MIT Logo
Vision Understanding intelligence

The high-level goal of the Mind Machine project is to reconcile natural intelligence with machine intelligence, and in doing so develop and engineer a class of intelligent machines.

Based in the Center for Bits and Atoms (CBA), MMP brings together researchers in integrated teams from CBA, Brain & Cognitive Sciences, the Computer Science and Artificial Intelligence Laboratory, the Research Laboratory of Electronics, and the Media Lab, as well as a network of institutional partners.

The work is divided into teams under the broad categories of Mind, Body, Memory, and Brain/Intent.

Mind: Develop a software model capable of understanding human social contexts- the signposts that establish these contexts, and the behaviors and conventions associated with them.
Research areas: hierarchical and reflective common sense
Lead researchers: Marvin Minsky, Patrick Winston

Body: Explore candidate physical systems as substrate for embodied intelligence
Research areas: reconfigurable asynchronous logic automata, propagator-oriented programming
Lead researchers: Neil Gershenfeld, Ben Recht, Gerry Sussman

Memory: Further the study of data storage and knowledge representation in the brain; generalize the concept of memory for applicability outside embodied local actor context
Research areas: common sense
Lead researcher: Henry Lieberman

Brain and Intent: Study the embodiment of intent in neural systems. It incorporates wet laboratory and clinical components, as well as a mathematical modeling and representation components. Develop functional brain and neuron interfacing abilities. Use intent-based models to facilitate representation and exchange of information.
Research areas: wet computer, brain language, brain interfaces
Lead researchers: Newton Howard, Sebastian Seung, Ed Boyden

Prospective applications include natural language understanding, unsupervised data inference, and assistance with mental illness and aging.

MMP is directed by Newton Howard. It was launched by an initial seven year, multi-million dollar gift, with support chaired by Richard Wirt, former Intel executive and Intel Senior Fellow.

Goals Building intelligent machines

The work of MMP spans four intellectual generations, revisiting fundamental assumptions about the nature of the brain, cognition, computing, and intelligence. The project is based on the belief that, by bringing together current advances in each of these areas with insights from their roots, it will be possible to fulfill the early vision that lies at their intersection.

Mind (models for thought), Memory (accumulating and using experience), Body (scalable substrates to embody intelligence), and Brain/Intent (looking for advanced applications of these technologies, such as "non-chemical based" solutions for psychiatric treatments and brain prostheses).

Research Initiatives include:

People Bios and research interests
Dr. Newton Howard, HDR La Sorbonne, Mathematics
MIT Principal Investigator and the Director of the Mind Machine Project

Dr. Newton Howard is the director of the Mind Machine Project and a resident scientist at MIT. He received his Doctoral degree in Cognitive Informatics and Mathematics from the University of Paris 1 - La Sorbonne (France) where he was also awarded the Habilitation à Diriger des Recherches for his leading work on the Physics of Cognition (PoC) and its applications to complex medical, economic, and security problems. While a graduate at the Faculty of Mathematical Sciences at the University of Oxford, England, he proposed the Theory of Intention Awareness (IA). He held positions as a professor of Mathematics and Psychiatry at The George Washington University, where he established leading academic programs directed to solve real world problems.

Dr. Marvin Minsky
Distinguished Scientist/Professor Emeritus, MIT

Dr. Minsky has made many contributions to AI, cognitive psychology, mathematics, computational linguistics, robotics, and optics. In recent years he has worked chiefly on imparting to machines the human capacity for commonsense reasoning. His conception of human intellectual structure and function is presented in The Society of Mind (CDROM, book) which is also the title of the course he teaches at MIT.

He received the BA and PhD in mathematics at Harvard (1950) and Princeton (1954). In 1951 he built the SNARC, the first neural network simulator. His other inventions include mechanical arms, hands and other robotic devices, the Confocal Scanning Microscope, the "Muse" synthesizer for musical variations (with E. Fredkin), and one of the first LOGO "turtles". A member of the NAS, NAE and Argentine NAS, he has received the ACM Turing Award, the MIT Killian Award, the Japan Prize, the IJCAI Research Excellence Award, the Rank Prize and the Robert Wood Prize for Optoelectronics, and the Benjamin Franklin Medal.

