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J-WEL AI Knowledgebase
DLCI
MIT Departments, Labs, Centers, and Initiatives (DLCI) involved with Artificial Intelligence (AI) and Machine Learning (ML)
The DLCI document lists various Massachusetts Institute of Technology (MIT) departments, programs, and initiatives related to Artificial Intelligence (AI) and Machine Learning (ML), along with associated researchers and resource links. It features MIT's AI+D and LIDS programs with numerous AI researchers and a podcast on smart grid modeling. Other departments like Chemical Engineering and Mechanical Engineering offer insights into the ethics of AI bias and AI for engineers. The Sloan School of Management discusses the intersection of machine learning and business, while the MIT Technology Review covers AI trends and societal impacts. The Media Lab explores AI's potential for personal development, and CSAIL provides extensive resources on AI and data science. Other highlighted entities include the MIT-IBM Watson AI Lab, Jameel Clinic, and MIT xPro, each contributing to the AI and ML dialogue with courses, conferences, and research projects.
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MIT AI Researcher List
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MIT Artificial Intelligence + Decision-making (AI+D)
AI+D
Artificial Intelligence and Decision-making combines intellectual traditions from across computer science and electrical engineering to develop techniques for the analysis and synthesis of systems that interact with an external world via perception, communication, and action; while also learning, making decisions and adapting to a changing environment.
Our research explores the foundations of machine learning and decision systems (artificial intelligence, reinforcement learning, statistics, causal inference, systems and control); the building blocks of embodied intelligence (computer vision, NLP, robotics); applications to real-world autonomous systems; life sciences; and the interface between data-driven decision-making and society.
Alan Oppenheim
Alan Willsky
Alexandre Megretski
Antonio Torralba
Antonio Torralba
Armando Solar-Lezama
Polina Golland
Regina Barzilay
Tim Kraska
Jonathan Ragan-Kelley
Jacob Andreas
Tommi Jaakkola
Sam Hopkins
Manolis Kellis
Martin Rinard
Fredo Durand
Tomas Lozano-Perez
Piotr Indyk
Mina Konakovic Lukovic
Leslie Kaelbling
Show 68 moreMIT Laboratory for Information and Decision Systems (LIDS)
LIDS
The Laboratory for Information and Decision Systems (LIDS) at MIT is an interdepartmental research center committed to advancing research and education in the analytical information and decision sciences, specifically:
Alexander Rakhlin
Ali Jadbabaie
Anuradha Annaswamy
Ashia Wilson
Asu Ozdaglar
Pulkit Agrawal
Tamara Broderick
Stefanie Jegelka
Luca Carlone
Stephen Bates
Kalyan Veeramachaneni
Mardavij Roozbehani
Song Han
Eytan Modiano
Hamsa Balakrishnan
Kuikui Liu
Cathy Wu
Youssef Marzouk
Devavrat Shah
Sertac Karaman
Show 19 morePodcast: The MIT Artificial Intelligence Podcast
Generative AI for smart grid modeling
Chemical Engineering
CE
Formally established as a separate department in 1920, MIT’s Chemical Engineering department (ChemE) has not only set the standard for instruction and research in the field, it continues to redefine the discipline’s frontiers. With one of three undergraduate programs focusing on chemical-biological engineering for students interested in the emerging biotech and life sciences industries, and two of three graduate programs providing an experiential course of study in chemical engineering practice in collaboration with MIT’s Sloan School of Management, ChemE at MIT is quite unlike chemical engineering anywhere else.
Ethics of AI Bias
Ethics Of AI Bias
MIT Sloan School of Management
Sloan
MIT Sloan is a different kind of management school. We’re not iterating on a better widget or cashing in on the latest business fad. We’re not talking about management in the abstract.
As part of the world’s leading research institution, we’re bringing together today’s brightest minds to tackle global challenges. For real.
Kate Kellogg
Jonathan Ruane
Paul McDonagh-Smith
John J. Horton
Luis Videgaray
Renee Richardson Gosline
Danielle Li
Rama Ramakrishnan
Simon Johnson
George F Westerman
Machine Learning in Business
How should AI-generated content be labeled?
Making AI Work: Machine Intelligence for Business and Society
Human Favoritism, Not AI Aversion: People’s Perceptions (and Bias) Toward Generative AI, Human Experts, and Human-GAI Collaboration in Persuasive Content Generation
Unsupervised Machine Learning: Unlocking the Potential of Data
Prediction: Machine Learning And Statistics
A generative AI tool to inspire creative workers
Data-Driven Teaching: AI for Pre- and Post-Class Surveys
AI Detectors Don’t Work. Here’s What to Do Instead.
