
无论是在跑道上奔跑、完成后空翻、随音乐起舞,还是进行踢拳表演,展示人形机器人做出“高难度动作”的视频越来越多,其表现也愈发惊艳。
然而,在上周二举行的《财富》人工智能头脑风暴大会上,多位嘉宾警告称,不要被这些炫目的动作所迷惑。一台机器人完成对人类来说都很难的后空翻,确实足够吸睛。但如果让机器人去做爬楼梯、端杯水这类看似简单的任务,许多当下的机器人仍然很难完成。
红杉资本(Sequoia Capital)合伙人斯蒂芬妮·詹解释说:“看似困难的实则简单,而看似简单的才是真正的难题。”她转述的是计算机科学家汉斯·莫拉维克的一个经典观察。早在上世纪80年代末,莫拉维克和其他计算机科学家就注意到,计算机在智力测试中往往表现出色,却无法完成连幼童都能胜任的任务。
机器人初创公司Skild AI的首席执行官迪帕克·帕塔克解释称,无论是机器人还是计算机,整体而言都擅长在受控环境中执行复杂任务。他在现场展示了一段Skild机器人在人行道上跳跃前行的视频,并强调:“除了地面,这个机器人没有与任何物体发生互动。”
帕塔克指出,在捡瓶子或爬楼梯这样的任务中,人类会依靠视觉对自身行为进行“持续修正”。“这种与环境即时互动的能力,正是人类通用智能的根源所在。我们对此浑然不觉,只是因为几乎每个人都具备这种能力。”
斯蒂芬妮·詹也提醒,网络上走红的人形机器人视频,既未展示产品的训练过程,也未说明其是否能在非受控环境中稳定运行。她表示:“对于这些视频的观看者来说,真正的挑战在于分辨哪些是真实能力,哪些只是表演。”
机器人的未来发展
尽管如此,两位嘉宾都乐观地认为,通用人工智能领域的突破性进展将很快催生出更高级、更灵活的机器人。
帕塔克表示:“过去,机器人高度依赖人类智能驱动。通常先由专家分析某个任务,然后通过数学建模的方式,对机器人进行预编程,让它执行该任务。”
他指出,不过现在机器人领域正经历一场从“依赖编程”到“从经验中学习”的转变。这一转变使新一代机器人能够在更不可控的环境中处理更复杂的任务,并且无需投入成本进行重新编程或改造,即可轻松适配到其他任务。

斯蒂芬妮·詹指出,如今的机器人企业“仍然受限于机器人功能单一的困局”。具备更强通用智能的机器人平台,则能开启“此前我们力所不及的诸多可能”,包括接手目前对人类具有危险性的工作。
消费者同样可能从中受益。斯蒂芬妮·詹表示:“我们现在看到的家用机器人,其实都只能做一件事。但如果我们成功打造出通用智能机器人,届时消费级机器人就能处理各类家务。”在本届人工智能头脑风暴大会早些时候,Arm首席执行官雷内·哈斯也表达了类似观点。他指出,人形机器人的通用适应能力,将使其在工厂场景中比当下使用的机械臂更具优势。
当然,机器人产业的繁荣也将带来社会层面的影响,冲击目前仍需由人类完成的工作岗位。但帕塔克对自动化普及所带来的社会效益持乐观态度。其一是安全性,机器人可以替代人类从事那些长期来看存在危险或损害健康的工作。另一益处则是缓解蓝领和制造业岗位面临的巨大劳动力短缺。(此问题一直是美国推动高端制造业从亚洲回流本土的主要障碍。)
此外,帕塔克还展望了这样一个未来:机器人将人类从繁重、枯燥的日常工作中解放出来。不过他也坦言,社会需要找到合理方式,来分配自动化带来的红利。他表示:“确实存在一个美好的前景,即每个人都可以做自己喜欢的事情。工作更多是出于自愿,人们可以投身自己热爱的事业之中。”(*)
译者:郝秀
审校:汪皓
无论是在跑道上奔跑、完成后空翻、随音乐起舞,还是进行踢拳表演,展示人形机器人做出“高难度动作”的视频越来越多,其表现也愈发惊艳。
然而,在上周二举行的《财富》人工智能头脑风暴大会上,多位嘉宾警告称,不要被这些炫目的动作所迷惑。一台机器人完成对人类来说都很难的后空翻,确实足够吸睛。但如果让机器人去做爬楼梯、端杯水这类看似简单的任务,许多当下的机器人仍然很难完成。
红杉资本(Sequoia Capital)合伙人斯蒂芬妮·詹解释说:“看似困难的实则简单,而看似简单的才是真正的难题。”她转述的是计算机科学家汉斯·莫拉维克的一个经典观察。早在上世纪80年代末,莫拉维克和其他计算机科学家就注意到,计算机在智力测试中往往表现出色,却无法完成连幼童都能胜任的任务。
机器人初创公司Skild AI的首席执行官迪帕克·帕塔克解释称,无论是机器人还是计算机,整体而言都擅长在受控环境中执行复杂任务。他在现场展示了一段Skild机器人在人行道上跳跃前行的视频,并强调:“除了地面,这个机器人没有与任何物体发生互动。”
帕塔克指出,在捡瓶子或爬楼梯这样的任务中,人类会依靠视觉对自身行为进行“持续修正”。“这种与环境即时互动的能力,正是人类通用智能的根源所在。我们对此浑然不觉,只是因为几乎每个人都具备这种能力。”
斯蒂芬妮·詹也提醒,网络上走红的人形机器人视频,既未展示产品的训练过程,也未说明其是否能在非受控环境中稳定运行。她表示:“对于这些视频的观看者来说,真正的挑战在于分辨哪些是真实能力,哪些只是表演。”
机器人的未来发展
尽管如此,两位嘉宾都乐观地认为,通用人工智能领域的突破性进展将很快催生出更高级、更灵活的机器人。
帕塔克表示:“过去,机器人高度依赖人类智能驱动。通常先由专家分析某个任务,然后通过数学建模的方式,对机器人进行预编程,让它执行该任务。”
他指出,不过现在机器人领域正经历一场从“依赖编程”到“从经验中学习”的转变。这一转变使新一代机器人能够在更不可控的环境中处理更复杂的任务,并且无需投入成本进行重新编程或改造,即可轻松适配到其他任务。
斯蒂芬妮·詹指出,如今的机器人企业“仍然受限于机器人功能单一的困局”。具备更强通用智能的机器人平台,则能开启“此前我们力所不及的诸多可能”,包括接手目前对人类具有危险性的工作。
消费者同样可能从中受益。斯蒂芬妮·詹表示:“我们现在看到的家用机器人,其实都只能做一件事。但如果我们成功打造出通用智能机器人,届时消费级机器人就能处理各类家务。”在本届人工智能头脑风暴大会早些时候,Arm首席执行官雷内·哈斯也表达了类似观点。他指出,人形机器人的通用适应能力,将使其在工厂场景中比当下使用的机械臂更具优势。
当然,机器人产业的繁荣也将带来社会层面的影响,冲击目前仍需由人类完成的工作岗位。但帕塔克对自动化普及所带来的社会效益持乐观态度。其一是安全性,机器人可以替代人类从事那些长期来看存在危险或损害健康的工作。另一益处则是缓解蓝领和制造业岗位面临的巨大劳动力短缺。(此问题一直是美国推动高端制造业从亚洲回流本土的主要障碍。)
此外,帕塔克还展望了这样一个未来:机器人将人类从繁重、枯燥的日常工作中解放出来。不过他也坦言,社会需要找到合理方式,来分配自动化带来的红利。他表示:“确实存在一个美好的前景,即每个人都可以做自己喜欢的事情。工作更多是出于自愿,人们可以投身自己热爱的事业之中。”(*)
译者:郝秀
审校:汪皓
Whether it’s running down a track, doing a backflip, dancing to music, or kickboxing, there are more and more videos of humanoid robots doing increasingly impressive things.
Yet speakers at the Fortune Brainstorm AI conference on Tuesday warned against getting too dazzled by the acrobatic feats. A robot doing a backflip–something difficult for a person–looks impressive. But ask a robot to perform seemingly easy tasks, say, climbing up stairs or grabbing a glass of water, and many of todays droids still struggle.
