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亚马逊 Prime Video 使用人工智能为原创剧集制作视频回顾

亚马逊在 Prime Video 上推出了 Video Recaps，为美国精选英语原创剧集提供“全面季回顾”，利用人工智能创建具有同步语音旁白、对话片段和音乐的影院品质视频摘要。该功能最初在联网电视设备上提供，旨在让观众在观看《全面瓦解》、《汤姆·克兰西的杰克·瑞恩》等新剧集之前了解最新情况。这标志着生成式人工智能在流媒体服务中的重要应用。优质视频

元股票下滑加深。这是另一个值得关注的人工智能成本。

投资者商业日报 (IBD) 提供的信息内容仅用于教育目的，不得解释为投资建议或买卖证券的建议。数据来自可靠的提供商，但不保证准确性和及时性。作者可能持有他们讨论的股票。IBD 不保证所讨论的任何投资策略的成功。实时价格来自纳斯达克最新交易；所有权和估计数据分别来自 LSEG 和 FactSet。投资者商业日报有限责任公司 2025 保留所有权利。

在最近的 Windows AI 强烈反对之后，微软 AI 首席执行官对批评者进行了反击——“人们不为所动的事实......令我震惊”

微软 AI 首席执行官 Mustafa Suleyman 通过淡化对 AI 功能的担忧来回应用户对 Copilot 和 Windows AI 的批评。在 X 上的一篇帖子中，他对人们对先进人工智能能力的怀疑表示惊讶。与此同时，微软为 Windows 推出了新的“你的人工智能画布”口号，旨在将其发展成为由人工智能代理支持的代理操作系统。然而，鉴于 Windows 平台持续存在的问题以及缺乏对广泛人工智能集成的需求，许多用户认为对人工智能的关注是错误的。苏莱曼的立场并没有解决用户的担忧，鉴于客户对其以人工智能为中心的方法的强烈反对，人们对微软的未来方向提出了质疑。

