Hiroshi Ishii and the Tangible Media Group at the MIT Media Lab have pioneered new ways for people to interact with computers, with the invention of the “tangible user interface.”It began with a vision of "Tangible Bits," where users can manipulate ordinary physical objects to access digital information. It evolved into a bolder vision of "Radical Atoms," where materials can change form and reconfigure themselves just as pixels can on a screen. This experimental exhibit of three iconic works — SandScape, inFORM, and TRANSFORM — is part of the MIT Museum's ongoing efforts to collect the physical machines as well as preserve the user experience of, in Ishii's words, making atoms dance.Learn more about the exhibits here, or watch the YouTube video of Hiroshi Ishii's talk at the MIT Museum below.This is an ongoing exhibition in our MIT Collects exhibition.

Janet Echelman's Remembering the Future widens our perspective in time, giving sculptural form to the history of the Earth's climate from the last ice age to the present moment, and then branching out to visualize multiple potential futures.Constructed from colored twines and ropes that are braided, knotted and hand-spliced to create a three-dimensional form, the immersive artwork greets you with its grand scale presiding over the MIT Museum lobby.This large-scale installation by 2022-2024 MIT Distinguished Visiting Artist Janet Echelman, was developed during her residency at the MIT Center for Art, Science & Technology (CAST). Architect, engineer and MIT Associate Professor Caitlin Mueller collaborated on the development of the piece.The title, Remembering the Future was inspired by the writings commonly attributed to Søren Kierkegaard: "The most painful state of being is remembering the future, particularly the one you'll never have."As the culmination of three years of dedicated research and collaboration, this site-specific installation explores Earth's climate timeline, translating historical records and possible futures into sculptural form.Echelman's climate research for this project was guided by Professor Raffaele Ferrari and the MIT Lorenz Center, creators of En-ROADS simulator which uses current climate data and modeling to visualize the impact of environmental policies and actions on energy systems.Learn more about Janet Echelman and the MIT Museum x CAST Collaboration.Learn more about the exhibition at the MIT Museum.

Enrollment: Limited: Advance sign-up required Limited to 35 participantsAttendance: Participants must attend all sessionsPrereq: Matrix MathematicsBig Data describes a new era in the digital age where the volume, velocity, and variety of data created across a wide range of fields is increasing at a rate well beyond our ability to analyze the data. Machine Learning has emerged as a powerful tool for transforming this data into usable information. Many technologies (e.g., spreadsheets, databases, graphs, matrices, deep neural networks, ...) have been developed to address these challenges. The common theme amongst these technologies is the need to store and operate on data as tabular collections instead of as individual data elements. This class describes the common mathematical foundation of these tabular collections (associative arrays) that apply across a wide range of applications and technologies. Associative arrays unify and simplify Big Data and Machine Learning. Understanding these mathematical foundations allows the student to see past the differences that lie on the surface of Big Data and Machine Learning applications and technologies and leverage their core mathematical similarities to solve the hardest Big Data and Machine Learning challenges.This interactive course will involve significant interactive student participation and a small amount of homework. Those students who fully participate and complete the homework will receive a certificate of completion.The MIT Press book "Mathematics of Big Data" that will be used throughout the course will be provided.E-mail the instructor to sign up.Instructors:Hayden Jananthan - Research Scientist MIT Supercomputing Center - hayden.jananthan@ll.mit.eduJeremy Kepner - Fellow & Head MIT Supercomputing Center - kepner@ll.mit.eduSignup Deadline: Dec 15

Workshop blurb:Ever wondered how are objects from our daily lives designed? How can we generate a computer 3D model of a classic iPod, a Play Station controller, or a LEGO Tower Bridge? What about designing the Taipei 101 tower? A banana? Or how about visualizing and interacting with these objects using VR? In this fun MIT IAP 2026 workshop, you will learn the skills to design and VR-visualize all of these, and much more!Split into 8 (6 CAD, 2 VR) 2-hour long sessions, the first half of each session will be spent learning new Autodesk Inventor and VR skills, while the second half will see the application of these new skills through in-class activities, with a focus on reverse engineering. In contrast to traditional mechanical design courses, this workshop places greater emphasis on the design process itself, understanding how we can plan and best leverage our available tools to arrive to our desired result. Thus, the sessions are less about following the instructions on an engineering drawing, and more about independent thinking and strategizing, reverse engineering an object into a 3D model. New to this edition of "How to CAD" are 2 sessions that will go through the process of visualizing 3D models using VR!Logistics:Please express your interest in this workshop by filling up the following form.You can find the "How to CAD Almost Anything" syllabus for this IAP 2026 here.

Time: 5:00 PMLocation: Cambridge, MA

The irony of artificial intelligence is that it often reveals more about human intelligence than machines themselves.From AI in the home to robots in the workplace, the presence of AI all around us compels us to question its potential and recognize the risks. What has become clear is that the more we advance AI technology and consider machine ability versus human ability, the more we need to mind the gap.Researchers at MIT have been at the forefront of this evolving field. The work presented in this exhibition builds on the pioneering contributions of figures such as Claude Shannon and Seymour Papert, while highlighting contemporary research that spans computer science, mechanical engineering, neuroscience, and the social sciences.As research probes the connections between human and machine intelligence, it also underscores the profound differences. With AI now embedded in everyday life — from smart assistants in our homes to robots in the workplace — we are challenged to ask critical questions about its potential, its risks, and the boundaries between machine ability and human capability.Join us in shining light on the tremendous promise, unforeseen impacts, and everyday misconceptions of AI in this riveting, interactive exhibition.Learn more about the exhibition.