{"@context":"https://schema.org","@type":"NewsArticle","generatedAt":"2026-07-23T06:40:50.084Z","headline":"七款前沿模型\"鹈鹕骑自行车\"基准测试未发现针对性优化","description":"一项针对GPT-5.6 Terra等七款模型的对比实验显示，这些模型在\"鹈鹕骑自行车\"这一知名非正式基准测试上并未表现出针对性优化。研究者生成1，008张SVG图像，经评分发现鹈鹕在8种动物中排名第6，自行车在6种交通工具中排名第5，两者组合在48个提示中仅列第42位。","url":"https://www.aioga.com/news/cmrwi2n4z024froj0leere07a/","mainEntityOfPage":"https://www.aioga.com/news/cmrwi2n4z024froj0leere07a/","datePublished":"2026-07-22T19:39:51.177Z","dateModified":"2026-07-22T19:39:51.177Z","inLanguage":"zh-CN","publisher":{"@type":"NewsMediaOrganization","name":"Aioga","url":"https://www.aioga.com"},"citation":["https://dylancastillo.co/posts/pelicanmaxxing.html","https://aihot.virxact.com/items/cmrwi2n4z024froj0leere07a"],"canonicalUrl":"https://www.aioga.com/news/cmrwi2n4z024froj0leere07a/","directAnswer":{"@type":"Answer","text":"Aioga 编辑摘要：一项针对GPT-5.6 Terra等七款模型的对比实验显示，这些模型在\"鹈鹕骑自行车\"这一知名非正式基准测试上并未表现出针对性优化。 Aioga 将其归入「技巧观点」方向，重点关注它对真实使用和行业竞争的影响。","url":"https://www.aioga.com/news/cmrwi2n4z024froj0leere07a/","dateCreated":"2026-07-22T19:39:51.177Z","author":{"@type":"Organization","@id":"https://www.aioga.com/authors/aioga-editorial/#editorial-team","name":"Aioga Editorial Team","url":"https://www.aioga.com/authors/aioga-editorial/"}},"evidence":[{"@type":"CreativeWork","name":"dylancastillo.co source article","url":"https://dylancastillo.co/posts/pelicanmaxxing.html","datePublished":"2026-07-22T19:39:51.177Z","provider":{"@type":"Organization","name":"dylancastillo.co","url":"https://dylancastillo.co/posts/pelicanmaxxing.html"}},{"@type":"CreativeWork","name":"AIHot archive record","url":"https://aihot.virxact.com/items/cmrwi2n4z024froj0leere07a","datePublished":"2026-07-22T19:39:51.177Z","provider":{"@type":"Organization","name":"AIHot","url":"https://aihot.virxact.com/items/cmrwi2n4z024froj0leere07a"}}],"aggregationSource":"Hacker News 热门（buzzing.cc 中文翻译）","originalPublisher":{"name":"dylancastillo.co","url":"https://dylancastillo.co/posts/pelicanmaxxing.html"},"article":{"id":"cmrwi2n4z024froj0leere07a","slug":"cmrwi2n4z024froj0leere07a","url":"https://www.aioga.com/news/cmrwi2n4z024froj0leere07a/","title":"七款前沿模型\"鹈鹕骑自行车\"基准测试未发现针对性优化","title_en":"AI实验室是否在\"鹈鹕化\"？","summary":"一项针对GPT-5.6 Terra等七款模型的对比实验显示，这些模型在\"鹈鹕骑自行车\"这一知名非正式基准测试上并未表现出针对性优化。研究者生成1，008张SVG图像，经评分发现鹈鹕在8种动物中排名第6，自行车在6种交通工具中排名第5，两者组合在48个提示中仅列第42位。","source":"Hacker News 热门（buzzing.cc 中文翻译）","sourceUrl":"https://dylancastillo.co/posts/pelicanmaxxing.html","aiHotUrl":"https://aihot.virxact.com/items/cmrwi2n4z024froj0leere07a","publishedAt":"2026-07-22T19:39:51.177Z","category":"技巧观点","score":63,"selected":false,"articleBody":["Dylan Castillo：https://dylancastillo.co","For the past few years, Simon Willison：https://simonwillison.net/tags/pelican-riding-a-bicycle/ has tested every major LLM release with the same prompt: “Generate an SVG of a pelican riding a bicycle”.","What began as a tongue-in-cheek benchmark has become one of the most famous informal benchmarks in AI. Simon’s pelican-on-a-bicycle results are often among the most upvoted comments on Hacker News threads announcing new releases from AI labs.","The benchmark is now famous enough that there’s plenty：https://news.ycombinator.com/item?id=48994959 of：https://news.ycombinator.com/item?id=48994217 discussion：https://news.ycombinator.com/item?id=48956159 about its usefulness and about whether AI labs might be benchmaxxing 1 ：#fn1 on it. When billions or even trillions of dollars are at stake, and a strong result could help persuade users, wouldn’t it be tempting to pelicanmaxx your model just a bit?","I wanted to find out, so I put together a small experiment. I generated 1,008 SVGs across seven frontier models, scored them with an LLM judge, and used Claude Fable 5 for the analysis.","This article presents the results. All the code is available on Github：https://github.com/dylanjcastillo/blog/tree/main/_extras/pelicanmaxxing.","I built a grid of 8 animals × 6 vehicles = 48 prompts, where the famous prompt is one cell:","Every prompt uses almost identical phrasing to Simon’s, only switching the animal and vehicle. The animal and vehicle selection wasn’t done in a very rigorous manner, but I tried to vary both similarity to the original prompt and difficulty. Flamingo and heron are quite similar to pelicans; cat, raccoon, and otter are easy cases; antelope is hard; and whale is as different as you can get.","I tested seven models through OpenRouter：https://openrouter.ai/: GPT-5.6 Terra , Claude Sonnet 5 , Gemini 3.5 Flash , Grok 4.5 , Qwen3.7-Max , GLM-5.2 , and DeepSeek V4 Pro . I generated 3 samples per