Is This Poker Player Bluffing? The AI Thinks So
Is This Poker Player Bluffing? The AI Thinks So
这位扑克选手在虚张声势吗？AI 认为是的
For serious poker players, the ability to sniff out the “tells” that expose an opponent’s intentions is nearly as important to winning as the cards themselves. 对于严肃的扑克玩家来说，察觉出暴露对手意图的“马脚”（tells）与手中的牌一样，对获胜至关重要。
Many gamblers have made careers out of their ability to decipher the meaning of everything other players do at the table—their conscious movements, their body language, and their subconscious tics, all of which might reveal their strategy—as a method of gaining an edge in this game of incomplete information. 许多赌徒通过解读牌桌上对手的一举一动来建立职业生涯——无论是刻意的动作、肢体语言，还是潜意识的抽动，这些都可能泄露其策略——以此作为在这一信息不完全博弈中获取优势的手段。
It’s understandable, then, that ESPN’s use of a new “AI tells detection” tool during the 2026 World Series of Poker Main Event broadcast stoked some serious debate within the poker community. 因此，ESPN 在 2026 年世界扑克系列赛（WSOP）主赛事转播中使用一种新的“AI 马脚检测”工具，在扑克界引发了激烈的争论，这也就不足为奇了。
The tool began appearing periodically during the first few days of the tournament’s live broadcast in early July. A text overlay displayed various live metrics on a player’s movements, plus a “hand strength model” chart breaking down different possibilities of the type of hand a player might be holding. The tool looks slick, but a viewer might naturally wonder how accurate its data is, or how the AI came to know the players’ tics and gestures well enough to venture such a guess. 该工具在 7 月初锦标赛直播的前几天里断断续续地出现。屏幕上的文字叠加层显示了选手动作的各种实时指标，以及一个“牌力模型”图表，分析了选手可能持有的各种牌型。该工具看起来很酷，但观众难免会怀疑其数据的准确性，或者 AI 是如何如此了解选手的习惯动作和姿态，以至于能做出这样的推测。
Is the tool just a neat party trick—or a silly one, depending on your sensibilities? Or is it an attempt to haphazardly stuff AI into the inherently human pursuit of poker, threatening the game’s soul and future? 这个工具究竟是一个巧妙的“派对戏法”——或者根据你的品味，是一个愚蠢的把戏？还是说，这是一种将 AI 强行塞入扑克这项本质上属于人类博弈的活动中的尝试，从而威胁到这项运动的灵魂与未来？
Do Tell
揭秘“马脚”
Hundreds of pros on the poker circuit specialize in spotting tells. This new tool, designed by an AI engineer for the US Air Force named Luke Geel, purports to digitize that process. It’s watched every hand captured on camera in the 2026 WSOP Main Event to build a tells database on various players. 扑克巡回赛中有数百名职业选手专门擅长捕捉“马脚”。这款由美国空军 AI 工程师卢克·吉尔（Luke Geel）设计的新工具，旨在将这一过程数字化。它观看了 2026 年 WSOP 主赛事中摄像机捕捉到的每一手牌，从而建立起针对不同选手的“马脚”数据库。
The system gathers inputs on the players ranging from eye movements and the rate at which they blink, to the players’ posture, chip handling movements, “hand fidget” metrics, and more. It analyzes that data and the outcomes of each hand to predict the likelihood of which general hand type a player might have: A strong made hand, a drawing hand, a bluff, and so on. 该系统收集选手的输入信息，范围涵盖眼球运动、眨眼频率、坐姿、筹码处理动作、“手部小动作”指标等。它通过分析这些数据以及每一手牌的结果，来预测选手可能持有的牌型概率：是强成手牌、听牌、虚张声势，等等。
The poker experts I spoke to are skeptical about the tool’s effectiveness—especially since it was trained on such a small amount of data. The 2026 edition of the WSOP Main Event tournament drew over 9,000 entries, but the vast majority of those players never spent time at one of three tables that were being recorded by cameras. (The same camera feeds used for the broadcast were also used to train the AI tool). Even those who did sit at those tables weren’t there long enough for the system to build a robust dataset that covers the vast range of situations possible in poker. 我采访的扑克专家对该工具的有效性持怀疑态度——尤其是因为它是在如此少量的数据上训练出来的。2026 年 WSOP 主赛事吸引了超过 9,000 名参赛者，但绝大多数选手从未在摄像机记录的三张牌桌上打过牌。（用于转播的摄像机画面也被用于训练该 AI 工具）。即使是那些坐在这些牌桌上的选手，停留的时间也不足以让系统建立起涵盖扑克中各种复杂情况的稳健数据集。
“The streams are varied enough that you don’t get the same players too frequently,” says Michael Gagliano, a 17-year poker professional who made the Main Event final table this year and is playing for the $10 million top prize this week. “直播流非常分散，你很难频繁看到同一位选手，”拥有 17 年经验的职业扑克选手迈克尔·加利亚诺（Michael Gagliano）说。他今年打进了主赛事决赛桌，本周正在争夺 1000 万美元的头奖。