This Home Robot Clears Tables and Loads the Dishwasher All by Itself Memo, a home robot by Sunday Robotics, impressively prepares espresso in an open-plan kitchen, showcasing its ability to identify objects and use them correctly despite the complexity of real-world environments. CEO Tony Zhao aims for Memo to handle chores like laundry and dishes by integrating hardware and AI training自主研发的模型。尽管目前机器人仍面临适应复杂家庭环境的挑战，Memo参与了洗碗和清理桌面等任务，并展示了抓取两个杯子的独特技巧。通过让远程工人佩戴类似Memo的手套进行家务劳动来收集训练数据是Sunday的关键创新之一。此外，来自Conviction的Sarah Guo和其他投资者看好Memo的实用性和发展潜力，认为它标志着家用机器人时代即将到来。 Memo may not be the world’s fastest barista, but it is impressive—for a robot. I recently watched as Memo, a new home robot from a company called Sunday Robotics, made coffee in an open-plan kitchen in Mountain View, California. Memo looks like something out of Wall-E, with a gleaming white body, two arms, a friendly cartoonish face, and a red baseball cap. Rather than using legs as a fully humanoid robot would, Memo moves around using a wheeled platform and changes its height by sliding up and down a central column atop that platform. The robot responded to a request for an espresso by rolling over to a countertop, and then using two pincerlike hands to slowly go through each step required to operate an espresso machine. It filled the porta filter with coffee grounds, tamped them down, slotted the porta filter into place and put a coffee cup below, pressed the buttons needed to start the machine, and finally retrieved the hot drink. “We want to build robots that free people from laundry, from the dishes, from all chores,” Tony Zhao, cofounder and CEO of Sunday Robotics, told me as the robot brought the coffee over to the person who requested it. Making a cup of espresso might not seem spectacular, but the feat is ridiculously hard for a robot to do in a real, messy kitchen. It requires the ability to identify different objects, figure out how to grasp them reliably, and use those objects properly. Sunday is not only building its own hardware but also training the models that allow its system to learn. “We think the way to make a home robot is to be full-stack, and to vertically integrate,” Zhao says. “And that’s a very ambitious thing to do.” Courtesy of Sunday Robotics Today most robots still do precise, repetitive work in tightly controlled environments; for example, moving the same item from one position to another over and over again. Unlike humans, industrial robots cannot typically adapt or improvise to changes or unfamiliar situations. The last decade has seen some companies build robots that use AI to do simple things, like identify objects on a conveyor belt and decide how to grasp them. This is, however, far less complex than operating in an environment as varied and messy as a real home. Of course, robot demos are not always a good indicator of how useful a robot will be. The real question is how well Memo can perform tasks in a wide variety of homes without Sunday’s engineers nearby. Even so, the robot has some skills. Besides making coffee, I watched Memo clear glasses from a table and load them into a dishwasher. This feat was especially impressive because it involved figuring out how to grasp two glasses in the same hand. Memo held one glass between its thumb and pointer finger, and used the rest of its hand to grab the second. This kind of dexterity relies on Sunday’s key innovation: a novel way of training robots that delivers more humanlike dexterity. Sunday pays remote workers to use gloves resembling Memo’s hands to do household chores. Zhao says the gloves, which cost roughly $400 a pair, provide a more accurate training signal than teleoperation, which is the standard way for a person to control a robot. The training data gathered from glove-wearing workers is fed into an AI model that takes input from the robot’s sensors and controls its motions. “This is a very exciting variant on home robots,” says Ken Goldberg , a roboticist at UC Berkeley and the cofounder of Ambi Robotics . “It’s a beautiful design, and a much smarter kind of data capture.” Courtesy of Sunday Robotics The fact that any company thinks it can build a useful and functional home robot is a sign of skyrocketing optimism about progress in robotics—and not without reason. Researchers have shown in the last few years that robots can tap into the capabilities of large language models , the brains behind today’s chatbots, and use them to respond to commands or make sense of a scene. Some researchers hope that gathering large amounts of data that shows how to perform different actions—picking up cups, folding shirts, and so on—will produce a more general kind of robotic intelligence. Zhao and Sunday’s other cofounder and CTO, Cheng Chi, have both contributed advances that have kindled hope of robotic breakthroughs. Zhao worked on a project called Mobile ALOHA at Stanford University that involved training robots using a low-cost mobile teleoperation system. Chi worked on a project from Stanford, Columbia University, and the Toyota Research Institute, that showed how a cheap clawlike device could be used to gather data from humans doing tasks like cleaning dishes. “If you think about the most powerful AIs, ChatGPT or image-generation models,” Zhao says, “they are trained on the whole internet. We just don't have the internet for robotics.” A handful of other startups are currently hustling to develop and deploy more capable robots, including systems designed to work in ordinary homes. Physical Intelligence , Skild , and Generalist are all working on robot models that can adapt to new situations using this approach. 1x recently revealed a humanoid home robot, though this system still requires teleoperation to perform some tasks. Sarah Guo, founder and managing partner of Conviction, says that Sunday, which includes veterans from Tesla and Google DeepMind, is well placed to build both hardware and models. “Tony and Cheng are incredibly good,” she says. “They’ve since recruited and enabled an all-star team that can uniquely do hardware–AI co-design, and deliver a full-stack product.” Eric Vishria, a general partner at venture capital firm Benchmark, which is backing Sunday, said in a statement that the startup’s practical approach is the way to make robots more useful. “The promise of AI robotics isn’t doing a backflip or dancing demos, but robots that work in messy, real-world situations,” Vishria said, adding that Sunday’s “breakthroughs mark the start of an exponential curve toward a future where robots actually work in our day-to-day lives.” Sunday plans to give Memo to beta testers next year. The pilot program will show how people respond to having a home robot that can do certain chores—albeit slowly, and perhaps not perfectly every time. A key question will be how reliably and efficiently Memo is able to do chores in real homes where kids, pets, and mess are guaranteed to complicate the challenge. After beta testing, Zhao says Sunday will roll Memo out to the first users. Just as early home computers were complicated and appealed mostly to enthusiasts, he believes Memo might initially be popular with those who want to live in a robotic future and are willing to tolerate some rough edges. This might even involve users showing their robots how to do something new. “I do think that people should be able to teach their own robots,” Zhao says. Perhaps the era of truly capable home robots is almost upon us. For now though, I’d settle for a decent espresso. Updated 12:23 pm ET, November 19, 2025 to clarify the cost of the gloves used for collecting robotic training data. Updated 1:26 pm ET, November 19, 2025: Added comments from Sarah Guo and additional details about the Sunday team.

超越哈佛大学和麻省理工学院——这所大学可能会赢得人工智能竞赛，但你可能从未听说过它

在全球人工智能主导地位的争夺中，中国正在迅速追赶美国，清华大学大量的人工智能研究论文和专利就证明了这一点。尽管美国在有影响力的人工智能专利和著名的人工智能模型方面仍然处于领先地位，但中国对人工智能的早期教育关注和政府的大力支持已经建立了庞大的科技劳动力队伍，吸引了寻求人才的美国公司。尽管地缘政治紧张，美国主要科技公司越来越多地聘用受过中国教育的人工智能研究人员。

Windows 11唯一有用的新功能与人工智能无关

微软在 Ignite 2025 大会上将日历小部件重新引入 Windows 11 的任务栏，四年前，该小部件已从操作系统中删除。虽然这一新增功能受到怀念 Windows 10 功能的用户的欢迎，但大多数新更新都侧重于在整个操作系统中集成 AI 功能，包括 Copilot，它承诺汇总文档并集成到文件资源管理器和任务栏搜索功能等各种应用程序中。这些变化旨在使 Windows 11 更加“代理”，允许对复杂任务进行后台处理。然而，数据安全性和用户对这些新功能的困惑仍然令人担忧，这可能会促使一些用户转向 Linux 替代品。