Practical Strategies for Teaching with AI
Getting Started with AI-Enhanced Teaching: A Practical Guide for Instructors
MIT Department of Mechanical Engineering
ME
The Department of Mechanical Engineering – MechE – embodies the Massachusetts Institute of Technology’s motto mens et manus, “mind and hand,” as well as “heart” by combining analysis and hands-on discovery with a commitment to making the world a better place. We train the next generation of mechanical engineers to develop creative products and solutions. By leveraging our strengths, we aspire to solve some of the grand challenges facing our world.
Ethics For Engineers: Artificial Intelligence
MIT Sloan Management Review
Sloan Review
At MIT Sloan Management Review (MIT SMR) we explore how leadership and management are transforming in a disruptive world. We help thoughtful leaders capture the exciting opportunities — and face down the challenges — created as technological, societal, and environmental forces reshape how organizations operate, compete, and create value.
We distribute our content on the web, in print, in audio podcast, and in apps, as well as via licensees and libraries around the world.
Podcast: Me, Myself, and AI
Building Robust RAI Programs as Third-Party AI Tools Proliferate
The Future of AI-Driven Customer Service
How Developers Can Lower AI’s Climate Impact
Learn to Make the Most of Your Relationship With AI
Increasing AI Tool Adoption by Front-Line Workers
Using Federated Machine Learning to Overcome the AI Scale Disadvantage
Machine Learning and Data Analytics in the Pandemic Era
Critical Success Factors for Achieving ROI From AI Initiatives
How to Succeed With AI Augmentation
Individual AI Use Can Benefit Organizations
Artificial Intelligence and Business Strategy
Finding Transformation Opportunities With Generative AI
Pair People and AI for Better Product Demand Forecasting
Are Responsible AI Programs Prepared for Third-Party and Generative AI?
Use Open Source for Safer Generative AI Experiments
To Be a Responsible AI Leader, Focus on Being Responsible
AI Is Helping Companies Redefine, Not Just Improve, Performance
Generative AI Demystified: What It Really Means for Business
Three Lessons From Chatting About Strategy With ChatGPT
Show 13 moreAmini Lab | Electrical Engineering and Computer Science
Amini Lab
MIT’s introductory course on deep learning methods with applications to computer vision, natural language processing, biology, and more! Students will gain foundational knowledge of deep learning algorithms and get practical experience in building neural networks in TensorFlow. Course concludes with a project proposal competition with feedback from staff and panel of industry sponsors. Prerequisites assume calculus (i.e. taking derivatives) and linear algebra (i.e. matrix multiplication), we’ll try to explain everything else along the way! Experience in Python is helpful but not necessary. Listeners are welcome!
MIT: Deep Learning | Introduction to Deep Learning
Nuclear Science and Engineering
NSE
The Department of Nuclear Science & Engineering provides educational opportunities for undergraduate and graduate students interested in advancing the frontiers of nuclear science and engineering and in developing applications of nuclear technology for the benefit of society and the environment. We prepare our students to make contributions to the scientific fundamentals of our field; to the development and engineering of nuclear systems for energy generation, security, health care, and other applications; and to the integration of nuclear systems into society and the natural environment.
Ethics For Engineers: Artificial Intelligence
Economics/Sloan
Economics/Sloan
In the MIT Sloan Applied Economics Group, we use economic theory and econometrics to address the practical challenges facing humanity. Our research spans a wide variety of fields, theoretical and empirical, and integrates a broad spectrum of tools. Our focus: high quality research with real-world implications. We study organizations, health economics, macroeconomics, pricing, markets and industrial organization, development economics, and energy and environmental economics. Like our peers across the Institute, we are always pushing the research frontier, collaborating widely with other academics and policy makers in the United States and around the globe.
Daron Acemoglu
Mathematics
Math
The Mathematics Department at MIT is a world leader in pure and applied mathematical research and education. In pure mathematics we explore exciting current research directions in most of the major fields. In applied mathematics, we look for important connections with other disciplines that may inspire interesting and useful mathematics, and where innovative mathematical reasoning may lead to new insights and applications. Our applied math group focuses on biology, combinatorics, computer science, scientific computing, numerical analysis, and areas of physical applied mathematics.
Mathematics Of Machine Learning
Introduction To Computational Thinking With Julia, With Applications To Modeling The COVID-19 Pandemic
CSAIL Embodied Intelligence
EI
Our goal is to understand the nature of intelligent behavior in the physical world, through the study of human intelligence and the design and implementation of intelligent robots. We bring expertise in perception, sensing, language, learning and planning, and have the objective of integrating these disciplines to make physical agents with human-like intelligence.
