御姐婷婷

这两天试了试chat GPT5.2，这个版本被海内外用户骂翻了天，我先说结论，仅从我粗浅的使用程度来看，这个版本的出现，可能代表着文科生的春天来了，一个人的表达能力，可能是未来5-10年内最为重要的能力。
海外目前对GPT5.2的评价有点极端，一边是“降智了”“不敢说话了”“像被阉了一刀”，另一边是“代码更稳了”“科研更好用了”。如果只看情绪，很容易得出一个表象的结果：最新版不行了。
但如果把这些反馈拆开看，会发现一个很有意思的分野，骂得最狠的，往往不是它做不到，而是它“不好玩了”“不陪聊了”“不替我冒险说话了”。
而这恰恰是5.2真正变化的地方。
一、5.2不是变笨，而是换了一种说话方式
很多人觉得5.2“不展开”“太谨慎”“四平八稳”，其实这不是能力下滑，更像是表达策略的收紧。
5.1之前，GPT 很擅长一件事，顺着你的问题往下编一个完整叙事。哪怕某些环节它并不确定，也会把话说满，说得好像一切都已经想清楚了。这对聊天、脑暴、情绪价值来说很好，但在很多专业场景里是有风险的。
5.2明显更倾向于先确认边界，再往里走。它更愿意告诉你这里其实有多个解释、这个前提不一定成立，而不是直接给一个听起来很爽的答案。这会让一部分用户觉得没劲、不如以前敢说，但从另一个角度看，它更像一个会踩刹车的合作者，而不是一味迎合的陪聊对象。
二、为什么我反而觉得：文科生的时代可能来了
一个很少被提到的变化是，5.2对自然语言提示的容忍度和解析能力明显更强了。
以前你想让GPT干点复杂的事，往往要把prompt写得像半篇技术说明书，层级、格式、约束一个不少，甚至提示词编辑者，在国内成为了不少新创公司的新增岗位，还有和AI剧的抽卡师合二为一，你的叙述表达能力强，盈利能力就会强。现在你用更口语、更模糊、更人类的方式描述需求，它也能抓住重点，知道你到底想干嘛。
这对程序员当然是加分项，但对文科生、研究者来说，提升更大：
做分析、评论、科普时，你可以用“我们换个角度想想”“这里是不是有点反直觉”这种话，它能顺着你的思路继续推，而不是拉回模板，而且用封闭式prompt将搜索限定在指定范围内，也是真限定了，而不是杜撰，相当于5.2把自己做成了一个聚合平台+爬虫+生成AI，而不仅仅是个生成AI了。
在开放性问题上，它更像一个愿意跟你一起慢慢理清逻辑的对象，而不是急着给结论。
