当人工智能遇到机器人：与麻省理工学院计算机科学与人工智能实验室（csail）主任达妮拉·鲁斯的对话

A conversation withDaniela RusDirector, Computer Science and ArtificialIntelligence Laboratory (CSAIL), MIT Executive Conversations DANIELA RUS Director, Computer Scienceand Artificial IntelligenceLaboratory (CSAIL) MIT WHEN AIMEETS ROBOTICS Daniela Rus is the Andrew (1956) and Erna ViterbiProfessor of Electrical Engineering and ComputerScience and Director of the Computer Science andArtificial Intelligence Laboratory (CSAIL) at MIT.Daniela’s research interests are in robotics, mobilecomputing, and data science. She is a Class of 2002MacArthur Fellow, a fellow of the Association forComputing Machinery (ACM), the Association for theAdvancement of Artificial Intelligence (AAAI), andthe Institute of Electrical and Electronics Engineers(IEEE), and a member of the National Academy ofEngineering (NAE), and the American Academy ofArts and Sciences. She earned her PhD in ComputerScience from Cornell University. What inspired you to pursue acareer in robotics and artificialintelligence (AI)? Daniela Rus:I’ve always been drawnto the intersection of mathematicsand computer science, but what reallyinspired me was the idea of computationthat interacts with the physical world.Systems that are not just abstract ordigital, but grounded in the messinessof materials, motion, and uncertainty.Unlike the clean, discrete world oftraditional computation, the real worldis continuous, noisy, and unpredictable.I found that challenge exciting andcompelling. Daniela RusDirector, Computer Science and ArtificialIntelligence Laboratory (CSAIL), MIT Robotics and AI offered a way to explorethat tension: to work on algorithms andmodels that must adapt, learn, and makedecisions in the face of ambiguity. I likedthat it was “mathy” but also physical.You could watch the output of your codetranslated into movement, interaction,or behavior. A big part of my inspiration also camefrom science fiction. I have always beenfascinated by the idea of intelligentmachines as collaborators, explorers,and extensions of human capability. Thatevolved into a curiosity about how wemight build systems that reason, act, andevolve in the real world. IN MANUFACTURING ANDLOGISTICS, ROBOTS WILLNO LONGER BE LIMITED TOREPETITIVE TASKS FROM AI AND ROBOTICS TO “PHYSICAL AI” How do you envision robotics transforming industry? Daniela Rus:We’re entering a phase where robotics will move far beyondstructured factory floors. We’ll see a shift from rigid, pre-programmedsystems to intelligent, reconfigurable machines that can operate in dynamicenvironments, whether that’s a warehouse, a farm, a hospital, a home, oreven a disaster zone. This will fundamentally reshape how we think aboutautomation as a tool for augmenting and extending human capability. In manufacturing and logistics, robots will no longer be limited to repetitivetasks. They’ll collaborate with humans, adapt to changes in workflows, andlearn new skills without reprogramming. In healthcare, we’ll see robots thatcan assist with surgery, rehabilitation, or elder care. These robots will beresponsive to the physical and emotional needs of individuals. In agriculture andconstruction, “soft” and autonomoussystems will navigate off-roadunstructured terrain, making decisionsin real time based on sensor data andenvironmental cues. In healthcare, we’llsee robots that canassist with surgery,rehabilitation, orelder care" Your work spans robotics, mobile computing, and datascience. Where do these fields converge, and what newpossibilities does this create? Daniela Rus:These fields are converging in exciting and transformativeways. Robotics provides embodiment, meaning machines that sense and actin the physical world. Mobile computing brings connectivity, responsiveness,and access to distributed resources, enabling robots to operate flexibly inreal time and in diverse environments. And data science adds the layer ofintelligence, with algorithms capable of extracting patterns from rich sensordata, enabling learning from experience, and supporting predictive decision-making. At their intersection, we’re seeing the rise of physically grounded intelligentsystems, which are robots that can perform tasks and learn from the world,adapt to new contexts, and collaborate with humans and other machines.For example, mobile robots can now continuously collect environmentaldata, learn optimal behaviors from it, and update their policies on the fly, allwhile staying connected to cloud platforms or edge networks that supportcoordination and insight-sharing. This convergence opens the door to new capabilities, from self-reconfiguringsoft robots that adapt their forms and functions in real time, to autonomoussystems that can operate in remote or unpredictable environments withminimal oversight. It’s about building systems that are adaptive, networked,and understand the world they move through. You wrote a book onhow robots and humanscan work together. Howdo you foresee thiscollaboration evolving? Increasingly, robotsare te