MIT Hardware Accelerated Neural-Nets Lab
Han Lab
Welcome to MIT HAN Lab, where efficiency meets performance, innovation converges with excellence in the realm of artificial intelligence (AI) and computer architecture. Our lab stands at the forefront of cutting-edge research, encompassing a wide spectrum of topics from LLM and genAI to TinyML and hardware design. Combining expertise in algorithm and hardware, we are dedicated to pushing the limits of efficiency in AI.
EfficientML.ai Lecture | EfficientML.ai Lecture, Fall 2023, MIT 6.5940
EfficientML.ai Lectures, Fall 2023, MIT 6.5940. Full Course
Tiny machine learning design alleviates a bottleneck in memory usage on internet-of-things devices
AI (Artificial Intelligence) and ML (Machine Learning) Club
AI & ML Club
The mission of the AI (Artificial Intelligence) and ML (Machine Learning) Club at the MIT Sloan School of Management is to provide a space for students to learn about and discuss the latest developments in artificial intelligence and machine learning. Through workshops, guest speakers, and networking events, the club aims to educate and inspire its members about the potential applications of AI and ML in business and other fields.
MIT AI/Machine Learning Club Youtube Channel
MIT Lincoln Laboratory
LL
MIT Lincoln Laboratory researches and develops a broad array of advanced technologies to meet critical national security needs. What sets us apart from many national R&D laboratories is our focus on building operational prototypes of the unique systems we design.
Our ability to turn concepts into field-worthy systems is supported by state-of-the-art facilities, such as a world-class semiconductor research and fabrication laboratory, a flight facility boasting several aircraft customized for field-testing airborne systems, and New England’s fastest, most powerful supercomputing center.
AI and ML Accelerator Survey and Trends
Cyber Network Data Processing; AI Data Architecture
Cyber Network Data Processing; AI Data Architecture
Artificial Intelligence and Machine Learning
AI (Artificial Intelligence) and ML (Machine Learning) Club
AI & ML Club
The mission of the AI (Artificial Intelligence) and ML (Machine Learning) Club at the MIT Sloan School of Management is to provide a space for students to learn about and discuss the latest developments in artificial intelligence and machine learning. Through workshops, guest speakers, and networking events, the club aims to educate and inspire its members about the potential applications of AI and ML in business and other fields.
From the MIT GenAI Summit: A Crash Course in Generative AI
MIT Technology Review
Tech Review
Founded at the Massachusetts Institute of Technology in 1899, MIT Technology Review is a world-renowned, independent media company whose insight, analysis, reviews, interviews and live events explain the newest technologies and their commercial, social and political impacts.
MIT Technology Review derives authority from its relationship to the world’s foremost technology institution and from its editors’ deep technical knowledge, capacity to see technologies in their broadest context, and unequaled access to leading innovators and researchers.
Five Key Trends in AI and Data Science for 2024
Conversational AI revolutionizes the customer experience landscape
This is how AI bias really happens—and why it’s so hard to fix
MIT Report: How Generative AI will Reshape the Enterprise: CIO perspectives on GenAI
Podcast: In Machines We Trust
The future of AI’s impact on society (Dec 2019)
Jameel World Education Lab
J-WEL
The Jameel World Education Lab takes this mission to the world. We are MIT’s connection point for educational innovators everywhere, enriching ongoing conversations by drawing in global faculty and other experts and co-designing practical innovations that broaden our knowledge. Through our work, we aim to define the cutting edge of educational practice that delivers global impact and transforms learning for all.
J-WEL test
MIT Sloan Management Review Connections
MIT SRM Connections
MIT SMR Connections is an independent content creation unit within MIT Sloan Management Review. Our team develops high-quality sponsored content to bring readers the latest insights on leadership, managing technology, and digital transformation.
MIT Research Report: How AI Changes the Rules: New Imperatives for the Intelligent Organization (2020)
How AI Demands Organizational Change
Making Strategic Technology Decisions for Successful Enterprise AI
Using Artificial Intelligence to Thrive in Challenging Times
AI & ML Club
The mission of the AI (Artificial Intelligence) and ML (Machine Learning) Club at the MIT Sloan School of Management is to provide a space for students to learn about and discuss the latest developments in artificial intelligence and machine learning. Through workshops, guest speakers, and networking events, the club aims to educate and inspire its members about the potential applications of AI and ML in business and other fields.
MIT Department of Physics
Physics
The MIT Physics Department is committed to excellence in research and education. We are also committed to continuously improving the working environment for our students, faculty, and staff through our Physics Community Values and Physics Values Committee.