Dr. Patrick Winston
Ford Professor of Artificial Intelligence and Computer Science, MIT

Patrick Henry Winston is an American computer scientist. Winston was director of the MIT Artificial Intelligence Laboratory for most of its existence, from 1972 to 1997. He succeeded Marvin Minsky, who left to found the MIT Media Lab shortly after establishing the AI Lab in the wake of the political upheavals at that time. He was succeeded by Rodney Brooks after a long, stable period. Brooks went on to terminate the lab by merger into the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).

Winston's thesis work concerned the difficulty of learning; he concluded you could only learn something you nearly already know. He was a student of Marvin Minsky. Currently, he is Ford Professor of Artificial Intelligence and Computer Science at the MIT CSAIL. He is active in research and interested in machine learning and human intelligence. Winston also teaches a heavily subscribed course at MIT titled "The Human Intelligence Enterprise" which teaches AI and how to effectively communicate. Winston is known within the MIT community for his strong commitment to supporting MIT undergraduate culture. He is also an avid woodworker having made all the furniture in his office.

Winston currently teaches 6.034: Artificial Intelligence and 6.803/6.833: Human Intelligence Enterprise. Winston is also a (co-)author of a number of CS and AI textbooks, including:

Dr. Gerry Sussman
Panasonic Professor of Electrical Engineering, MIT

Gerald Jay Sussman received the S.B. and the Ph.D. degrees in mathematics from the Massachusetts Institute of Technology in 1968 and 1973, respectively. He has been involved in artificial intelligence research at M.I.T. since 1964. His research has centered on understanding the problem-solving strategies used by scientists and engineers, with the goals of automating parts of the process and formalizing it to provide more effective methods of science and engineering education. Sussman has also worked in computer languages, in computer architecture and in VLSI design.

Sussman is a coauthor (with Hal Abelson and Julie Sussman) of the introductory computer science textbook used at M.I.T. The textbook, "Structure and Interpretation of Computer Programs," has been translated into French, German, Chinese, Polish, and Japanese. As a result of this and other contributions to computer-science education, Sussman received the ACM's Karl Karlstrom Outstanding Educator Award in 1990, and the Amar G. Bose award for teaching in 1991.

Sussman's contributions to Artificial Intelligence include problem solving by debugging almost-right plans, propagation of constraints applied to electrical circuit analysis and synthesis, dependency-based explanation and dependency-based backtracking, and various language structures for expressing problem-solving strategies. Sussman and his former student, Guy L. Steele Jr., invented the Scheme programming language in 1975.

Sussman has pioneered the use of computational descriptions to communicate methodological ideas in teaching subjects in Electrical Circuits and in Signals and Systems. Over the past decade Sussman and Wisdom have developed a subject that uses computational techniques to communicate a deeper understanding of advanced Classical Mechanics. Computational algorithms are used to express the methods used in the analysis of dynamical phenomena. Expressing the methods in a computer language forces them to be unambiguous and computationally effective. Students are expected to read our programs and to extend them and to write new ones. The task of formulating a method as a computer-executable program and debugging that program is a powerful exercise in the learning process. Also, once formalized procedurally, a mathematical idea becomes a tool that can be used directly to compute results. Sussman and Wisdom, with Meinhard Mayer, have produced a textbook, "Structure and Interpretation of Classical Mechanics," to capture these ideas.

Sussman is a fellow of the Institute of Electrical and Electronics Engineers (IEEE). He is a member of the National Academy of Engineering (NAE), a fellow of the American Association for the Advancement of Science (AAAS), a fellow of the Association for the Advancement of Artificial Intelligence (AAAI), a fellow of the Association for Computing Machinery (ACM), a fellow of the American Academy of Arts and Sciences, and a fellow of the New York Academy of Sciences (NYAS). He is also a bonded locksmith, a life member of the American Watchmakers-Clockmakers Institute (AWI), a member of the Massachusetts Watchmakers-Clockmakers Association, a member of the Amateur Telescope Makers of Boston (ATMOB), and a member of the American Radio Relay League (ARRL).

Prof. Neil Gershenfeld
Director of the Center for Bits and Atoms

Prof. Gershenfeld's unique laboratory is breaking down boundaries between digital and physical worlds, from creating molecular quantum computers to virtuosic musical instruments. Technology from his lab has been seen and used in settings including New York's Museum of Modern Art and rural Indian villages, the White House and the World Economic Forum, inner-city community centers and automobile safety systems, Las Vegas shows and Sami herds.