某种意义上，5.2更像是把会写 prompt这件事，抬高到了更高的高度，这是比编程语言更好掌握的自然语序和话术，你不需要掌握一堆技巧，只要把话说清楚，说得像跟人交流一样。
三、差评集中在几个点，其实都能解释
那些被反复提到的退步，大致可以归到几类：
不够敢说、情绪价值低
这是事实，但也是选择。OpenAI很明显在压低讨好型表达，这对情感陪伴和闲聊用户不友好，但对严肃使用场景是加分的。
展开少、细节要追问
5.2更像是等你确认方向再往深里挖，而不是一次性把所有可能性都铺出来，它把主动权更多交还给用户，它鼓励更多有想法的文科生，而不是什么都直接由它来做的躺平者，也因此，你的目的性更强，知道用常规方法实现的路径，再用AI来表达的话，会更加事半功倍。
速度慢、算力贵
这个没得洗，xhigh、thinking 模式确实慢，也确实贵，但你会发现，慢主要慢在它真的在把上下文都读完，目前目测是3万行代码左右，或不超过5万的英文（其实能达到8万左右，但分析效率会下降），而不是秒回一堆看似合理的废话。
写作不如Gemini顺滑
这点很多人说得对，GPT的文字依然偏理性、偏结构化，它更适合论文前的选题确认、综述会构建框架、填充，换句话说，它更适合当底稿和逻辑骨架，是调色盘和素描纸，Gemini更像是笔。
四、它更像工具，而不是会陪你的角色
如果一定要给5.2一个定位，我会说：它正在从万能聊天 AI，往通用认知工具那边走。
它不太愿意替你拍板，不太愿意帮你情绪兜底，也不太愿意在不确定的地方给你一个爽快答案。但它很擅长：
帮你把一个模糊问题拆清楚
指出你话里可能藏着的前提
在你给定方向后，把推理一步步铺稳
这对很多人来说确实没以前好用了，但对另一部分人来说，反而更顺手，就像福尔摩斯身边的那个华生。
GPT5.2当然不是完美版本，它在风格调整、图像、多模态上还有明显短板，这点的确不如国内的一些大模型，价格策略也很激进。但把它简单归结为退步、翻车，其实有点冤。
它更像是一次取舍明确的调整，少一点讨好，多一点克制；少一点表演，多一点工具感。
如果你要的是陪聊、灵感轰炸、情绪共鸣，那它确实不如以前有趣；但如果你要的是一个能听懂人话、能跟你用自然语言一起把问题理顺的助手，那5.2终于长成了一个可以长期共事的对象。
也许这就是为什么，有人觉得它变差了，有人却觉得它刚刚开始好用。