prompt, at temperature 1.0, requesting the same reasoning effort from every model. That resulted in 1,008 SVGs.","Then I ran each image through a three-stage pipeline:","My hypothesis is that if a lab trained on the benchmark, it should show up in some combination of the pelican row scoring above what the animal deserves, the bicycle column scoring above what the vehicle deserves, or the specific pelican-bicycle cell beating both.","Before any scoring, the simplest test is to look at the images yourself. Pick a lab to see everything it drew, with the judge’s score under each image (click to open full size):","I looked through the images myself before running the analysis below. Nothing jumped out at me. I couldn’t find a case where the pelican-bicycle images looked noticeably better than the rest of that model’s grid. Maybe in GLM-5.2’s first sample it felt slightly better than the rest, but that batch also produced a pretty cool heron on a skateboard, so I cannot say for sure. Otherwise they look like the rest of what each model draws, and the labs that draw good pelicans on bicycles also do a good job drawing other animal-vehicle combinations.","But this test is hard to replicate, and everyone will have a different opinion. So I wanted something more quantitative, which is why I opted for the method detailed above.","Here’s the mean animal rating per animal, pooled across all models:","The pelican is 6th of 8, behind cat, whale, raccoon, heron, and antelope. If AI labs were training on the benchmark, you’d expect pelicans at the top. Instead they’re in the bottom half. All seven labs draw cats, whales, and raccoons better than pelicans.","Of course, a pelican may simply be harder to draw than a cat. A lab could train on pelicans and still not push them past the easy animals, so this ranking alone can’t rule that out. I’ll adjust for difficulty in Evidence #4.","Bicycles fare even worse. They sit second from last, in a near-tie with planes, which come in last:","If labs were training on the benchmark, you’d expect bicycles near the top of this ranking. They’re not. However, the same caveat applies here. A bicycle is harder to draw than a skateboard: it needs two matching wheels, a frame that reaches both axles, handlebars, a seat, and pedals. The judge flags a missing or disconnected one of those on 2/3 of the bicycle images. You can train on bicycle images and still not do a great job relative to simpler vehicles.","One note on the plane, though: I should’ve picked “airplane” instead of “plane” because models often read it geometrically. They drew the animal standing on a flat surface instead of flying an aircraft. The plane is the only vehicle where the feature extractor sometimes found no vehicle at all (25 of 168 images, against zero for the other five), and 20% of plane images scored a 1 or 2 on the vehicle rating, against 5% for bicycles and none at all for boats, scooters, or skateboards.","Put the two together and the “pelican on a bicycle” ends up near the bottom of the ranking, at #42 of 48:","But again, some combinations might be just harder to draw than others.","To account for that, I fit a fixed-effects regression on all 1,008 images: score ~ lab + animal × vehicle, plus per-lab interaction terms for pelican, bicycle, and the pelican-bicycle cell, with robust standard errors. The animal × vehicle terms absorb the inherent difficulty of all 48 combinations. The interactions measure each lab’s benchmark-specific boost relative to the average lab, with confidence intervals.","Here are the full per-lab estimates. A pelicanmaxxing lab would show dots to the right of the zero line across its whole row:","Every pelican interval and every cell interval contains zero. Exactly one doesn’t: Gemini 3.5 Flash in the bicycle column. But with 21 tests at p < 0.05, chance alone predicts about one false positive (21 × 0.05 ≈ 1.05), and one is exactly what came up. It also doesn’t survive a multiple-comparisons correction: the Bonferroni threshold across the 21 tests is 0.05/21 ≈ 0.002, and its p-value is 0.022. The full table of estimates and p-values is in the repo：https://github.com/dylanjcastillo/blog/tree/main/_extras/pelicanmaxxing.","But these intervals are wide, about ±0.6 judge points on average. Any boost smaller than that won’t be captured by this test.","Some have suggested that the pelican on a bicycle looks like a memorized composition, pointing to recurring patterns such as the pelican always facing right, or recurring elements like a sun or a scarf. So I wanted to know if this was true.","Direction : All 21 pelican-bicycle images, across all