Three ways AI is changing the 2024 Olympics for athletes and fans
人工智能正在为运动员和球迷改变2024年奥运会的三种方式
When more than 10,000 athletes from around 200 countries gather in Paris for the 2024 Summer Olympic Games this week, they will have an all-new friendly — but faceless — voice to greet and guide them.
本周，当来自约200个国家的1万多名运动员齐聚巴黎参加2024年夏季奥运会时，他们将有一个全新的、友好但不露面的声音来迎接和引导他们。
How do I reach my sporting venue? Can I livestream the opening ceremony? Will there be a computer refereeing my games? Where can I get freebies from sponsors?
如何到达我的体育场馆？我可以直播开幕式吗？我的比赛会有电脑裁判吗？我在哪里可以得到赞助商的赠品？
These are just some of the questions that athletes will be able to ask AthleteGPT, an artificial intelligence (AI) chatbot designed for them, accessible through the Athlete365 mobile app. It’ll be able to scour through “thousands of information pages very quickly, and be available 24/7 to answer questions”, says Todd Harple, the Olympics AI Innovation programme lead at Intel Labs in Hillsboro, Oregon, who is involved with the effort.
这些只是运动员可以向AthleteGPT提出的一些问题。AthleteGPT是为运动员设计的人工智能聊天机器人，可以通过Athlete365移动的应用程序访问。它将能够快速浏览“数千个信息页面，并全天候回答问题”，俄勒冈州希尔斯伯勒英特尔实验室奥运会人工智能创新项目负责人托德哈普尔说。谁参与了这项工作。
The chatbot — a large language model (LLM) built using an AI developed by Paris-based company Mistral AI and Intel’s Gaudi processors — is just one way in which AI is leaving its imprint on this year’s Olympics, which begin on 26 July. Few would have been familiar with LLMs or heard of ChatGPT during the last summer games, in Tokyo in 2021. But sprinters in Paris can only hope to match the strides that AI technologies have made since.
聊天机器人是一种大型语言模型（LLM），使用巴黎公司Mistral AI开发的人工智能和英特尔的高迪处理器构建，这只是人工智能在今年7月26日开始的奥运会上留下印记的一种方式。在2021年东京举行的上届夏季奥运会上，很少有人熟悉LLMs或听说过ChatGPT。但巴黎的短跑运动员只能希望能赶上人工智能技术自那时以来所取得的进步。
The International Olympics Committee (IOC) is embracing the technology. In April, it rolled out its AI agenda — an effort to streamline the explosive growth of AI research in sport and to strategize its use in the Olympics. “We have to be leaders of change, and not the object of change,” said Thomas Bach, the president of the IOC in Lausanne, Switzerland, at a press event in London, which showcased the capabilities of various AI sports tools.
国际奥委会（IOC）正在接受这项技术。今年4月，它推出了人工智能议程-努力简化人工智能研究在体育领域的爆炸性增长，并制定其在奥运会上的使用战略。瑞士洛桑国际奥委会主席托马斯·巴赫在伦敦举行的新闻发布会上表示：“我们必须成为变革的领导者，而不是变革的对象。”各种人工智能体育工具的功能。
Nature explores three ways in which AI is changing how athletes and spectators will experience the Olympic Games.
《自然》探讨了人工智能改变运动员和观众体验奥运会的三种方式。
Athlete performance and training
运动员的表现和训练
As early as 1900, when Paris first hosted the Olympic Games, French scientist Étienne-Jules Marey was pioneering the use of technology to study athletes in motion. His high-speed chronophotography — which involved rigging a camera like a machine gun, feeding it photographic plates like ammunition to rapidly capture frames — snapped sprinters and long-jumpers. He analysed the body’s biomechanics to “discover the secret of superiority of certain athletes”, a Nature editorial commented in 1901.