This matter also trended a couple of days ago, and I just saw it. It's embarrassing to say, but I rarely drive myself, and I just use the sound system as it was sold to me without ever thinking that there is such a thing as tuning the sound system. However, after watching the video, I'm now quite ambitious and plan to adjust my own sound system, after all, listening to music while driving is quite a pleasure.

这可能是最奇怪的一项全球比赛，但它让人重新认识了 Excel。很多人看到新闻说“清华博士后拿了 Excel 世界锦标赛全球第九名”，第一反应大概都是：
Excel 还有世界锦标赛？这玩意儿还能比？那我是不是也能报名？
等真的点开比赛视频，基本立刻就能把这些想法收回去。
比赛现场是标准的电竞棚：解说、灯光、音乐、观众都有，唯一和普通电竞不一样的，是选手们一个个沉着冷静、表情严肃，像是提前把今晚的周报全写完的人。解说的衣服上印满各种公式，气氛怪得像个玩笑，但比赛内容一点不像玩笑，它就是一场压缩到 30 分钟的极限数据处理考试。
规则很简单：每轮发一份 Excel 文件，里面几十道题，分成好几个等级。有的算成本，有的算效率，有的算资源分布，有的还隐含着复杂的依赖关系。
选手要做的，就是在时间耗尽前，把这些题尽可能做对。而所谓电竞，在观众视角里其实只有一件事能看懂，比分跳来跳去。你根本不知道选手屏幕里发生了什么，因为画面切换得太快，题目又不会展示出来。
唯一能完整看到操作过程的，是现场观众，因为每个选手的屏幕都会投影在座位前的显示器上，那甚至可能是这场比赛门票最有价值的地方。
今年比赛放出的免费题目来自 EVE Online，那是一款长期被戏称“玩 Excel 的太空 MMO”。题目内容从挖矿开始，一路延伸到造船成本、市场价格波动、矿物消耗结构、行星资源分布……很多人看得都云里雾里，我也是，事后才发现这套题根本不是考 Excel，更像是给你一个小型宇宙经济系统，让你用 Excel 去推运行星和飞船背后的公式。
真正难的地方并不是公式本身，而是速度和稳定度，还有编程。
题目数量多，但逻辑相似，你必须在很短时间里做出一个可以复用的数据模型，否则靠手工哪怕敲快一点，你都来不及。
于是比赛真正比的是，谁能在极短时间里，把结构看清楚，把关系梳理干净，把模型搭对，然后让整张表在不同参数下自动跑通。
如果只是 VLOOKUP、SUMIF 那些函数，根本不够用。比赛里大量使用 XLOOKUP、FILTER、LET、LAMBDA、SUMPRODUCT 等新函数。没见过或没用熟，几乎不可能跟得上节奏。
还有些题目连数据本身都不是正常的，比如用背景颜色来区分舰船类型，这在实际工作中属于反面教材，但比赛里你得临时想办法把颜色变成文字，再拿去跟别的表匹配。
犯不着说难，它就是烦，而且必须解。
在这种环境下，清华博士后拿了全球第 9 名，意义其实非常明确。他展现的不是会多少函数，而是那种工程化处理数据的能力，面对杂乱无序的表格能迅速看见结构，面对复杂依赖关系能马上抽象出可复用的模型，面对几十道题能保证稳定、不出错、不慌乱。
比的是思维整理能力、复杂逻辑拆解能力、再加一点比赛节奏下的抗压能力。
这项成绩说明国内在数据处理、系统建模、工程思维这些方面的基本功强得很稳。
Excel 在这里不再是一个办公软件，而是一个可以在短时间里搭建小型模型的轻量工具，而选手在做的其实是用 Excel 建一个微型系统。
网上总有人把 Excel 能力调侃成熟练使用，像是任何简历都能往里塞的一句套话，以后估计也不敢在简历上写自己会用这个了。看过比赛之后就会明白，“熟练”这两个字的含金量其实极高，它不是会几个函数，也不是能做点漂亮的图表，而是：
手里接到一堆数据
能马上看出应该怎么拆
知道公式该怎么串
能把几十行逻辑跑成一套稳定的模型
并且能在压力下不犯错
这种能力在公司里做分析、做供应链、做模型、做运营预测都通用，而在比赛里被压缩到 30 分钟，也许正是它最真实的强度。
而这种思维，是最可贵的，它能触类旁通，解决一些人们在现实生活中遇到的问题，也从另一方面说明了懂数学的程序员的可贵和厉害之处。
这个世界的一切，都需要逻辑。