The Department has about 100 faculty, 190 undergraduate majors, and 270 graduate students. Our research falls into four primary areas:
The Impact of chatGPT on Physics Education (2023) - Prof. Max Tegmark (MIT)
MIT News
News
AI model speeds up high-resolution computer vision
Technique enables AI on edge devices to keep learning over time
Learning on the edge
System brings deep learning to “internet of things” devices
Robust artificial intelligence tools to predict future cancer
MIT Professional Education
PE
MIT’S GATEWAY TO NON-DEGREE PROGRAMS FOR WORKING PROFESSIONALS
MIT Professional Education provides continuing education courses and lifelong learning opportunities for science, engineering, and technology professionals at all levels, from around the world. Worthy of note is that MIT professors and lecturers lead and teach all MIT Professional Education offerings. Some of our programs have a long history, others are relatively new.
Applied Generative AI for Digital Transformation
Applied Generative AI for Digital Transformation
edX
edX
edX is the online learning platform from world-leading digital education company 2U, Inc. edX was founded by Harvard and MIT as an experiment to make the world’s best education available to everyone.
Today, as part of 2U, edX connects over 86 million people worldwide with online learning that delivers real professional progress across nearly every career discipline, from artificial intelligence and robotics to sustainability and public health. Together with universities and organizations at the forefront of their fields, edX offers thousands of job-relevant programs designed to give every ambitious learner a path to achievement.
MITx: Probability - The Science of Uncertainty and Data
MITx: Introduction to Computational Thinking and Data Science
MIT Sloan School of Management: Artificial Intelligence: Implications for Business Strategy
MITx: Introduction to Computer Science and Programming Using Python
MITx: Computational Thinking for Modeling and Simulation
Adaptive Markets: Financial Market Dynamics and Human Behavior
MITx: Machine Learning with Python: from Linear Models to Deep Learning
MITx: Understanding the World Through Data
Electrical Engineering and Computer Science
EECS
The Department of Electrical Engineering and Computer Science is the largest department at MIT, annually preparing hundreds of graduate and undergraduate students for career leadership in fields such as academia, research, and the high-technology industry. Part of both the Schwarzman College of Computing and the School of Engineering, MIT EECS consistently tops the U.S. News & World Report and other college rankings and is widely recognized for its world-class faculty, who provide outstanding education and conduct innovative and award-winning research.
Introduction To Machine Learning
The Human Intelligence Enterprise
Machine Vision
AI 101
Knowledge-Based Applications Systems
Artificial Intelligence
Machine Learning For Healthcare
Ethics For Engineers: Artificial Intelligence
Introduction To Computational Thinking With Julia, With Applications To Modeling The COVID-19 Pandemic
MicroMasters program in Statistics and Data Science.
MicroMasters
This MicroMasters® program in Statistics and Data Science (SDS) was developed by MITx and the MIT Institute for Data, Systems, and Society (IDSS). It is a multidisciplinary approach comprised of four online courses and a virtually proctored exam that will provide you with the foundational knowledge essential to understanding the methods and tools used in data science, and hands-on training in data analysis and machine learning. You will dive into the fundamentals of probability and statistics, as well as learn, implement, and experiment with data analysis techniques and machine learning algorithms. This program will prepare you to become an informed and effective practitioner of data science who adds value to an organization.
Machine Learning with Python: from Linear Models to Deep Learning
MIT Media Lab
Media
The Media Lab is an interdisciplinary creative playground rooted squarely in academic rigor, comprising dozens of research groups, initiatives, and centers working collaboratively on hundreds of projects. We focus not only on creating and commercializing transformational future technologies but also on their potential to impact society for good.
Our diverse community of students, researchers, faculty, and staff seeks to continually transform ideas into impactful new applications, fields, and movements by exploring imaginatively, experimenting iteratively, collaborating playfully, and analyzing critically. We will create opportunities for others around the world to engage in their creative explorations to envision better lives, communities, and environments.
Alex ‘Sandy’ Pentland
Andrew Lippman
Joseph Jacobson
Tod Machover
Deb Roy
Ramesh Raskar
Deblina Sarkar
Mitchel Resnick
Rosalind W. Picard
Pattie Maes
Priming users with different mental models of an AI’s motives significantly influences their perception of the AI’s trustworthiness, empathy, and performance
AI + Ethics Curricula for Middle School Youth: Lessons Learned from Three Project‑Based Curricula
Using Generative AI to cultivate positive emotions and mindsets for self-development and learning
AI-generated characters for supporting personalized learning and well-being
MIT Laboratory for Financial Engineering
LFE
The MIT Laboratory for Financial Engineering (LFE) is a research center created as a partnership between academia and industry, designed to support and promote research in financial engineering and computational finance.
