category><![CDATA[large]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[limit]]></category>
		<category><![CDATA[llm]]></category>
		<category><![CDATA[model]]></category>
		<category><![CDATA[openai]]></category>
		<category><![CDATA[quota]]></category>
		<category><![CDATA[rate]]></category>
		<category><![CDATA[tier]]></category>
		<guid isPermaLink="false">https://blog.gslin.org/?p=13267</guid>

					<description><![CDATA[上禮拜收到 OpenAI 信件提到 API 分級制度改版，本來的五級變成三級，把本來的 Tier 1 與 Tier 3 拉高到與 Tier 2 與 Tier 4 相同的 quota，然後再加上新的名字上去： Here’s how the tiers will change: Tiers 1 and 2 → Build Tiers 3 and 4 → Launch Tier 5 → Grow Organizations currently in Tiers 1 and 3 will receive higher rate limits. Organizations in Tiers &#8230; <a href="https://blog.gslin.org/archives/2026/10/12/13267/openai-%e7%9a%84-api-%e5%88%86%e7%b4%9a%e5%88%b6%e5%ba%a6%e6%94%b9%e7%89%88/" class="more-link">Continue reading<span class="screen-reader-text"> "OpenAI 的 API 分級制度改版"</span></a>]]></description>
										<content:encoded><![CDATA[<p>上禮拜收到 <a href="https://en.wikipedia.org/wiki/OpenAI">OpenAI</a> 信件提到 API 分級制度改版，本來的五級變成三級，把本來的 Tier 1 與 Tier 3 拉高到與 Tier 2 與 Tier 4 相同的 quota，然後再加上新的名字上去：</p>
<blockquote><p>Here’s how the tiers will change:</p>
<ul>
<li>Tiers 1 and 2 → Build</li>
<li>Tiers 3 and 4 → Launch</li>
<li>Tier 5 → Grow</li>
</ul>
</blockquote>
<blockquote><p>Organizations currently in Tiers 1 and 3 will receive higher rate limits. Organizations in Tiers 2, 4, and 5 will keep their existing limits.</p></blockquote>
<p>我記得 Tier 2 比 Tier 1 高不少，這樣對於想要快速跑資料的人應該會方便一些，之前撞 429 撞的亂七八糟的...</p>
]]></content:encoded>
					
					<wfw:commentRss>https://blog.gslin.org/archives/2026/10/12/13267/openai-%e7%9a%84-api-%e5%88%86%e7%b4%9a%e5%88%b6%e5%ba%a6%e6%94%b9%e7%89%88/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">13267</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 39/51 objects using APC
Page Caching using APC (Page is feed) 
Minified using APC
Database Caching using APC

Served from: blog.gslin.org @ 2026-10-18 17:13:37 by W3 Total Cache
-->