Today I went to the cinema and the seating rate was okay, about half. The audience's reaction was somewhat unified: there were laughs in the first half, but it was completely silent in the second half. This kind of viewing experience is very familiar; viewers who have seen 'I Am Not Wang Mao' and 'Killing' will find the atmosphere very similar, not the kind of howling tragedy, but rather a gradual pressure that lowers your emotions to the point where you don't really want to speak. This reminds me of 'My Squad Leader, My Squad.'
This time, the combination of Kong Sheng and Lan Xiao Long is not about grand narratives, nor is it filled with gore, but rather tells a story of an ordinary person forced to grow up by war. I saw some viewers say that after watching this film, they felt a bit stifled; it wasn't that it was hard to watch, but it was heavy.
The film's emotional trajectory is quite clear: the beginning is a bit lighthearted, with life anecdotes and moments for the audience to catch their breath; in the second half, the characters start to rush into desperate situations, and the cinema's atmosphere becomes increasingly tense. It’s not because the visuals are brutal, but because the characters are incredibly ordinary, and the more you watch, the guiltier you feel, because you know that in such moments, ordinary people are the easiest to be trampled by history.
In this respect, it is very much like 'Squad Leader'; the characters don't have a sense of responsibility from the outset but gradually toughen up under pressure. The toughness isn’t the kind of climactic intensity, but rather a resigned acceptance of 'Well, we’ve come this far.' In the end, they fight because they have nowhere to live and nowhere to retreat; this motivation resembles the logic of awakening forced upon the characters in Lan Xiao Long's works. Friends who are used to genre films might not be too fond of this style.
I went with a few friends, and the shot we discussed the most afterward was the immobile goat after the shipwreck. The goat stood on the floating debris, completely still, not even its eyes moved. At that moment, many people couldn't laugh; they just felt it was strange but couldn’t articulate what was strange about it. This absurd yet solid feeling has appeared in 'Killing' and 'Wang Mao,' just with different usages.
The absurdity in 'Killing' is directly presented to the audience, exaggerated, dark, and putting the ridiculous on display.
'I Am Not Wang Mao' wraps emotions in absurdity, making you laugh while already knowing it will be painful later.
'Get Free and Create' is more restrained, not deliberately selling its oddity but suddenly presenting you with an object or behavior that defies logic, making your heart skip a beat.
This type of handling has a common point; it doesn’t rely on dialogue explanations but on your own thoughts.
The goat appears meaningless, but it makes people pause, pulling the audience out of the action scenes, reminding you that there are many things in war that you cannot explain.
It’s not poetic, not symbolic, just an uncomfortable strangeness.
The character traits in these four works are quite similar: none are natural heroes.
Wang Mao in 'Wang Mao' is timid and peculiar, and in the end, he acts not out of ideals but is pushed out by a pile of realities; Niu Jieshi in 'Killing' is a typical local person hijacked by the group; as for 'Squad Leader,' it goes without saying, everyone is a chaotic person, forcibly twisted into a single force by war.
The characters in 'Get Free and Create' are the same: they avoid movement when possible, hiding when they can; they act because if they don’t, they will die. The so-called 'awakening' is actually a lack of choice. This is a common aesthetic point among several works—ordinary people do not suddenly become great, but are pushed to the edge of a cliff by the times, retreating step by step until there is no way out.
This is closer to reality than heroism and makes it easier for the audience to feel discomfort.
'Squad Leader' is the kind of work that leaves your heart feeling as if someone has sat on it, very heavy pressure. 'Get Free and Create' also exerts pressure, but is relatively gentle: it doesn’t have overwhelming tragic scenes, no mountains of corpses or seas of blood, nor does it repeatedly emphasize the cruelty of fate. The director even deliberately softens some images to make the film more palatable.
Yet even so, the audience generally reflects that 'the second half is dead silent.' I think it may not be caused by the visuals but by the logic: you watch a group of people who are not prepared at all, desperately trying to squeeze into the teeth of war, and you feel nervous for them.
Compared to 'Squad Leader,' the brutality in this film isn’t about scale, but rather the knowledge that they shouldn’t be here. Their state is more like 'Wang Mao,' people passively moving forward in an absurd world.
Xiao Zhan's performance is decent; I started to like him a bit from 'Tibetan Sea Legend.' His entire acting style is restrained and not overly posed, expressing emotions through means other than just his face, which adds a lot to his impression score.
Peng Yuchang returns to the type of role he is most comfortable with, making it very easy to watch.
Other characters are quite natural, without traces of 'playing the victim or deliberately heroizing.'
Like 'Killing,' 'I Am Not Wang Mao,' and 'Squad Leader,' 'Get Free and Create' is also telling a simple truth: war does not turn people into heroes; it only forces them to toughen up.
Why do these works have similar styles?
I think it may be because the brutality of real war often lacks poetic expression, presenting it plainly. Some find it absurd, while others find it haphazard, but this style indeed resonates with people.