He is the author of numerous technical publications, patents, and books including Fab, When Things Start To Think, The Nature of Mathematical Modeling, and The Physics of Information Technology, and has been featured in media such as The New York Times, The Economist, and the McNeil/Lehrer News Hour. He is a Fellow of the American Physical Society, has been named one of Scientific American's 50 leaders in science and technology, has been selected as a CNN/Time/Fortune Principal Voice, and by Prospect/FP as one of the top 100 public intellectuals. Prof. Gershenfeld has a BA in Physics with High Honors and an honorary Doctor of Science from Swarthmore College, a Ph.D. from Cornell University, was a Junior Fellow of the Harvard University Society of Fellows, and a member of the research staff at Bell Labs.

Dr. Henry Lieberman
Research Scientist, MIT Media Lab

Henry Lieberman has been a Research Scientist at the MIT Media Laboratory since 1987. His interests are in the intersection of artificial intelligence and the human interface. He directs the Software Agents group, which is concerned with making intelligent software that provides assistance to users in interactive interfaces.

Many of his current projects revolve around applying Common Sense Reasoning to interactive interfaces. He is using a large knowledge base of Commonsense facts about everyday life to streamline interfaces, provide intelligent defaults, and proactive help. Application areas include predictive typing, multilingual communication, management of photo and media libraries, product recommendation and e-commerce tools. He has edited or co-edited three books, including End-User Development (Springer, 2006), Spinning the Semantic Web (MIT Press, 2004), and Your Wish is My Command: Programming by Example (Morgan Kaufmann, 2001).

From 1987-1994 he worked with graphic designer Muriel Cooper on tools for visual thinking, and new graphic metaphors for information visualization and navigation. He holds a strong interest in making programming easier for non-expert users. He is a pioneer of the the technique of Programming by Example, where a user demonstrates examples, which are recorded and generalized using techniques from machine learning. He has also worked on reversible debuggers, 3D programming, and natural language programming.

From 1972-87, he was a researcher at the MIT Artificial Intelligence Laboratory. He started with Seymour Papert in the group that originally developed the educational language Logo, and wrote the first bitmap and color graphics systems for Logo. He also worked with Carl Hewitt on actors, an early object-oriented, parallel language, and developed the notion of prototype object systems and the first real-time garbage collection algorithm. He holds a doctoral-equivalent degree (Habilitation) from the University of Paris VI and was a Visiting Professor there in 1989-90.

H. Sebastian Seung
Professor of Computational Neuroscience, MIT; Investigator, Howard Hughes Medical Institute

Dr. Seung is Professor of Computational Neuroscience in the Department of Brain and Cognitive Sciences and the Department of Physics at the Massachusetts Institute of Technology, and Investigator of the Howard Hughes Medical Institute. He studied theoretical physics with David Nelson at Harvard University and completed postdoctoral training with Haim Sompolinsky at the Hebrew University of Jerusalem. Before joining the MIT faculty, he was a member of the Theoretical Physics Department at Bell Laboratories. He has been a Packard Fellow, Sloan Fellow, and McKnight Scholar.

His algorithms for nonnegative matrix factorization have been widely applied to problems in visual learning, semantic analysis, spectroscopy, and bioinformatics. His theories of empiric and hedonistic synapses are hypothetical implementations of reinforcement learning for spiking neural networks. He advanced a spiking network model of neural integrators, after conceptualizing them in terms of continuous dynamical attractors. At the core of his theory of permitted and forbidden sets is a new idea about how memories can be latent in the synaptic connections of a recurrent neural network.

Dr. Ed Boyden
Benesse Career Development Professor, MIT Media Lab

I lead the Synthetic Neurobiology Group at MIT. We are inventing new tools for analyzing and engineering brain circuits. We are devising technologies for controlling specific neural circuit elements, to understand their causal contribution to normal and pathological neural computations. Our inventions include 'optogenetic' tools we developed for activation and silencing of neural circuits with light, and noninvasive devices using novel physical principles to control neural activity. We are using our inventions to enable systematic approaches to neuroscience, revealing how entire neural circuits operate to generate behavior, and empowering new therapeutic strategies for neurological and psychiatric disorders. Our entrepreneurial approach to tackling clinically and philosophically important problems will hopefully yield a better understanding of the nature of human existence, and the ability to engineer improvements thereupon.