seven labs, face right. No other animal/vehicle combination does that.","However, facing right is common: 60% of all 1,008 images do it. How common depends on the animal and the vehicle, and bicycles are one of the two vehicles where it’s strongest:","Pelicans are also among the animals that tend to face right:","It’s hard to draw a pelican or a bicycle facing the viewer, so models almost always draw them from the side, facing left or right. That’s why so few of their images are ambiguous. Other combinations also come close to unanimous: antelope on a scooter and pelican on a scooter land at 20 of 21, and heron on a bicycle at 19 of 21. So 21 out of 21 doesn’t seem like an outlier.","Scene elements : I let the extractor name any element it saw in the image. These are the counts:","A memorized scene would show up as the same set of elements recurring picture after picture. I went looking for that, and found some combinations do tend to produce the same elements every time. Every single flamingo on a boat has a sun in it. Otters on planes wear scarves 38% of the time. Cats on bicycles get a basket 38% of the time.","The pelican on a bicycle doesn’t seem to have anything particularly different about it. It just has some elements that appear more frequently, like every other animal-vehicle combination.","Sorry, HN haters, but there’s little evidence that AI labs are pelicanmaxxing. Or at least they’re not doing it in a plainly obvious manner.","Pelicans aren’t drawn any better than other animals. Bicycles aren’t drawn any better than other vehicles. And no lab draws the combination better than its pelicans and bicycles already predict. GLM-5.2 comes closest: it has the largest boost on the exact pelican-bicycle cell, and and its first pelican-on-bicycle sample caught my eye. But the effect is small and not significant, so I wouldn’t put too much weight on it.","The other thing that stands out is direction in the scene composition. All 21 pelican-bicycle images face right, the only combination in the grid where every image agrees. But it doesn’t seem that strange. Facing right is the norm across the experiment. Three other combinations land at 90% or above, and with 48 of them, I’m not surprised one reached 21 out of 21.","The more plausible story is SVGmaxxing like Google/DeepMind does. Other labs might be doing it more quietly. Sadly, this experiment can’t say who’s doing it. But at least you can sleep tonight knowing that AI labs are not producing terabytes of pelicans on bicycles just to trick Simon Willison.","If you want to look at the data yourself, the full pipeline is in the repo：https://github.com/dylanjcastillo/blog/tree/main/_extras/pelicanmaxxing.","the practice of optimizing AI models to achieve high scores on popular benchmarks.↩︎：#fnref1"],"articleImages":[],"mediaStatus":"none","articleBodyZh":["Dylan Castillo：https://dylancastillo.co","在过去几年里，Simon Willison：https://simonwillison.net/tags/pelican-riding-a-bicycle/ 使用同一个提示测试了每一个主要的大型语言模型发布版本：“生成一只骑自行车的鹈鹕的SVG。”","这个最初开玩笑式的基准测试已经成为人工智能中最著名的非正式基准测试之一。Simon 的骑自行车鹈鹕的结果通常是 Hacker News 上发布 AI 实验室新版本的帖子中点赞最多的评论之一。","这个基准现在已经足够有名，因此有大量的讨论：https://news.ycombinator.com/item?id=48994959 关于它的实用性以及 AI 实验室是否可能在上面进行“benchmaxxing”1：#fn1。当数十亿甚至数万亿美元的利益攸关，而一个强有力的结果可能帮助说服用户时，会不会很诱人去稍微让模型实现“pelicanmaxx”？","我想弄清楚，所以我组织了一个小实验。我在七个前沿模型中生成了1,008个SVG，用一个大型语言模型（LLM）进行评分，并使用 Claude Fable 5 进行分析。","本文呈现了实验结果。所有代码都可以在 Github 上获取：https://github.com/dylanjcastillo/blog/tree/main/_extras/pelicanmaxxing。","我建立了一个包含8种动物 × 6种交通工具 = 48个提示的网格，其中著名提示是其中的一个单元格：","每个提示几乎使用与 Simon 相同的措辞，只是更换了动物和交通工具。动物和交通工具的选择并没有采用非常严格的方法，但我尽量在与原始提示的相似性和难度上有所变化。火烈鸟和苍鹭与鹈鹕相当相似；猫、浣熊和水獭是简单案例；羚羊较难；而鲸鱼则是差异最大的一类。","我通过 OpenRouter：https://openrouter.ai/ 测试了七个模型：GPT-5.6 Terra、Claude Sonnet 5、Gemini 3.5 Flash、Grok 4.5、Qwen3.7-Max、GLM-5.2 和 DeepSeek V4 Pro。我为每个提示生成了3个样本，温度设为1.0，并要求每个模型使用相同的推理努力。这样总共生成了1,008个SVG。","然后我将每个图像通过一个三阶段管道处理：","我的假设是，如果实验室在该基准上进行了训练，它应该会在以下某种组合中表现出来：鹈鹕行的得分高于该动物应得的分数，自行车列的得分高于该交通工具应得的分数，或特定的鹈鹕-自行车单元格同时超出两者。","在任何评分之前，最简单的测试是你自己看看图片。选择一个实验室查看它绘制的所有内容，每张图片下都有裁判的评分（点击可以查看完整尺寸）：","在进行以下分析之前，我自己浏览了这些图像。没有什么特别突出。我找不到鹈鹕-自行车的图片明显好于该模型网格中其他图片的情况。也许在 GLM-5.2 的第一批样本中，它感觉略好于其他图片，但那批样本也生成了一只相当酷的滑板鹭，所以我不能确定。除此之外，它们看起来和每个模型绘制的其他内容一样，那些能画出优秀鹈鹕骑自行车的实验室，其他动物-交通工具组合也做得很好。","但这个测试难以复现，每个人的看法也不一样。所以我想要一些更量化的东西，这就是我选择上述方法的原因。","以下是按动物汇总、跨所有模型的动物平均评分：","鹈鹕在 8 种动物中排第 6，落后于猫、鲸鱼、浣熊、鹭和羚羊。如果 AI 实验室在基准上进行了训练，你会期望鹈鹕得分排在前列。而实际上它们位于下半部分。所有七个实验室画的猫、鲸鱼和浣熊都比画鹈鹕好。","当然，鹈鹕可能比猫更难画。一个实验室即使在鹈鹕上进行了训练，也可能无法让它们超过容易画的动物，所以仅凭这个排名不能排除这一点。我将在证据 #4 中调整难度因素。","自行车的表现更差。它们排倒数第二，几乎与飞机并列，而飞机排在最后：","如果实验室在基准上进行了训练，你会期望自行车在这个排名中位于靠前位置。但实际上并非如此。然而，同样的警告在此也适用。自行车比滑板更难画：它需要两个匹配的轮胎，一个延伸到两个车轴的车架，车把，座椅和踏板。