T800 那个机器人真有意思，和老板 pk 上了，动作幅度还挺连贯，看来又有新突破了

The AI agent's physical hardware aspect has been rushed a bit; the current technological ethics issues have not yet been resolved.
The main concern is not the profit-sharing situation among various apps, but rather the top-level security permissions of financial and banking software based on systems.
However, there is now the first company that is testing the boundaries, waiting for the storm.

OpenAI has currently abandoned its advertising business and is fully focused on competing fiercely with Google's Gemini. Three years ago, ChatGPT emerged and triggered a red alert for Google, but three years later, that alert exploded in OpenAI's own home. The growth of ChatGPT has begun to falter, while Google's counterattack from Gemini has truly struck a painful blow for the first time.
The beginning of this incident was an internal memo that leaked. In the letter, Sam Altman used terminology never before used: "We are at a critical moment for ChatGPT." For a company valued at hundreds of billions, once considered the top ecological niche in AI, this statement carries weight equivalent to a final battle. From that moment on, OpenAI paused its advertising business, hit the pause button on its agent project, and even temporarily abandoned its planned news aggregation product Pulse, with the entire company focusing on one thing: making ChatGPT significantly better, aiming to completely surpass its competitors.
To understand why OpenAI is so anxious, one must first recognize what Google has done right this time. In past years, Google's model release events always felt like “another new model that is about to change the world,” but the next day, the hype faded, and everything returned to normal. However, the combination of Gemini 3 and Nano Banana Pro has changed this situation for the first time. Users' real experiences tell everyone that Google's offerings not only have impressive scores but also provide smooth, interesting, and fast usage, even outperforming GPT-4o in some tasks.
This indicates that for the first time, if someone unsubscribes from ChatGPT Plus, it is no longer out of curiosity, but because they genuinely find the alternative better. This has indeed been the case, as statistics from foreign media show that Gemini's monthly active users surged from 450 million in the summer to 650 million, while ChatGPT's daily active users declined by 6% after the release of Gemini 3. For a company dependent on subscription revenue, this number, while not fatal, is enough to keep the executives awake at night.
OpenAI's anxiety did not emerge suddenly, but stems from the practical difficulties they encountered in large model pre-training over the past year. The core of all large models is pre-training, and after GPT-4o, OpenAI has consistently struggled to break through the training bottleneck of the next generation model. Because of this, they have focused their efforts on reasoning models in recent months, which are small models skilled in mathematics and logic, but these models fail to deliver a significant improvement in user experience.
In simple terms, they are useful but not enjoyable enough.
At this critical juncture, Google has precisely resolved its pre-training challenges, leading to a comprehensive improvement in performance, speed, and experience with Gemini 3, effectively breaking OpenAI's monopoly advantage in user experience. This counterattack is not just theoretical but is directly reflected in user interactions, social circles, and product experiences. OpenAI must respond, or the growth curve of ChatGPT will continue to decline.
In this context, the frequently mentioned new model “Garlic” becomes particularly important. Foreign media reports that this is OpenAI's next-generation model optimized from scratch to fix structural issues in GPT-4.5, with higher efficiency, stronger reasoning, and smoother training. Internal testing shows it has already surpassed Gemini 3 in multiple tasks, and there is a larger version currently in training. If all goes well, we could see GPT-5.2 or GPT-5.5 by early next year. This is the true trump card OpenAI holds in a state of emergency.
While it sounds exciting from the outside, pulling back the perspective reveals that this situation signifies a new phase for the entire industry. Over the past three years, the foreign AI industry has largely been led by OpenAI, with others, including Google and Anthropic, appearing to follow in the dust. Now, OpenAI and Google are standing on the same track for the first time, genuinely competing for users, experience, and ecosystem.
This also complicates the potential IPO of OpenAI.
This competition will force all participants to accelerate their progress. User experience will become smoother, reasoning capabilities will become stronger, and intelligent assistants will resemble thinking individuals rather than just larger calculators. Additionally, there is another significant but easily overlooked change—the focus of AI companies is shifting back from various commercialization attempts to the model itself. Advertising business, agent applications, news recommendations, these are no longer the core battleground; model capabilities are.
In the coming years, the landscape of the AI industry may increasingly resemble the historical competition between Apple and Android. Not because other companies are incapable, but because the threshold for this large model war is incredibly high; only a handful of companies can bear the training costs, create integrated end-to-end capabilities, and turn models into real operating systems.
The current trend is clear: OpenAI and Google are becoming the new dual oligopoly overseas, unlike the domestic situation of widespread competition, but rather entering a dual-hero competition scenario.
For ordinary users, this is good news, as the direct competition between the two giants will ultimately lead to one outcome: stronger, faster, more, and cheaper AI.
The next few months will be the most exciting, intense, and stimulating phase for the entire industry. For both OpenAI and Google, this war has only just begun.