External Collaborators

Dr. Mathieu Guidère
Professor, University of Geneva

Dr. Mathieu Guidère is a leading researcher on cognitive linguistics and its applications. A graduate of the Faculty of Languages at the University of Toulouse-Le Mirail, he holds two Masters degrees in French and Arabic, and a Doctoral degree in Computational Linguistics from La Sorbonne (France). From 1998 to 2002, Dr. Guidère was an associate professor at the University of Lyon 2 (France). From 2000 to 2003, Dr. Guidère was Editor-in-Chief of "Les Langues Modernes", an interdisciplinary academic journal sponsored by the French Language Association. Having developed the "Multilingual Monitoring Methodology" (M3), he has also published several books and numerous articles on Arabic language processing. From 2003 to 2007, he was Professor at the French Military Academy (Saint-Cyr) where he taught Arabic history, culture and dialects. From 2003 to 2007, Dr. Guidère was Director of the Strategic Information Analysis Unit at the Saint-Cyr Research Center in France, where he addressed the applications of text mining and mass data processing and headed several research projects which focus on language modeling and codification. Since 2007, Dr. Guidère is full Professor at the University of Geneva, Switzerland, where he leads a research group on language processing and translation.

Dr. Ben Recht
Assistant Professor, Computer Sciences, University of Wisconsin

Dr. Richard Wirt
Intel Senior Fellow

Richard Wirt, a senior technology executive with 35 years of experience in the computer industry, was Vice President and General Manager of Intel Corporation’s Software and Solutions Group. He developed and nurtured the Intel software group from when he founded it in 1982 to a 3000 person worldwide operation in 2007. Working closely with Intel Capital, Dr. Wirt made many successful worldwide investments including 10 large acquisitions of software companies. Operating at the highest executive level, Dr. Wirt worked with Intel industry partners such as Microsoft, Dell, Oracle, HP, IBM, NEC, Fujitsu, Redhat, and many others, building ecosystems to grow Intel’s processors’ market while maintaining more than 85% market share. In 2007 Dr. Wirt also served as Chief Scientist and Executive Vice President at In-Q-Tel, a technology investment group that supports the U.S. government.

Sergey Kanareykin
Researcher, University of Paris 1 / Partner, Oxantium Group

Sergey Kanareykin received a bachelor's degree in Computer Science from Denison University, and a master's degree in Computer Science from The George Washington University, with a concentration is information assurance. He a doctoral student at the University of Paris 1, La Sorbonne (France), conducting research in the areas of cognitive informatics and applications to network security. Previously, as the CTO of the Center for Advanced Defense Studies in Washington DC, Sergey was instrumental in establishing the Center's technology research and development capacity in the fields of information sharing and security, with funding from the Department of Justice, Department of Defense, as well as private industry, such as Intel Corporation and Harris Corporation. As a partner with a venture group, he also oversees investment strategies for computing platforms, cognitive technologies, and collaborative systems.

Guy Fedorkow
Consultant, Mind Machine Project
Guy C. Fedorkow received his BASc and MASc in Engineering Sciences at University of Toronto, and went on to develop both communications and high-throughput parallel computer architectures at Bolt, Berank and Newman in Cambridge, MA. After joining Cisco Systems in January 1995, he served as system architect for a number of Cisco products, including the LS2020 multiservice ATM switch, the Cisco 10000 Edge Services Router, and the Cisco 9000 Metro Ethernet Switch, and has also contributed to platform-independent developments in the area of modular I/O and network synchronization.

Bent Schmidt-Nielsen
Consultant, Mind Machine Project
Bent Schmidt-Nielsen has seven years of experience at Dragon Systems in applying speech recognition to useful products. At Mitsubishi Electric Research Laboratories, he worked on making speech interfaces robust and usable. Bent has very broad interests in science and technology. Among many other activities he has taught genetics at the University of Massachusetts at Boston and he has been a leader in the development of an easy to use mass market database.

Mark M. Atallah
Research Assistant, Make a Mind Co.