“What looks hard is easy, but what looks easy is really hard,” Stephanie Zhan, a partner at Sequoia Capital, explained, paraphrasing an observation from computer scientist Hans Moravec. In the late Eighties, Moravec and other computer scientists noted that it was easier for computers to perform well on tests of intelligence, yet failed at tasks that even young children could do.
Deepak Pathak, CEO of robotics startup Skild AI, explained that robots, and computers in general, were good at doing complex tasks when operating in a controlled environment. Showing a video of a Skild robot skipping down a sidewalk, Pathak noted that “apart from the ground, the robot is not interacting with anything.”
Yet for tasks like picking up a bottle or walking up stairs, a person is using vision to “continuously correct” what he or she is doing, Pathak explains. “That interaction is the root reason for human general intelligence, which you don’t appreciate because almost every human has it.”
Zhan explained that viral videos of humanoid robots don’t show how the product was trained, nor whether it can operate in an uncontrolled environment. “The challenge for you as a consumer of all these videos is to really discern what’s real and what’s not,” she said.
The next step for robots
Still, both speakers were optimistic that advances in general intelligence will soon lead to more advanced and flexible robots.
“Robots used to be driven more by human intelligence. Somebody super smart would look at [a task], and…pre-program the robot mathematically to do it,” Pathak said.
But now, the robotics field is shifting from “programming something to learning from experience,” he explained. This allows for new robots that handle more complex tasks in more uncontrolled environments, and which can easily be adapted for other tasks without the cost of reprogramming and retooling them.
Today’s robotics firms are “still constrained by having robots that are only built for specific things,” Zhan argued. A robotics platform with more general intelligence can open up “possibilities that are otherwise not possible for us to achieve,” including tasks that are currently dangerous for human workers.
Consumers could benefit too. “You see all these household robots, but they’re only capable of doing one thing,” Zhan said. “But if we succeed at building general intelligent robots, you will finally have consumer robots that can tackle the whole host of household tasks that you now have.” A similar point was made earlier at Brainstorm AI by Arm CEO Rene Haas, who said that the general adaptability of humanoid robots will make them much better suited for factory jobs than the robotics arms used today.
There are social repercussions to a robotics boom, dislodging jobs that, as of now, still needed to be done by humans. Yet Pathak was sanguine about the social benefits of spreading automation. One is safety, as robots remove the need for humans to do jobs that are hazardous or unhealthy in the long-run. Another benefit is filling the massive labor shortage for blue-collar and manufacturing jobs. (That shortfall has been a barrier to U.S. efforts to re-shore much of its advanced manufacturing from Asian economies.)
Yet Pathak also envisioned a future where robots free humans from the drudgery of everyday work, even as he admitted that societies needed to figure out how to spread the gains from automation. “There lies a scenario, a good scenario, where everybody is doing things that they like,” Pathak said. “Work is more optional, and they are doing things that they enjoy.”