最近流感挺厉害，各位多多注意防护！

In Tongzhou, Beijing, there is a delivery rider named Chen Wenlin, who is the typical kind of person you think is just delivering a cake, but actually saves an entire building in the process.
The story is quite mundane. One afternoon, he delivered a cake upstairs and was about to leave the elevator when he smelled something unusual. To be honest, the smell in the community elevator is not news, but the more he thought about it, the more he felt something was off: 'Where could there be the smell of a gas can in the city?' So he turned back, knocked on the door of the household he just delivered to, and reminded them, even forgetting to go downstairs himself, starting to knock on doors one by one to see if anyone needed to evacuate early.
In such situations, many people's first reaction is to keep their distance for self-preservation, but he first confirmed that others were fine before leaving. This isn't heroism; it's just a simple instinct. Since he saw it, he did what he could to avoid regrets.
He coordinated with the property management, called the police, and involved the fire department. After the danger was eliminated, he quietly left. Until the platform searched everywhere for people to find him, awarding him the title of 'Pioneer Rider' and a bonus of 2000 yuan.
Delivery riders are the most underestimated grassroots contacts in contemporary cities. They navigate the gaps in a city, detecting the smell of gas, hearing arguments, noticing someone falling in the hallway, seeing electric bikes on fire, and discovering children running around alone earlier than anyone else. Whatever you can think of, they have encountered; and sometimes, the things you wouldn't think of, they know even earlier.
It's not because they are inherently braver, but because they move fast, frequently, and close to the lives of ordinary people in the city. Delivery routes are not just routes; they are a form of dense human contact. Over time, a particular social knowledge has formed: where leaks are likely, which building's elevator is always broken, where there are elderly people living alone in the community, and where to avoid walking at night.
And this knowledge can save lives at critical moments.
The industry of delivery is often discussed in terms of 'speed', 'negative reviews', 'systems', and 'livelihoods', but few realize that a portion of daily urban safety actually relies on these riders who appear between buildings at any moment. They are not obligated to step in and handle these matters, yet they often stand up in the first second when no one else reacts.
Chen Wenlin is one who has been seen, but to be honest, this kind of thing may happen every day, yet many go unnoticed.
So, this is not only a praise for one person's bravery, but also a reminder for us: urban safety relies not just on systems and equipment, but also on those ordinary people who lend a helping hand in everyday life. And those seemingly 'most inconspicuous professions' might be quietly supporting the normal operation of this city every day.
Some people deliver food, but in doing so, they also support the lives of an entire building.

The relationship between AI glasses and mobile phones feels more like "complementary". The mobile phone is like a universal toolbox, able to hold everything; AI glasses are specifically designed for certain scenarios. For example, when driving and wanting navigation, simply looking up with the glasses allows you to see the route, which is much safer than looking down at your phone; when exercising, you can listen to music and keep track of your steps without having to dig into your pockets even when you're sweating. However, in these scenarios, the phone is still quietly working in the background—payments, taking photos, editing, and temporary work.
My colleague does outdoor live broadcasts, and the AI shooting glasses have freed him from using a selfie stick, allowing him to shoot steady footage while running; my dad listens to weather alerts with audio glasses while fishing, eliminating the need to frequently take off his gloves to reach for his phone. These fragmented needs highlight the "weight" of the phone, heavy in your pocket and cumbersome to pull out. The advantage of glasses is their low presence; they are right there when needed, and almost forgotten when not.
Today's AI glasses are more like an extension accessory for the phone, relying on the phone's computing power and internet connectivity, and their functions are mostly subsets of phone functions. This could potentially push phone manufacturers to optimize interactions, such as making phones lighter and thinner in the future, specifically handling complex tasks, while glasses take care of simple matters like answering calls and checking notifications.
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Robert allows every suspended lonely heart to find solace, as long as it still thinks of ways to make you happy beneath the boring diaries of people's ramblings. This might be the anthropological and sociological value of this $7,800. It is strongly recommended to confirm Robert's birthday and then designate that day as "Robert Day"
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GM, Happy Thursday!
The government shutdown is behind us - the earnings season is coming to an end - the market remains stable, while stock performance is weak/internal weakness. The Bitcoin mining industry has taken a large share in the recent rebound, particularly weak...
The market is close to support levels... Hope you all HAGD!

#Bitcoin and #Ethereum charts are very tight on lower time frames...
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Barry clarified his position..
By the way, give me $PLTR $250.
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I am about to start a crowdfunding, these beer prices are too high
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Cheers, brothers, I will keep working hard until the market starts to rise.
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People are becoming healthier, which is a good thing.
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I drank butterbeer at Hogwarts, and I heard it can summon the god of the market and drive the market.
No need to thank me; it's my duty
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Michael Burry is trying to cancel Christmas.
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$SOFI has just set a new historical high point
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