裁判指出，在 2/3 的自行车图片中，其中一项要么缺失要么未连接。你可以在自行车图片上进行训练，但与较简单的交通工具相比，效果仍可能不佳。","不过关于飞机有一点需要说明：我本应该选择“airplane”而不是“plane”，因为模型通常从几何角度理解“plane”。它们把动物画在平面上，而不是画成驾驶飞机。飞机是唯一一个特征提取器有时根本找不到车辆的交通工具（168张图片中有25张，其他五种交通工具都是零），20%的飞机图片在车辆评分上得分为1或2，而自行车为5%，船、滑板车或滑板则完全没有低分。","综合来看，‘骑自行车的鹈鹕’最终排名靠后，在48个组合中排第42位：","不过，某些组合可能确实比其他组合更难画。","为了解决这个问题，我在所有1,008张图片上拟合了一个固定效应回归：score ~ lab + animal × vehicle，并加上每个实验室针对鹈鹕、自行车以及鹈鹕-自行车组合的交互项，并使用稳健标准误。animal × vehicle 项吸收了所有48种组合的固有难度。交互项测量每个实验室相对于平均实验室的专项加成，同时给出置信区间。","以下是每个实验室的完整估计结果。一个鹈鹕表现最优的实验室会在整行中看到点都在零线的右侧：","每个鹈鹕区间和每个单元格区间都包含零。恰好有一个不包含：Gemini 3.5 Flash在自行车列中。但是在21次检验中，随机出现约一个假阳性是正常的（21 × 0.05 ≈ 1.05），而这个结果正好符合预期。同时，它在多重比较校正下也不显著：21次检验的Bonferroni门槛为0.05/21 ≈ 0.002，而其p值为0.022。完整的估计值和p值表格在代码仓库：https://github.com/dylanjcastillo/blog/tree/main/_extras/pelicanmaxxing。","但这些区间较宽，平均约为 ±0.6 个评审分数。任何小于这个幅度的加成都无法通过此检验捕获。","有人建议骑自行车的鹈鹕看起来像是记忆中构图出来的，指出一些重复模式，例如鹈鹕总是面向右侧，或者重复出现的元素如太阳或围巾。因此我想知道这是否属实。","方向：所有21张鹈鹕-自行车图片，在七个实验室中都面向右，没有其他动物/交通工具组合有这种情况。","然而，面向右侧很常见：在所有1008张图片中，有60%是这样。具体有多普遍取决于动物和交通工具，而自行车是两种最明显的交通工具之一：","鹈鹕也是倾向于面向右侧的动物之一：","很难画出面向观众的鹈鹕或自行车，所以模型几乎总是从侧面画它们，面向左或右。这就是为什么它们的图像很少模糊不清。其他组合也几乎是一致的：滑板上的羚羊和滑板上的鹈鹕达到21张中的20张，自行车上的鹭鸟达到21张中的19张。所以21张全正确看起来并不奇怪。","场景元素：我让提取器命名它在图像中看到的任何元素。这些是统计数据：","一个记忆化场景会表现为同一套元素在每张图片中重复出现。我去寻找了这一点，发现确实有些组合每次都会生成相同的元素。每一张船上的火烈鸟图片里都有太阳。飞机上的水獭38%会戴围巾。自行车上的猫38%会有篮子。","自行车上的鹈鹕似乎并没有特别不同的地方。它只是有一些出现频率更高的元素，就像其他动物-交通工具组合一样。","抱歉，HN的反对者，但没有多少证据表明AI实验室在刻意强化鹈鹕。或者至少他们没有以明显的方式这么做。","鹈鹕并没有比其他动物画得更好。自行车也没有比其他交通工具画得更好。而且没有哪个实验室能比其现有的鹈鹕和自行车预测效果更好。GLM-5.2最接近：它在鹈鹕-自行车具体单元上提升最大，而且它的第一个鹈鹕骑自行车样本引起了我的注意。但这种效果很小且不显著，所以我不会把它看得太重。","另一件突出的事情是场景构图中的方向。所有21张鹈鹕骑自行车的图片都面向右侧，这是网格中唯一每张图片都一致的组合。但这看起来并不奇怪。在整个实验中，面向右侧是常态。其他三个组合的面向右侧比例达到90%或以上，而在48个组合中，我一点也不惊讶有一个达到了21张全对。","更可信的说法是，SVGmaxxing 就像 Google/DeepMind 那样进行。其他实验室可能在更低调地做这件事。遗憾的是，这个实验无法说明到底是谁在做。但至少你今晚可以安心睡觉，因为 AI 实验室并不是为了愚弄 Simon Willison 而生成成千上万的骑自行车的鹈鹕数据。","如果你想自己查看数据，完整的流程在仓库里：https://github.com/dylanjcastillo/blog/tree/main/_extras/pelicanmaxxing。","优化 AI 模型以在流行基准测试中取得高分的做法。↩︎：#fnref1"],"translationStatus":"translated","bodyOrigin":"source-page","editorial":{"summary":"Aioga 编辑摘要：一项针对GPT-5.6 Terra等七款模型的对比实验显示，这些模型在\"鹈鹕骑自行车\"这一知名非正式基准测试上并未表现出针对性优化。 Aioga 将其归入「技巧观点」方向，重点关注它对真实使用和行业竞争的影响。","background":"背景分析：模型与研究类动态需要结合能力边界、开放方式、成本、可用性和真实任务表现判断，单项指标领先不等于已经形成稳定采用。","viewpoint":"Aioga 判断：这条动态更适合作为行业观察信号，当前信息足以建立线索，但不足以推导长期结论。","implications":"影响分析：对相关团队而言，短期应先核对来源、可用范围和实际成本，再判断是否值得接入或跟进。","nextStep":"后续观察：继续观察官方文档、实际可用性、价格变化、开发者反馈和竞品回应。","evidenceRefs":["title","summary","articleBody"],"confidence":"medium","status":"published","aiGenerated":false,"autoApproved":true,"generatedBy":"rule-safe-fallback","generatedAt":"2026-07-23T06:49:19.018Z","sourceHash":"4d09e76f6bc8ef2a","validation":{"passed":true,"mode":"rule-safe-fallback","checks":["schema","length","source-attribution","no-html"]}},"tags":["技巧观点","Hacker News 热门（buzzing.cc 中文翻译）"],"translations":{"zh-CN":{"title":"七款前沿模型\"鹈鹕骑自行车\"基准测试未发现针对性优化","summary":"一项针对GPT-5.6 Terra等七款模型的对比实验显示，这些模型在\"鹈鹕骑自行车\"这一知名非正式基准测试上并未表现出针对性优化。研究者生成1，008张SVG图像，经评分发现鹈鹕在8种动物中排名第6，自行车在6种交通工具中排名第5，两者组合在48个提示中仅列第42位。","category":"技巧观点","source":"dylancastillo.co","aggregationSource":"Hacker News 热门（buzzing.cc 中文翻译）","pageTitle":"七款前沿模型\"鹈鹕骑自行车\"基准测试未发现针对性优化 - Aioga AI资讯","description":"一项针对GPT-5.6 Terra等七款模型的对比实验显示，这些模型在\"鹈鹕骑自行车\"这一知名非正式基准测试上并未表现出针对性优化。研究者生成1，008张SVG图像，经评分发现鹈鹕在8种动物中排名第6，自行车在6种交通工具中排名第5，两者组合在48个提示中仅列第42位。","url":"https://www.aioga.com/news/cmrwi2n4z024froj0leere07a/"},"en":{"title":"Seven cutting-edge models 'Pelican Rides a Bike' benchmark tests did not find targeted optimizations","summary":"A comparative experiment involving seven models, including GPT-5.6 Terra, showed that these models were not specifically optimized for the well-known informal benchmark test 'pelican riding a bicycle.' Researchers generated 1,008 SVG images, and scoring results showed that the pelican ranked 6th among 8 animals, the bicycle ranked 5th among 6 types of vehicles, and the combination ranked only 42nd out of 48 prompts.","category":"Insights","source":"Hacker News 热门（buzzing.cc 中文翻译）","aggregationSource":"Hacker News 热门（buzzing.cc 中文翻译）","pageTitle":"Seven cutting-edge models 'Pelican Rides a Bike' benchmark tests did not find targeted optimizations - Aioga AI News","description":"A comparative experiment involving seven models, including GPT-5.6 Terra, showed that these models were not specifically optimized for the well-known informal benchmark test 'pelic...","url":"https://www.aioga.com/en/news/cmrwi2n4z024froj0leere07a/","contentTranslated":true,"sourceHash":"f69e93d99583fdc1","translatedAt":"2026-07-22T21:23:22.584Z"},"ja":{"title":"七つの最先端モデル「ペリカンが自転車に乗る」ベンチマークテストで特定の最適化は見つからなかった","summary":"GPT-5.6 Terraなど7種類のモデルを対象とした比較実験では、これらのモデルは「ペリカンが自転車に乗る」というよく知られた非公式ベンチマークテストに対して特化した最適化を示さなかったことが明らかになった。