早在1900年，当巴黎首次举办奥运会时，法国科学家Étienne-Jules Marey就率先使用技术来研究运动员的运动。他的高速计时摄影术–包括像机关枪一样操纵一台相机，像弹药一样喂给它感光板来快速捕捉画面–给短跑运动员和跳远运动员拍照。1901年，《自然》杂志的一篇社论评论说，他分析了身体的生物力学，“发现了某些运动员优越的秘密”。
Today, it is possible to do much more just by recording with a smartphone. Intel’s 3D athlete tracking (3DAT) technology uses AI to track 21 points across the human body to render its precise physical movement, providing “all the biomechanical insights that coaches look for” in elite athletes, Harple says. He thinks that such technologies will lead to closer competition and new records.
今天，仅仅通过智能手机记录就可以做更多的事情。英特尔的3D运动员跟踪（3DAT）技术使用人工智能来跟踪人体的21个点，以呈现其精确的身体运动，提供“教练在精英运动员身上寻找的所有生物力学见解”，Harple说。他认为，这些技术将导致更紧密的竞争和新的记录。
The ways in which AI is being used to enhance athletes’ performance range from designing custom-built athletic shoes and clothing to determining optimum nutrition and training schedules. “It may even accelerate our discovery of new strategies of playing sports,” he says. A historic example of such a fundamental change is the Fosbury flop — now the dominant style of high jump, and pioneered by US athlete Dick Fosbury at the 1968 Olympics.
人工智能用于提高运动员成绩的方式从设计定制运动鞋和服装到确定最佳营养和训练计划。他说：“这甚至可能加速我们发现新的体育运动策略。”这种根本性变化的一个历史性例子是背越式跳高-现在是跳高的主导风格，由美国运动员迪克·福斯伯里在1968年奥运会上开创。
捕捉运动的照片和视频并分析数据是运动员可以通过人工智能提高成绩的一种方式。
The ease of collecting individual data, combined with AI analysis, could also help coaches to identify talent, making sports more equitable. In March, the IOC piloted a scouting programme that used 3DAT to identify more than 40 children in Senegal who showed promise in becoming Olympic athletes, by analysing simple drills such as running and jumping.
收集个人数据的便利性，结合人工智能分析，也可以帮助教练识别人才，使体育运动更加公平。今年3月，国际奥委会试行了一项童子军计划，利用3DAT技术，通过分析跑步和跳跃等简单训练，确定了塞内加尔40多名有望成为奥运会运动员的儿童。
But sports and nations with big professional leagues will retain a big advantage, because they have the resources to gather high-quality data, and to train algorithms with them. “The problem with some of the Olympic sports is that there is not a big footprint of data,” says Patrick Lucey, chief scientist at the sports-technology company Stats Perform in Chicago, Illinois. This extends how the technology can be used in other aspects of these games, such as judging and officiating.
但拥有大型职业联赛的体育运动和国家将保持很大的优势，因为他们有资源收集高质量的数据，并用这些数据训练算法。伊利诺斯州芝加哥的体育技术公司Stats Perform的首席科学家帕特里克·露西说：“一些奥运项目的问题是没有大量的数据。”这扩展了该技术如何用于这些游戏的其他方面，例如裁判和裁判。
Refereeing and real-time data
裁判和实时数据
Olympics water polo referee Frank Ohme is no stranger to AI. His day job as an astrophysicist at the Max Planck Institute for Gravitational Physics in Heidelberg, Germany, involves hunting for signals of colliding black holes — sometimes with AI’s help — in noisy gravitational-wave data. But when he dons the all-white referee uniform in Paris, he’ll need to peer through splashing water waves to decide whether the ball has crossed the line into the goal.
奥运会波罗裁判Frank Ohme对AI并不陌生。他的日常工作是德国海德堡马克斯普朗克引力物理研究所的天体物理学家，包括在嘈杂的引力波数据中寻找碰撞黑洞的信号-有时在人工智能的帮助下。但是当他在巴黎穿上全白的裁判制服时，他需要透过飞溅的水波来判断球是否越过了球门线。
AI is already informing such decisions in sports including football, using information recorded by an array of cameras around the stadium and chips implanted in the ball. But it’s yet to catch on in other sports — and AI will probably be slower to pervade areas such as refereeing, which requires real-time data analysis.