Research Associates/Assistants

Scott Greenwald
Research Assistant, Center for Bits and Atoms, MIT

Forrest Green
Research Assistant, Center for Bits and Atoms, MIT

Dr. Catherine Havasi
Research Associate, Common Sense Computing Initiative and Software Agents Group, MIT
Catherine Havasi has been active in common sense research since 1999, focusing her current research on that along with natural language processing and learning. She is one of the co-founders of the Open Mind Common Sense project at the MIT Media Lab and currently works to expand and sustain its research. Her current research interests include streaming semantic analysis, computation creativity, working with stories, and grounding common sense. She received her S.B. in Computer Science from MIT, her masters from the same place, and her Ph.D from Brandeis University.

David Dalrymple
Research Assistant, Mind Machine Project, MIT

David Dalrymple is a 17-year-old doctoral student at MIT's Center for Bits and Atoms and the Mathematics and Computation Group. He earned bachelor's degrees in computer science and mathematics in 2005 from UMBC with numerous honors, then spent a year working as an independent consultant in Maryland and New York before starting graduate school at MIT at age 14. In his master's thesis, he developed Asynchronous Logic Automata, a massively parallel architecture of computing that is also intuitive to program. In his Ph.D., he is continuing to develop the model into Reconfigurable Asynchronous Logic Automata (RALA), and leveraging this technology as a platform for novel work in programming languages and artificial intelligence. Dalrymple is also an avid photographer and musician, and will be appearing in the upcoming feature film "The Singularity is Near".

Peter Schmidt-Nielsen
Collaborator

Dr. Alexey Radul
Research Associate, Mathematics and Computation Group, MIT CSAIL

Alexey Radul began his career in AI investigating natural language. However, after observing some intensely engineered multistage systems that nonetheless exhibited performance worse than chance on tasks humans find easy, he concluded that without a better model for communication between stages, human-like intelligence is impossible. Probability theory describes one such better communication style, because instead of one stage having to commit to the data it passes to the next, it can say "I think the answer is A, but it might also be B, or perhaps even C, though the last two are much less likely; and if you don't like any of that, let me know and I can compute some more and maybe come up with some other possibilities." This observation prompted Dr. Radul to move into the field of probability programming, aiming to build a language that eased just such communication between subsystems. After trying it, however, he came to the conclusion that the essence of their revolutionary capabilities lay not in probability — it is one possible aspect of communication between stages — but in multidirectionality itself, in the ability for one stage of a computation to hold semantic discourse with another. His current research is in propagator networks, a multidirectional programming paradigm where different types of communication (including probabilistic communication, but others are possible) can be used where needed, modularly. The goal is to distill the fundamental communication substrate that will make AI possible.

Dustin Smith
Research Assistant, MIT Media Lab

Dustin Smith's research goal is to make computers understand English in a similar functional capacity as people. This ambition treads many academic topics: machine reading and story understanding, event structures and lexical semantics, semantic role labeling, statistical relational learning, sequence mining, event recognition and extraction, planning, plan recognition, metacognition and self-modeling.

Rob Speer
Research Assistant, Software Agents Group, MIT Media Lab

Bo Morgan
Research Assistant and PhD Candidate, MIT Media Lab

Bo Morgan was born and raised in sunny San Diego, California. Morgan was an undergraduate at MIT from 1999 to 2004, when he graduated with a BS in Electrical Engineering and Computer Science with a focus in Artificial Intelligence. As an undergraduate he loved neuroscience and the brain and took 13 neuroscience classes studying learning, memory, and biochemical implementations of human thinking. He attended the MIT Media Lab for his Masters degree, which he received in 2006 in Commonsense Reasoning under the late Push Singh, under whom he had studied and built simulations of social commonsense robotics for the previous six years. After Push's untimely death, Morgan was adopted by Joe Paradiso's research group in order to study distributed computation and found himself a home to develop Marvin Minsky's cognitive architectures.

Morgan's PhD thesis work is focused on how parents and children learn to communicate problem solving knowledge through reflective commonsense reasoning. He is also an avid funk bass guitar player, which is the inspiration for the name of his reflective functional programming language, Funk2.

Morgan has taught Rosalind Picard's pattern recognition class, and for the last four years he has been a teaching assistant in Marvin Minsky's Society of Mind class with Dustin Smith.

Material Enter IsisWorld

Research Initiatives

Code Other Publications News