The principal focus of the LFE is the quantitative analysis of financial markets using mathematical, statistical, and computational models and methods. The goal of LFE is not only to spur academic advances in financial engineering, but also to reach out to students, industry professionals, regulators, and policymakers to support their applications of financial technology in practical settings.
Generative AI Applications: Andrew Lo
Linguistics and Philosophy
Linguistics
The MIT Linguistics Group has been engaged in the study of language since the 1950’s, and the first class of PhD students was admitted in 1961. Our research aims to discover the rules and representations underlying the structure of particular languages and what they reveal about the general principles that determine the form and development of language in the individual and the species. The program covers the traditional subfields of linguistics (phonetics, phonology, morphology, syntax, semantics, and psycholinguistics) as well as interfaces with philosophy and logic, speech science and technology, computer science and artificial intelligence, and study of the brain and cognition.
Abby Everett Jaques
MIT Initiative on the Digital Economy (IDE)
IDE
Examining how people and businesses work, interact, and prosper.
The MIT Initiative on the Digital Economy (IDE) is a team of visionary, internationally recognized thought leaders and researchers examining how people and businesses work, interact, and will ultimately prosper in a time of rapid digital transformation.
Technology advances quickly, yet organizations and skills tend to move at a slower pace. In the coming decades, the divide between swiftly evolving technology and the slower pace of human development will grow wider as exponential improvements in artificial intelligence, robotics, networks, analytics, and digitization affect more and more of the economy and society.
MIT Open Learning
OL
The mission of Open Learning is to transform teaching and learning at MIT and around the globe through the innovative use of digital technologies.
Mission-Focused
We are committed to our collective mission first and foremost. We align our work, priorities, and strategies with those of the Institute. We steward our collective resources, and leverage our capabilities and capacities for the greatest impact.
MIT GenAI Summit Live Webcast 2023
Generative AI Shaping The Future Keynote: Refik Anadol
Full MIT Generative AI Week 2023 Playlist (55 Video Presentations)
Generative AI Demystified: What It Really Means for Business
Finding Transformation Opportunities With Generative AI
MIT-Amazon Science Hub
Science Hub
The Science Hub is a collaboration launched by MIT and Amazon in October 2021. Hosted by the MIT Schwarzman College of Computing, the Hub is designed to connect researchers across disciplines, generate new computing and AI tools and technologies, and build an inclusive community to ensure that the benefits of our research are widely shared.
New AI model could streamline operations in a robotic warehouse
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
CSAIL
MIT’s Computer Science and Artificial Intelligence Laboratory pioneers research in computing that improves the way people work, play, and learn.
We focus on developing fundamental new technologies, conducting basic research that furthers the field of computing, and inspiring and educating future generations of scientists and technologists.
Already a major part of everyday life, computing will become more and more integrated into human experience over the next 50 years. CSAIL will be a driver of this change, attracting brilliant, original thinkers who will dream up technological advances that truly improve our collective existence.
Ainesh Bakshi
Alaa Maalouf
Alan Edelman
Albert R. Meyer
Aleksander Madry
Alexander Amini
Amar Gupta
Amy Fox
Anand Natarajan
Anantha Chandrakasan
Anant Agarwal
Andrei Barbu
Andrew Lo
Ankur Moitra
Arthur Berger
Arvind Mithal
Ashay Athalye
Costis Daskalakis
Lingling Fan
Ben Lengerich
Show 149 moreMachine Learning in Business
MIT CSAIL Researcher Explains: AI Image Generators
Data Curation for LLMs
Label Errors and Confident Learning
Interpretability in Data-Centric ML
Intro to Data-Centric AI: Data Privacy and Security (2023) (link to full course)
Class Imbalance, Outliers, and Distribution Shift
Dataset Creation and Curation
Towards a Theory of Mind for Artificial Intelligence Agents
Data-Centric AI vs. Model-Centric AI
Encoding Human Priors: Data Augmentation and Prompt Engineering
Advanced Confident Learning, LLM and GenAI applications
Taking AI to School: A Conversation With MIT’s Anant Agarwal (June 2023)
AI Senses People Through Walls
Using AI to protect against AI image manipulation
The Future of Robot Learning: MIT 6.S191
Growing or Compressing Datasets
Data-centric Evaluation of ML Models
OpenAI and MIT - Aleksander Madry | Collective Intelligence Ep 1
MIT Embodied Intelligence
EI
Our goal is to understand the nature of intelligent behavior in the physical world, through the study of human intelligence and the design and implementation of intelligent robots. We bring expertise in perception, sensing, language, learning and planning, and have the objective of integrating these disciplines to make physical agents with human-like intelligence.