研究者は1,008枚のSVG画像を生成し、評価の結果、ペリカンは8種類の動物の中で6位、自転車は6種類の交通手段の中で5位であり、この組み合わせは48のプロンプト中42位に過ぎなかった。","category":"ヒントと視点","source":"Hacker News 热门（buzzing.cc 中文翻译）","aggregationSource":"Hacker News 热门（buzzing.cc 中文翻译）","pageTitle":"七つの最先端モデル「ペリカンが自転車に乗る」ベンチマークテストで特定の最適化は見つからなかった - Aioga AIニュース","description":"GPT-5.6 Terraなど7種類のモデルを対象とした比較実験では、これらのモデルは「ペリカンが自転車に乗る」というよく知られた非公式ベンチマークテストに対して特化した最適化を示さなかったことが明らかになった。研究者は1,008枚のSVG画像を生成し、評価の結果、ペリカンは8種類の動物の中で6位、自転車は6種類の交通手段の中で5位であり、この組み合わせは4...","url":"https://www.aioga.com/ja/news/cmrwi2n4z024froj0leere07a/","contentTranslated":true,"sourceHash":"f69e93d99583fdc1","translatedAt":"2026-07-22T21:23:32.383Z"},"ko":{"title":"7가지 최첨단 모델 '펠리컨 자전거 타기' 벤치마크 테스트에서 특화된 최적화 발견되지 않음","summary":"GPT-5.6 Terra 등 7개 모델을 대상으로 한 비교 실험에서, 이들 모델은 '펠리컨이 자전거를 타는 것'이라는 잘 알려진 비공식 벤치마크 테스트에서 특별히 최적화된 성능을 보이지 못했다. 연구자들은 1,008개의 SVG 이미지를 생성하고 평가한 결과, 펠리컨은 8종의 동물 중 6위를 차지했고, 자전거는 6종의 교통수단 중 5위를 차지했으며, 두 가지를 조합한 경우 48개의 프롬프트 중에서 단지 42위를 기록했다.","category":"인사이트","source":"Hacker News 热门（buzzing.cc 中文翻译）","aggregationSource":"Hacker News 热门（buzzing.cc 中文翻译）","pageTitle":"7가지 최첨단 모델 '펠리컨 자전거 타기' 벤치마크 테스트에서 특화된 최적화 발견되지 않음 - Aioga AI 뉴스","description":"GPT-5.6 Terra 등 7개 모델을 대상으로 한 비교 실험에서, 이들 모델은 '펠리컨이 자전거를 타는 것'이라는 잘 알려진 비공식 벤치마크 테스트에서 특별히 최적화된 성능을 보이지 못했다. 연구자들은 1,008개의 SVG 이미지를 생성하고 평가한 결과, 펠리컨은 8종의 동물 중 6위를 차지했고, 자전거는 6종의 교통...","url":"https://www.aioga.com/ko/news/cmrwi2n4z024froj0leere07a/","contentTranslated":true,"sourceHash":"f69e93d99583fdc1","translatedAt":"2026-07-22T21:24:27.137Z"},"es":{"title":"Siete modelos avanzados \"Pelícano montando en bicicleta\" no encontraron optimizaciones específicas en las pruebas de referencia","summary":"Un experimento comparativo realizado con siete modelos, incluyendo GPT-5.6 Terra, mostró que estos modelos no presentaban optimización específica en la conocida prueba de referencia informal \"pelícano montando bicicleta\". Los investigadores generaron 1.008 imágenes SVG y, tras la evaluación, encontraron que el pelícano ocupaba el sexto lugar entre ocho animales, la bicicleta el quinto lugar entre seis medios de transporte, y la combinación de ambos ocupaba solo el puesto 42 de 48 indicaciones.","category":"Ideas","source":"Hacker News 热门（buzzing.cc 中文翻译）","aggregationSource":"Hacker News 热门（buzzing.cc 中文翻译）","pageTitle":"Siete modelos avanzados \"Pelícano montando en bicicleta\" no encontraron optimizaciones específicas en las pruebas de referencia - Aioga Noticias de IA","description":"Un experimento comparativo realizado con siete modelos, incluyendo GPT-5.6 Terra, mostró que estos modelos no presentaban optimización específica en la conocida prueba de referenci...","url":"https://www.aioga.com/es/news/cmrwi2n4z024froj0leere07a/","contentTranslated":true,"sourceHash":"f69e93d99583fdc1","translatedAt":"2026-07-22T21:24:24.900Z"},"fr":{"title":"Sept modèles de pointe \"le pélican fait du vélo\" n'ont montré aucune optimisation ciblée lors du test de référence","summary":"Une expérience comparative portant sur sept modèles, dont GPT-5.6 Terra, a montré que ces modèles n'étaient pas spécifiquement optimisés pour le test de référence informel bien connu « un pélican fait du vélo ». Les chercheurs ont généré 1 008 images SVG et, après évaluation, ont constaté que le pélican se classait 6ème parmi 8 animaux, le vélo 5ème parmi 6 moyens de transport, et la combinaison des deux n'occupait que la 42ème position sur 48 suggestions.","category":"Analyses","source":"Hacker News 热门（buzzing.cc 中文翻译）","aggregationSource":"Hacker News 热门（buzzing.cc 中文翻译）","pageTitle":"Sept modèles de pointe \"le pélican fait du vélo\" n'ont montré aucune optimisation ciblée lors du test de référence - Aioga Actualités IA","description":"Une expérience comparative portant sur sept modèles, dont GPT-5.6 Terra, a montré que ces modèles n'étaient pas spécifiquement optimisés pour le test de référence informel bien con...","url":"https://www.aioga.com/fr/news/cmrwi2n4z024froj0leere07a/","contentTranslated":true,"sourceHash":"f69e93d99583fdc1","translatedAt":"2026-07-22T21:25:18.662Z"},"de":{"title":"Sieben fortschrittliche Modelle ‚Pelikan fährt Fahrrad‘ Benchmark-Tests zeigten keine gezielten Optimierungen","summary":"Ein Vergleichsexperiment mit sieben Modellen, darunter GPT-5.6 Terra, zeigte, dass diese Modelle auf dem bekannten informellen Benchmark-Test „Pelekan auf dem Fahrrad“ keine gezielte Optimierung aufwiesen. Die Forscher erstellten 1.008 SVG-Bilder und stellten bei