Gagliano, who started the final in eighth chip position, says he went back through every second of ESPN’s live streams during the two-and-a-half-week break after the final table was reached in mid-July, combing for any tells or info he could pick up on his remaining opponents. But that lack of screen time for any one player limited his ability to spot the tells, even for players who made it all the way to the final table and spent lots of time on camera. 加利亚诺以第八名的筹码量进入决赛，他说在 7 月中旬决赛桌确定后的两周半休息期间，他回看了 ESPN 直播的每一秒，试图搜寻关于剩余对手的任何“马脚”或信息。但由于每位选手在镜头前的时间太少，限制了他捕捉“马脚”的能力，即使是对那些一路打进决赛桌、在镜头前花费了大量时间的选手也是如此。
“I don’t know how much actual information I’m going to be able to act on from what I saw,” he says. Any AI looking at the footage would face the same issue, even for a tournament as long as the Main Event. “我不知道从我看到的内容中能提取多少实际有用的信息，”他说。任何观看这些录像的 AI 都会面临同样的问题，即使是像主赛事这样漫长的锦标赛也不例外。
More Than Just Cookies
不仅仅是奥利奥
Tell detection is nuanced work, and pros are dubious that a camera-based AI tool can effectively do it better than a human. “马脚”检测是一项微妙的工作，职业选手们怀疑基于摄像头的 AI 工具能否比人类更有效地完成这项任务。
Most nonplayers’ exposure to the importance of poker tells comes from the penultimate scene in the 1998 film Rounders. Matt Damon’s character, Mike McDermott, folds a monster hand to John Malkovich’s Teddy KGB after recognizing that the gangster has him beat—and McDermott discovers this after spotting a tell based on KGB’s habit of eating Oreos at the table. It’s arguably the most memorable poker scene in movie history because it perfectly expresses the battle of wits that underlies every poker game, even though in reality it’s quite reductive. 大多数非玩家对扑克“马脚”重要性的认知，源于 1998 年电影《赌王之王》（Rounders）的倒数第二幕。马特·达蒙饰演的迈克·麦克德莫特在意识到对手泰迪·克格勃（约翰·马尔科维奇饰）胜券在握后，弃掉了一手好牌——而麦克德莫特发现这一点，是因为他捕捉到了克格勃在牌桌上吃奥利奥饼干的习惯。这可以说是电影史上最令人难忘的扑克场景，因为它完美地表达了每一场扑克游戏背后的智力博弈，尽管在现实中这被大大简化了。
“To reference the Rounders Oreo cookie tell, it’s a little more abstract than that,” says Shaun Deeb, a two-time winner of the WSOP Player of the Year award and one of the most recognizable players in the game. (Deeb also made a deep run in the 2026 Main Event, finishing 15th.) “如果参考《赌王之王》里的奥利奥饼干‘马脚’，现实情况要比那抽象得多，”两届 WSOP 年度最佳选手奖得主、扑克界最具辨识度的选手之一肖恩·迪布（Shaun Deeb）说。（迪布在 2026 年主赛事中也表现出色，最终获得第 15 名。）
“Physical tells are so much more expansive than I think the public realizes,” Deeb says. “There are leg tells, checking tells, verbal tells, breathing tells, pulse tells. There’s an insane amount of tells available, and most of those can’t be picked up by a camera.” “肢体‘马脚’比公众想象的要广泛得多，”迪布说。“有腿部动作、过牌动作、言语、呼吸、脉搏等‘马脚’。有无数种可能的‘马脚’，而其中大多数是摄像机无法捕捉到的。”
An AI can track visual and audio patterns, but it can’t deduce intention; the former is only so valuable without the latter. Even if the tool was hypothetically perfect at determining when a player was projecting confidence or weakness, that alone isn’t a road map to deciphering their actual hand. AI 可以追踪视觉和音频模式，但它无法推断意图；没有后者，前者价值有限。即使该工具在判断选手何时表现出自信或虚弱方面达到了完美的程度，这本身也不是解读他们实际手牌的路线图。
“How strong is two pair to one player versus another player?” says Gagliano. “Maybe someone is extra confident with a hand that’s actually weak for the situation, but for some reason they think they have the best hand, so they’re really confident. Maybe if I was playing a casual tournament, I would think my two pair is extremely strong. But in the Main Event I’m still a little nervous, because it’s a high-stakes situation. So maybe my body language is referencing the situation rather than the hand strength.” “对于不同的选手，两对（Two Pair）的牌力强弱定义是一样的吗？”加利亚诺说。“也许有人对一手在当前局势下其实很弱的牌表现得格外自信，但出于某种原因，他们认为自己拿到了最好的牌，所以表现得很自信。也许如果我是在打一场休闲锦标赛，我会觉得我的两对非常强。但在主赛事中，我仍然会有点紧张，因为这是高风险的局面。所以，我的肢体语言可能是在反映当前局势，而不是手牌的强弱。”
For a broadcast entertainment tool, those flaws aren’t necessarily a deal-breaker. No one is expecting some all-knowing oracle—Geel, the tool’s creator, least of all. He’s transparent about the fact that a larger sample of hands would be better for his tool, telling WIRED via email that he’s run some blind tests on other poker competitions with mixed results. 对于一个广播娱乐工具来说，这些缺陷并不一定是致命的。没有人指望它成为全知全能的先知——该工具的创造者吉尔本人更是如此。他坦诚地表示，更大的样本量对他的工具会更有利，并通过电子邮件告诉《连线》（WIRED）杂志，他在其他扑克比赛中进行了一些盲测，结果好坏参半。