CSAIL Embodied Intelligence
Seminar: Towards Large Behavior Models: Versatile and Dexterous Robots via Supervised Learning
MIT Center for Advanced Virtuality
CAV
The MIT Center for Advanced Virtuality pioneers innovative experiences using technologies of virtuality. Such technologies, ranging from Virtual Reality (VR) to Cinematic Reality (CR) and beyond, all use computing to construct imaginative experiences atop our physical world. It is crucially important to create and deploy such technologies effectively since they are now used every day to communicate, express, learn, play, and work.
Responsible AI for Social Empowerment and Education
RAISE
Artificial Intelligence is transforming our personal and professional lives. Around the world, governments, companies, and institutions are proclaiming that we are entering the “era of AI” with the rapid development of intelligent devices that can recognize faces and interact via speech, robots that can work alongside people to help automate warehouse logistics and manufacture goods, algorithms that can generate novel photo realistic images and music, computers that can provide decision support to clinicians to help detect cancer more reliably, and so much more. In every feat that AI can do, however, there lurks potential for misuse and the spreading of inequity. AI education can help change that.
Evan Patton
Xiajie Zhang
Mary Cate Gustafson Quiett
Christina Bosch
Cynthia Breazeal
Safinah Ali
Eric Klopfer
David Kim
Selim Tezel
Randi Williams
Huili Chen
Sarah Wharton
Jeff Freilich
Daniella DiPaola
Hae Won Park
Hal Abelson
RAISE (Responsible AI for Social Empowerment and Education)
MIT Sloan Executive Education
ExecEd
MIT Sloan Executive Education’s non-degree executive courses are led by MIT Sloan faculty and provide a targeted and flexible means to futureproof your business and your career. Fueled by cutting-edge research and aided by the latest technology, our offerings include 90+ in-person and online courses offered throughout the year, as well as custom programs for organizations, and Executive Certificates.
Artifical Intelligence in Healthcare
Artificial Intelligence: Implications for Business Strategy
MIT Press
MIT Press
Established in 1962, the MIT Press is one of the largest and most distinguished university presses in the world and a leading publisher of books and journals at the intersection of science, technology, art, social science, and design. MIT Press books and journals are known for their intellectual daring, scholarly standards, interdisciplinary focus, and distinctive design.
The MIT Press is committed to responsible and ethical conduct in our workplace. To support the Press’s mission to push the boundaries of scholarly publishing and advance knowledge, and in alignment with MIT’s policies and procedures, we embrace a code of conduct that governs all of our collaborations.
Measuring Autonomy for Life-Like AI
McGovern Institute for Brain Research
McGovern
The mission of the McGovern Institute is to understand the brain and to apply that knowledge to improve human health and well-being. To accomplish these goals, we study the brain at many levels, across multiple disciplines, and we collaborate with academic, clinical, and industry partners around the world to challenge and probe the unknown.
James DiCarlo
Brains, Minds And Machines Summer Course
Aeronautics and Astronautics
AeroAstro
In the MIT Department of Aeronautics and Astronautics, we look ahead by looking up. At its core, aerospace empowers connection — interpersonal, international, interdisciplinary, and interplanetary. We seek to foster an inclusive community that values technical excellence, and we research and engineer innovative aerospace systems and technologies that have a world-changing impact. We educate the next generation of leaders, creative engineers, and entrepreneurs who will push the boundaries of the possible to shape the future of aerospace. We do these things while holding ourselves to the highest standards of integrity and ethical practice. Working together with our partners in the public and private sectors, we aim to expand the benefits of aerospace to create a more sustainable environment, strengthen global security, contribute to a prosperous economy, and explore other worlds for the betterment of humankind.
Cognitive Robotics
Ethics For Engineers: Artificial Intelligence
MIT Schwarzman College of Computing
Schwarzmann
The mission of the MIT Stephen A. Schwarzman College of Computing is to address the opportunities and challenges of the computing age — from hardware to software to algorithms to artificial intelligence — by transforming the capabilities of academia in three key areas:
MIT GenAI Summit Live Webcast 2023
Generative AI Shaping The Future Keynote: Refik Anadol
Full MIT Generative AI Week 2023 Playlist (55 Video Presentations)
Media Arts and Sciences
MAS
The Media Lab is a community of designers, researchers, and inventors who work together as members of research teams, doing things that conventional wisdom says can’t or shouldn’t be done. The approximately 400 projects underway at the Lab are as varied as the students who conduct them: from tools for learning and expression, to innovative devices for human adaptation and augmentation, to new modes of transportation for tomorrow’s smart cities.