人工智能已经在包括足球在内的体育运动中告知这些决定，使用体育场周围的一系列摄像头记录的信息和植入球中的芯片。但它还没有在其他体育运动中流行起来-人工智能可能会更慢地渗透到裁判等需要实时数据分析的领域。
Another hurdle is funding, and the specific needs of each sport — there will be 32 events at the Paris games. Despite water polo being the oldest Olympic team sport, there’s not nearly as much money in it as there is in basketball or football, says Ohme. Using AI in water polo would also present different challenges, such as training algorithms on images taken under water and in chaotic scenarios, he adds.
另一个障碍是资金，以及每项运动的具体需求–巴黎奥运会将有32个项目。奥姆说，尽管波罗是最古老的奥运会团体运动，但它的收入远不如篮球或足球。他补充说，在波罗中使用人工智能也会带来不同的挑战，例如在水下和混乱场景中拍摄的图像上训练算法。
Precise and open communication is key whenever AI assistance is used to make calls in real time. “The easiest way to convince teams and spectators is to give them all the information through an image or visualization where they can determine [the call] themselves,” Ohme says.
无论何时使用人工智能协助进行真实的呼叫，精确和开放的沟通都是关键。“说服球队和观众的最简单方法是通过图像或可视化方式向他们提供所有信息，让他们自己确定[呼叫]，”Ohme说。
It’s also hard to remove ambiguity in actions such as fouls in contact sports. These are split-second decisions that not even all humans can agree on. “I wouldn’t even know how to start putting those into numbers,” says Ohme, who thinks that detecting black holes is an easier task for AI in comparison.
在接触性运动中，也很难消除诸如犯规等行为的模糊性。这些都是瞬间的决定，甚至不是所有的人类都能达成一致。“我甚至不知道如何开始把这些数字，”Ohme说，他认为相比之下，探测黑洞对人工智能来说是一项更容易的任务。
Enhancing viewer experience
增强观众体验
The torrents of data collected during the games will feed not only AI algorithms, but also television viewers hungry for statistics. “Sport is its own language. It crosses barriers to help everyone communicate,” Lucey says. Statistics and numbers enrich these conversations by providing extra benchmarks for comparison. “Of course people want that,” he adds.
在奥运会期间收集的大量数据不仅将为人工智能算法提供支持，还将为渴望获得统计数据的电视观众提供支持。“体育是自己的语言。它跨越障碍，帮助每个人沟通，”露西说。统计数据和数字通过提供额外的比较基准丰富了这些对话。“人们当然希望这样，”他补充道。
Broadcasters are rushing to find ways to augment this new wealth of information and put it onto television screens. Viewers were enthralled when the virtual world-record line was superimposed onto the screen for television viewers during the Sydney 2000 games. In 2024, broadcasters have the ability to display much more, such as acceleration, top speeds and stride lengths, says Harple.
广播公司正急于寻找方法来增加这一新的信息财富，并把它放在电视屏幕上。在2000年悉尼奥运会期间，当虚拟的世界纪录线叠加在电视观众的屏幕上时，观众们都被迷住了。Harple说，到2024年，广播公司有能力显示更多信息，如加速度、最高速度和步幅。
What excites Harple most is the prospect of personalized highlights made available to viewers through Intel’s Geti computer-vision AI platform, which could be a feature of future broadcasts. With so much sporting action being recorded simultaneously, Harple says that the ability of AI to pick out exactly what viewers want to see will be a game-changer. This could be particularly beneficial for coaches and broadcasters from nations that have more limited access to production resources. “If someone wants every three-point shot made by the Nigerian men’s basketball team, AI can go through all the footage and automatically put them together,” he says.
最让Harple兴奋的是通过英特尔的Geti计算机视觉AI平台为观众提供个性化亮点的前景，这可能是未来广播的一个特点。由于同时记录了如此多的体育动作，Harple表示，人工智能准确挑选观众想要看到的内容的能力将改变游戏规则。这对于那些获得制作资源的机会有限的国家的教练和广播员来说尤其有利。“如果有人想要尼日利亚男子篮球队的每一个三分球，人工智能可以浏览所有的镜头并自动将它们放在一起，”他说。