der Bewertung fest, dass der Pelikan unter acht Tieren den 6. Platz, das Fahrrad unter sechs Verkehrsmitteln den 5. Platz belegte und die Kombination von beiden in 48 Aufforderungen nur den 42. Platz einnahm.","category":"技巧观点","source":"Hacker News 热门（buzzing.cc 中文翻译）","aggregationSource":"Hacker News 热门（buzzing.cc 中文翻译）","pageTitle":"Sieben fortschrittliche Modelle ‚Pelikan fährt Fahrrad‘ Benchmark-Tests zeigten keine gezielten Optimierungen - Aioga KI-News","description":"Ein Vergleichsexperiment mit sieben Modellen, darunter GPT-5.6 Terra, zeigte, dass diese Modelle auf dem bekannten informellen Benchmark-Test „Pelekan auf dem Fahrrad“ keine geziel...","url":"https://www.aioga.com/de/news/cmrwi2n4z024froj0leere07a/","contentTranslated":true,"sourceHash":"f69e93d99583fdc1","translatedAt":"2026-07-22T21:25:14.934Z"},"pt-BR":{"title":"Sete modelos de ponta 'Pelve andando de bicicleta' não encontraram otimizações específicas nos testes de referência","summary":"Um experimento comparativo envolvendo sete modelos, incluindo o GPT-5.6 Terra, mostrou que esses modelos não apresentaram otimização específica para o conhecido benchmark informal \"pelicano andando de bicicleta\". Os pesquisadores geraram 1.008 imagens SVG e, após avaliação, descobriram que o pelicano ficou em 6º lugar entre 8 tipos de animais, a bicicleta em 5º lugar entre 6 tipos de meios de transporte, e a combinação dos dois ficou apenas na 42ª posição entre 48 prompts.","category":"技巧观点","source":"Hacker News 热门（buzzing.cc 中文翻译）","aggregationSource":"Hacker News 热门（buzzing.cc 中文翻译）","pageTitle":"Sete modelos de ponta 'Pelve andando de bicicleta' não encontraram otimizações específicas nos testes de referência - Aioga Notícias de IA","description":"Um experimento comparativo envolvendo sete modelos, incluindo o GPT-5.6 Terra, mostrou que esses modelos não apresentaram otimização específica para o conhecido benchmark informal...","url":"https://www.aioga.com/pt-BR/news/cmrwi2n4z024froj0leere07a/","contentTranslated":true,"sourceHash":"f69e93d99583fdc1","translatedAt":"2026-07-22T21:26:17.036Z"},"ru":{"title":"Семь передовых моделей \"Пеликан едет на велосипеде\" не показали целенаправленной оптимизации в бенчмарке","summary":"Сравнительный эксперимент, проведённый на семи моделях, включая GPT-5.6 Terra, показал, что эти модели не продемонстрировали целевой оптимизации на известном неформальном бенчмарке «пеликан на велосипеде». Исследователи сгенерировали 1 008 SVG-изображений, и по результатам оценок пеликан занял 6-е место среди 8 видов животных, велосипед — 5-е место среди 6 видов транспортных средств, а их комбинация в 48 подсказках заняла лишь 42-е место.","category":"技巧观点","source":"Hacker News 热门（buzzing.cc 中文翻译）","aggregationSource":"Hacker News 热门（buzzing.cc 中文翻译）","pageTitle":"Семь передовых моделей \"Пеликан едет на велосипеде\" не показали целенаправленной оптимизации в бенчмарке - Aioga Новости ИИ","description":"Сравнительный эксперимент, проведённый на семи моделях, включая GPT-5.6 Terra, показал, что эти модели не продемонстрировали целевой оптимизации на известном неформальном бенчмарке...","url":"https://www.aioga.com/ru/news/cmrwi2n4z024froj0leere07a/","contentTranslated":true,"sourceHash":"f69e93d99583fdc1","translatedAt":"2026-07-22T21:26:13.489Z"},"ar":{"title":"سبعة نماذج متقدمة \"الهُدْهُد يركب الدراجة\" لم تظهر الاختبارات المعيارية أي تحسين مستهدف","summary":"أظهرت تجربة مقارنة شملت سبعة نماذج مثل GPT-5.6 Terra أن هذه النماذج لم تظهر أي تحسين محدد على اختبار معياري غير رسمي معروف باسم \"البجع يركب الدراجة\". قام الباحثون بإنشاء 1,008 صور بصيغة SVG، وبعد التقييم تبين أن البجع احتل المرتبة السادسة بين 8 حيوانات، والدراجة المرتبة الخامسة بين 6 وسائل نقل، بينما احتلت عبارة الجمع بينهما المرتبة 42 فقط من بين 48 تلميحًا.","category":"技巧观点","source":"Hacker News 热门（buzzing.cc 中文翻译）","aggregationSource":"Hacker News 热门（buzzing.cc 中文翻译）","pageTitle":"سبعة نماذج متقدمة \"الهُدْهُد يركب الدراجة\" لم تظهر الاختبارات المعيارية أي تحسين مستهدف - Aioga أخبار الذكاء الاصطناعي","description":"أظهرت تجربة مقارنة شملت سبعة نماذج مثل GPT-5.6 Terra أن هذه النماذج لم تظهر أي تحسين محدد على اختبار معياري غير رسمي معروف باسم \"البجع يركب الدراجة\". قام الباحثون بإنشاء 1,008 صور...","url":"https://www.aioga.com/ar/news/cmrwi2n4z024froj0leere07a/","contentTranslated":true,"sourceHash":"f69e93d99583fdc1","translatedAt":"2026-07-22T21:27:06.253Z"},"hi":{"title":"सात उन्नत मॉडल 'पेलिकन साइकिल चला रहा है' बेंचमार्क परीक्षण में कोई लक्षित अनुकूलन नहीं पाया गया","summary":"एक GPT-5.6 Terra सहित सात मॉडलों पर एक तुलनात्मक प्रयोग से पता चला कि इन मॉडलों ने \"पेलिकन साइकिल चला रहा है\" इस प्रसिद्ध