Affective Computing
Institute for Artificial Intelligence and Fundamental Interactions (IAIFI)
IAIFI
The NSF AI Institute for Artificial Intelligence and Fundamental Interactions (IAIFI, pronounced /aɪ-faɪ/) is one of the inaugural NSF AI research institutes. The IAIFI is enabling physics discoveries and advancing foundational AI through the development of novel AI approaches that incorporate first principles from fundamental physics. The goal of the IAIFI is to advance physics knowledge and galvanize AI research innovation.
MIT App Inventor
App Inventor
MIT App Inventor is an intuitive, visual programming environment that allows everyone – even children – to build fully functional apps for Android phones, iPhones, and Android/iOS tablets. Those new to MIT App Inventor can have a simple first app up and running in less than 30 minutes. And what’s more, our blocks-based tool facilitates the creation of complex, high-impact apps in significantly less time than traditional programming environments. The MIT App Inventor project seeks to democratize software development by empowering all people, especially young people, to move from technology consumption to technology creation.
App Building Guides for the Youth Mobile Power Series
Introduction to Machine Learning: Image Classification
Fake Voices: The Ethics of Deepfakes
Comparative Media Studies (CMS)
CMS
We develop thinkers who understand the dynamics of media change and can apply their insights to contemporary problems. We cultivate practitioners, scholars, and artists who can work in multiple forms of contemporary media. Our students and research help shape the future as critical and visionary partners at a time of rapid transformation.
At CMS/W, we are devoted to understanding the ways that media technologies and their uses can enrich the lives of individuals locally, across the U.S., and globally.
Justin Reich
The MIT Abdul Latif Jameel Clinic for Machine Learning in Health
Jameel Clinic
The Jameel Clinic draws on MIT’s unique expertise in technology and industry to drive the creation and adoption of high-precision, affordable, and scalable machine learning technologies, and solutions across three key areas — clinical AI, drug discovery, and epidemiology.
MIT: Artificial Intelligence in Pharma and Biotech
AI Cures Conference: April 1 2024
MIT OpenCourseWare
OCW
Since 2001, MIT OpenCourseWare has been creating new opportunities for millions of learners and educators, sharing Open Educational Resources (OER) from MIT and helping to lead a global revolution in free access to knowledge.
MIT OpenCourseWare continues to build on this foundation. With a new web platform, ever-growing content, and collaborations across the vibrant open education ecosystem, we’re creating a world of more equitable and inclusive education for all.
Mathematics Of Big Data And Machine Learning
Day of AI | Machine Learning For Inverse Graphics
RAISE (Responsible AI for Social Empowerment and Education)
Media Literacy in the Age of Deepfakes
Principles Of Autonomy And Decision Making
Class 3: Artificial Intelligence in Finance
Class 2: FinTech and Artificial Intelligence, Machine Learning, and Deep Learning
MIT Artifical Intelligence Course Lectures Playlist (2010)
AI 101 with Brandon Leshchinskiy
Artificial Intelligence and Machine Learning
Social and Ethical Responsibilities of Computing (SERC)
Exploring Fairness in Machine Learning for International Development | Exploring Fairness In Machine Learning For International Development
MIT Data to AI Group
DAI
The Data to AI group in the Laboratory for Information and Decision Systems focuses on how to build large scale AI systems that work alongside humans. These systems have to continually learn from the data, generate predictions from them and seamlessly integrate with human efforts and interactions. The group develops foundational algorithms, abstractions and systems to enable these three tasks at scale. The group’s work as a result is at the intersection of statistics and machine learning, human data interaction and distributed systems. Algorithms, systems and open source software developed by the group are applied across a broad range of use cases that come from financial, medical, cybersecurity and education industry.
ATMSeer: Increasing Transparency and Controllability in Automated Machine Learning
Ballet: A lightweight framework for open-source, collaborative feature engineering
MIT Corporate Relations
Corporate Relations
MIT Corporate Relations aids and directs companies interested in multidisciplinary involvement with the Institute. Its expert staff works with MIT senior administration, faculty, and company executives to structure and define individualized alliances that mutually benefit the company and MIT.
MIT Corporate Relations also offers industry access to MIT through two integrated programs, the MIT Industrial Liaison Program (ILP) and MIT Startup Exchange.
2020 Frontiers of AI:ML - Aleksander Madry
Department of Materials Science and Engineering
Material Science
DMSE is home to the world’s premier program focused on materials science and engineering—the study of matter and how it is made. Our faculty, staff, and students undertake interdisciplinary materials projects that draw on fundamental sciences in pursuit of beneficial engineering solutions. From novel manufacturing methods to high-capacity batteries, their work has resulted in powerful discoveries and innovations that positively influence virtually every corner of society.
Ju Li
MIT-IBM Watson AI Lab
Watson
The MIT-IBM Watson AI Lab is a community of scientists from MIT and IBM Research dedicated to pushing the frontiers of artificial intelligence and translating breakthroughs into real-world impact. Founded in 2017, the Lab works with industry to translate fundamental science into applications that solve immediate problems in the business world and beyond. The Lab currently manages a research portfolio of more than 80 projects, with an emphasis on data-driven, deep learning approaches to understanding language and the visual world and techniques for making large-scale AI systems more efficient and robust. The Lab is also developing AI systems for healthcare and a variety of decision-making applications. In all of its work, the Lab is committed to building trustworthy and socially responsible AI systems.
Vikash Mansinghka
Beyond AI Exposure: Which Tasks are Cost-Effective to Automate with Computer Vision?
MIT Industrial Liaison Program
ILP
The MIT Industrial Liaison Program (ILP) and MIT Startup Exchange is a membership-based program for large organizations interested in long-term, strategic relationships with MIT. We engage with organizations from around the globe – in any sector – that are concerned with emerging research- and education-driven results that will be transformative.
Generative AI and Its Business Impact: March 14, 2024
Massachusetts Institute of Technology
MIT
Founded to accelerate the nation’s industrial revolution, MIT is profoundly American. With ingenuity and drive, our graduates have invented fundamental technologies, launched new industries, and created millions of American jobs. At the same time, and without the slightest sense of contradiction, MIT is profoundly global. Our community gains tremendous strength as a magnet for talent from around the world. Through teaching, research, and innovation, MIT’s exceptional community pursues its mission of service to the nation and the world.
MIT GenAI Summit Live Webcast 2023
Generative AI Shaping The Future Keynote: Refik Anadol
Full MIT Generative AI Week 2023 Playlist (55 Video Presentations)
MIT xPro
xPro
Technology is accelerating at an unprecedented pace causing disruption across all levels of business. Tomorrow’s leaders must demonstrate technical expertise as well as leadership acumen in order to maintain a technical edge over the competition while driving innovation in an ever-changing environment.
MIT uniquely understands this challenge and how to solve it with decades of experience developing technical professionals. MIT xPRO’s online learning programs leverage vetted content from world-renowned experts to make learning accessible anytime, anywhere. Designed using cutting-edge research in the neuroscience of learning, MIT xPRO programs are application focused, helping professionals build their skills on the job.
Designing and Building AI Products and Services
MIT Deep Learning
Deep Learning
MIT’s introductory program on deep learning methods with applications to natural language processing, computer vision, biology, and more! Students will gain foundational knowledge of deep learning algorithms, practical experience in building neural networks, and understanding of cutting-edge topics including large language models and generative AI. Program concludes with a project proposal competition with feedback from staff and panel of industry sponsors. Prerequisites assume calculus (i.e. taking derivatives) and linear algebra (i.e. matrix multiplication), we’ll try to explain everything else along the way! Experience in Python is helpful but not necessary. Listeners are welcome!
Xtreme Transistors Group
Xtreme
Our research group at MIT investigates new transistor designs with the goal of pushing the frontiers of electronics to higher frequencies, higher speed, smaller size, lower power consumption, higher operating temperature or to switch electrical power or amplify electrical signals at higher power levels. This is relevant for applications in computation, communications, signal processing, and energy management. Our research currently emphasizes III-V and III-N compound semiconductors but we are also interested in newer materials such as diamond.
Jesus del Alamo
Health Sciences and Technology
HS&T
Founded in 1970, the Harvard-MIT Program in Health Sciences and Technology (HST) is one of the world’s oldest interdisciplinary educational programs focused on translational medical science and engineering.
The program is an inter-institutional collaboration between MIT, Harvard, and local teaching hospitals, dedicated to fostering academic excellence, scientific rigor, and clinical expertise.
Civil and Environmental Engineering
CEE
In the MIT Department of Civil and Environmental Engineering, we are driven by a simple truth: we only have one Earth to call home. Our intellectual focus is on the human-built environment and the complex infrastructure systems that it entails, as well as the man-made effect on the natural world. We seek to foster an inclusive community that pushes the boundaries of what is possible to shape the future of civil and environmental engineering. Our goal is to educate and train the next generation of researchers and engineers, driven by a passion to positively impact our society, economy, and our planet.
Ethics For Engineers: Artificial Intelligence
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