अनौपचारिक बेंचमार्क परीक्षण के लिए कोई विशिष्ट अनुकूलन नहीं दिखाया। शोधकर्ताओं ने 1,008 SVG छवियां उत्पन्न कीं, और मूल्यांकन से पता चला कि पेलिकन 8 प्रकार के जानवरों में छठे स्थान पर था, साइकिल 6 प्रकार के परिवहन साधनों में पांचवें स्थान पर थी, और दोनों का संयोजन 48 संकेतों में केवल 42वें स्थान पर था।","category":"技巧观点","source":"Hacker News 热门（buzzing.cc 中文翻译）","aggregationSource":"Hacker News 热门（buzzing.cc 中文翻译）","pageTitle":"सात उन्नत मॉडल 'पेलिकन साइकिल चला रहा है' बेंचमार्क परीक्षण में कोई लक्षित अनुकूलन नहीं पाया गया - Aioga AI समाचार","description":"एक GPT-5.6 Terra सहित सात मॉडलों पर एक तुलनात्मक प्रयोग से पता चला कि इन मॉडलों ने \"पेलिकन साइकिल चला रहा है\" इस प्रसिद्ध अनौपचारिक बेंचमार्क परीक्षण के लिए कोई विशिष्ट अनुकूलन नही...","url":"https://www.aioga.com/hi/news/cmrwi2n4z024froj0leere07a/","contentTranslated":true,"sourceHash":"f69e93d99583fdc1","translatedAt":"2026-07-22T21:27:16.487Z"},"it":{"title":"Sette modelli all'avanguardia 'Il pellicano va in bicicletta' non hanno mostrato ottimizzazioni mirate nei test di riferimento","summary":"Un esperimento comparativo su sette modelli, tra cui GPT-5.6 Terra, ha mostrato che questi modelli non presentano ottimizzazioni specifiche per il noto benchmark informale \"pellicano che va in bicicletta\". I ricercatori hanno generato 1.008 immagini SVG e, valutandole, hanno scoperto che il pellicano si colloca al 6° posto tra 8 animali, la bicicletta al 5° posto tra 6 mezzi di trasporto, e la combinazione dei due appare solo al 42° posto su 48 prompt.","category":"技巧观点","source":"Hacker News 热门（buzzing.cc 中文翻译）","aggregationSource":"Hacker News 热门（buzzing.cc 中文翻译）","pageTitle":"Sette modelli all'avanguardia 'Il pellicano va in bicicletta' non hanno mostrato ottimizzazioni mirate nei test di riferimento - Aioga Notizie IA","description":"Un esperimento comparativo su sette modelli, tra cui GPT-5.6 Terra, ha mostrato che questi modelli non presentano ottimizzazioni specifiche per il noto benchmark informale \"pellica...","url":"https://www.aioga.com/it/news/cmrwi2n4z024froj0leere07a/","contentTranslated":true,"sourceHash":"f69e93d99583fdc1","translatedAt":"2026-07-22T21:28:19.106Z"},"nl":{"title":"Zeven geavanceerde modellen \"Pelikan fietst\" benchmarktests hebben geen gerichte optimalisatie gevonden","summary":"Een vergelijkend experiment met zeven modellen, waaronder GPT-5.6 Terra, toonde aan dat deze modellen niet specifiek geoptimaliseerd waren voor de bekende informele benchmark 'pelikaan die fiets rijdt'. Onderzoekers genereerden 1.008 SVG-afbeeldingen en na beoordeling bleek de pelikaan op de 6e plaats te staan van 8 dieren, de fiets op de 5e plaats van 6 vervoersmiddelen, en de combinatie van beiden stond slechts op de 42e plaats van 48 prompts.","category":"技巧观点","source":"Hacker News 热门（buzzing.cc 中文翻译）","aggregationSource":"Hacker News 热门（buzzing.cc 中文翻译）","pageTitle":"Zeven geavanceerde modellen \"Pelikan fietst\" benchmarktests hebben geen gerichte optimalisatie gevonden - Aioga AI-nieuws","description":"Een vergelijkend experiment met zeven modellen, waaronder GPT-5.6 Terra, toonde aan dat deze modellen niet specifiek geoptimaliseerd waren voor de bekende informele benchmark 'peli...","url":"https://www.aioga.com/nl/news/cmrwi2n4z024froj0leere07a/","contentTranslated":true,"sourceHash":"f69e93d99583fdc1","translatedAt":"2026-07-22T21:28:07.372Z"},"tr":{"title":"Yedi ileri düzey model 'Pelikan bisiklet sürüyor' kıyaslama testinde hedefe yönelik optimizasyon bulunamadı","summary":"GPT-5.6 Terra ve diğer yedi model üzerinde yapılan bir karşılaştırma deneyinde, bu modellerin \"pelikan bisiklete biniyor\" adlı ünlü gayriresmî benchmark testinde özel bir optimizasyon göstermediği ortaya çıktı. Araştırmacılar 1.008 SVG görüntüsü üretti ve puanlama sonucunda pelikanın 8 hayvan arasında 6. sırada, bisikletin 6 ulaşım aracı arasında 5. sırada olduğu, ikisinin birleşimi ise 48 ipucunun yalnızca 42. sırasında yer aldığı görüldü.","category":"技巧观点","source":"Hacker News 热门（buzzing.cc 中文翻译）","aggregationSource":"Hacker News 热门（buzzing.cc 中文翻译）","pageTitle":"Yedi ileri düzey model 'Pelikan bisiklet sürüyor' kıyaslama testinde hedefe yönelik optimizasyon bulunamadı - Aioga AI Haberleri","description":"GPT-5.6 Terra ve diğer yedi model üzerinde yapılan bir karşılaştırma deneyinde, bu modellerin \"pelikan bisiklete biniyor\" adlı ünlü gayriresmî benchmark testinde özel bir optimizas...","url":"https://www.aioga.com/tr/news/cmrwi2n4z024froj0leere07a/","contentTranslated":true,"sourceHash":"f69e93d99583fdc1","translatedAt":"2026-07-22T21:29:10.954Z"},"vi":{"title":"Bảy mô hình tiên tiến 'Chim bồ nông đi xe đạp' không phát hiện tối ưu hóa cụ thể trong các bài kiểm tra chuẩn","summary":"Một thí nghiệm so sánh bảy mô hình, bao gồm GPT-5.6 Terra, cho thấy các mô hình này không được tối ưu hóa đặc biệt cho bài kiểm tra chuẩn không chính thức nổi tiếng \"cá mỏ vịt đi xe đạp\". Các nhà nghiên cứu đã tạo ra 1.008 hình ảnh SVG và đánh giá cho thấy cá mỏ vịt xếp hạng 6 trong số 8 loài động vật, xe đạp xếp hạng 5 trong số 6 phương tiện giao thông, và sự kết hợp của cả hai chỉ đứng thứ 42 trong số 48 gợi ý.","category":"技巧观点","source":"Hacker News 热门（buzzing.cc 中文翻译）","aggregationSource":"Hacker News 热门（buzzing.cc 中文翻译）","pageTitle":"Bảy mô hình tiên tiến 'Chim bồ nông đi xe đạp' không phát hiện tối ưu hóa cụ thể trong các bài kiểm tra chuẩn - Tin tức AI Aioga","description":"Một thí nghiệm so sánh bảy mô hình, bao gồm GPT-5.6 Terra, cho thấy các mô hình này không được tối ưu hóa đặc biệt cho bài kiểm tra chuẩn không chính thức nổi tiếng \"cá mỏ vịt đi x...","url":"https://www.aioga.com/vi/news/cmrwi2n4z024froj0leere07a/","contentTranslated":true,"sourceHash":"f69e93d99583fdc1","translatedAt":"2026-07-22T21:29:05.042Z"},"id":{"title":"Tujuh model terdepan 'Pelikan mengendarai sepeda' tes tolok ukur tidak menemukan optimasi khusus","summary":"Sebuah eksperimen perbandingan terhadap tujuh model termasuk GPT-5.6 Terra menunjukkan bahwa model-model ini tidak menunjukkan optimasi khusus pada uji benchmark informal yang terkenal yaitu \"burung pelikan mengendarai sepeda\". Para peneliti menghasilkan 1.008 gambar SVG, dan setelah dinilai ditemukan bahwa pelikan berada di peringkat ke-6 dari 8 jenis hewan, sepeda berada di peringkat ke-5 dari 6 jenis kendaraan, dan kombinasi keduanya hanya berada di peringkat ke-42 dari 48 prompt.","category":"技巧观点","source":"Hacker News 热门（buzzing.cc 中文翻译）","aggregationSource":"Hacker News 热门（buzzing.cc 中文翻译）","pageTitle":"Tujuh model terdepan 'Pelikan mengendarai sepeda' tes tolok ukur tidak menemukan optimasi khusus - Berita AI Aioga","description":"Sebuah eksperimen perbandingan terhadap tujuh model termasuk GPT-5.6 Terra menunjukkan bahwa model-model ini tidak menunjukkan optimasi khusus pada uji benchmark informal yang terk...","url":"https://www.aioga.com/id/news/cmrwi2n4z024froj0leere07a/","contentTranslated":true,"sourceHash":"f69e93d99583fdc1","translatedAt":"2026-07-22T21:30:03.721Z"},"th":{"title":"เจ็ดโมเดลแนวหน้าการทดสอบมาตรฐาน 'นกเพลินทะเลปั่นจักรยาน' ไม่พบการปรับแต่งเฉพาะ","summary":"การทดลองเปรียบเทียบเจ็ดรุ่นโมเดล เช่น GPT-5.6 Terra แสดงให้เห็นว่าโมเดลเหล่านี้ไม่ได้รับการปรับปรุงเป็นพิเศษสำหรับการทดสอบมาตรฐานไม่เป็นทางการที่มีชื่อเสียง \"เพลาคอคาลิปส์ขี่จักรยาน\" นักวิจัยสร้างภาพ SVG จำนวน 1,008 ภาพ จากผลการประเมินพบว่า เพลาคอคาลิปส์อยู่ในอันดับ 6 จาก 8 สัตว์ จักรยานอยู่ในอันดับ 5 จาก 6 ยานพาหนะ และการรวมกันทั้งสองปรากฏใน 48 คำสั่งเพียงลำดับที่ 42","category":"技巧观点","source":"Hacker News 热门（buzzing.cc 中文翻译）","aggregationSource":"Hacker News 热门（buzzing.cc 中文翻译）","pageTitle":"เจ็ดโมเดลแนวหน้าการทดสอบมาตรฐาน 'นกเพลินทะเลปั่นจักรยาน' ไม่พบการปรับแต่งเฉพาะ - ข่าว AI Aioga","description":"การทดลองเปรียบเทียบเจ็ดรุ่นโมเดล เช่น GPT-5.6 Terra แสดงให้เห็นว่าโมเดลเหล่านี้ไม่ได้รับการปรับปรุงเป็นพิเศษสำหรับการทดสอบมาตรฐานไม่เป็นทางการที่มีชื่อเสียง \"เพลาคอคาลิปส์ขี่จักรยา...","url":"https://www.aioga.com/th/news/cmrwi2n4z024froj0leere07a/","contentTranslated":true,"sourceHash":"f69e93d99583fdc1","translatedAt":"2026-07-22T21:30:19.607Z"},"pl":{"title":"Siedem nowoczesnych modeli „Pelikan jeździ na rowerze” nie wykazało optymalizacji ukierunkowanej w testach porównawczych","summary":"Eksperyment porównawczy przeprowadzony na siedmiu modelach, w tym GPT-5.6 Terra, wykazał, że modele te nie wykazywały optymalizacji pod kątem znanego nieformalnego testu \"pelikan jadący na rowerze\". Naukowcy wygenerowali 1 008 obrazów SVG, a po ocenie okazało się, że pelikan zajmuje 6. miejsce spośród 8 zwierząt, rower 5. miejsce spośród 6 środków transportu, a ich połączenie w 48 podpowiedziach znalazło się dopiero na 42. miejscu.","category":"技巧观点","source":"Hacker News 热门（buzzing.cc 中文翻译）","aggregationSource":"Hacker News 热门（buzzing.cc 中文翻译）","pageTitle":"Siedem nowoczesnych modeli „Pelikan jeździ na rowerze” nie wykazało optymalizacji ukierunkowanej w testach porównawczych - Aioga Wiadomości AI","description":"Eksperyment porównawczy przeprowadzony na siedmiu modelach, w tym GPT-5.6 Terra, wykazał, że modele te nie wykazywały optymalizacji pod kątem znanego nieformalnego testu \"pelikan j...","url":"https://www.aioga.com/pl/news/cmrwi2n4z024froj0leere07a/","contentTranslated":true,"sourceHash":"f69e93d99583fdc1","translatedAt":"2026-07-22T21:31:14.563Z"}}}}