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J-WEL AI Knowledgebase
MIT's AI Resources
Empowering You to Engage, Explore, and Excel with the AI Revolution
MIT offers a diverse array of AI resources, including research papers, online courses, and seminar recordings, many of which are freely accessible. Topics range from AI in finance and healthcare to ethics and machine learning techniques, catering to both academic and industry professionals. The resources are often associated with MIT faculties and labs, such as the MIT Sloan School of Management and CSAIL. While many offerings are open access, some, like certificate courses, are behind a paywall. The content spans various formats, from video presentations to research publications, and covers cutting-edge AI themes like generative AI, data-centric AI, and AI-driven business strategies.
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To Be a Responsible AI Leader, Focus on Being Responsible
MIT Sloan Management Review
New research shows that although leaders agree that responsible AI should be a top management concern, few have prioritized such initiatives.
AI and ML Accelerator Survey and Trends
MIT Lincoln Laboratory
This paper updates the survey of AI accelerators and processors from past three years. This paper collects and summarizes the current commercial accelerators that have been publicly announced with peak performance and power consumption numbers. Oct 2022
How should AI-generated content be labeled?
MIT Sloan School of Management
In late October, President Joe Biden issued a wide-ranging executive order on AI security and safety. The order includes new standards and best practices for clearly labeling AI-generated content, in part to help Americans determine whether communications that appear to be from the government are authentic. Nov 2023
AI + Ethics Curricula for Middle School Youth: Lessons Learned from Three Project‑Based Curricula
MIT Media Lab
This paper presents three AI literacy curricula designed to engage middle school students in learning about AI through hands-on activities, embedded ethics, and accessible resources, equipping them with the critical skills needed to navigate an AI-driven world.
AI model speeds up high-resolution computer vision
MIT News
News Article: The system could improve image quality in video streaming or help autonomous vehicles identify road hazards in real-time.
AI Is Helping Companies Redefine, Not Just Improve, Performance
MIT Sloan Management Review
Research on organizations’ use of artificial intelligence reveals how they can apply the technology to redefine strategic measurement and KPIs.
Class Imbalance, Outliers, and Distribution Shift
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
This lecture covers three common problems in real-world ML data: class imbalance, outliers, and distribution shift.
Adaptive Markets: Financial Market Dynamics and Human Behavior
edX
A completely new way of thinking about financial markets, institutions, and innovation that reconciles human behavior with market efficiency using concepts from evolutionary biology, cognitive neuroscience, and artificial intelligence.
Technique enables AI on edge devices to keep learning over time
MIT News
News Article: Machine-learning models can efficiently and continuously learn from user data on edge devices like smartphones.
Generative AI Demystified: What It Really Means for Business
MIT Sloan Management Review
MIT Open Learning
This session lays the groundwork for GenAI, including what it is and isn’t, how it relates to current and past technologies, and what it takes to make good decisions about its use. (2024! VIDEO)
AI Unleashed: Tackle Data Management Hurdles for Success
MIT Sloan Management Review
Artificial intelligence offers the potential to boost productivity and solve key business problems; but for many organizations, effective data management remains a top barrier to successful AI adoption and use. | Artificial intelligence offers the potential to boost productivity and solve key business problems. (2024 VIDEO)
Day of AI | Machine Learning For Inverse Graphics
MIT OpenCourseWare
This resource is to support teachers and educators to run Day of AI activities in their classrooms through curriculum packages and teacher training, all of which is available at no cost to participants. Spring 2021
Three Lessons From Chatting About Strategy With ChatGPT
MIT Sloan Management Review
When Geoffrey Hinton, a pioneer of deep learning, quit Google recently, he made it clear that he is worried about the risks of artificial intelligence. May 2023
AI Detectors Don’t Work. Here’s What to Do Instead.
MIT Sloan School of Management
As AI tools like ChatGPT gain popularity on campus, instructors face new questions around academic integrity and AI.
Dataset Creation and Curation
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
Creating a dataset for supervised learning requires the collection of examples and labels.
Making AI Work: Machine Intelligence for Business and Society
MIT Sloan School of Management
This six-week online course from MIT Sloan and MIT Schwarzman College of Computing provides a comprehensive approach to understanding the impact of AI on business and society, equipping participants with the skills to identify and mitigate unintended consequences, while leveraging AI’s potential for competitive advantage and inclusive prosperity.
Practical Strategies for Teaching with AI
MIT Sloan School of Management
This guide offers practical strategies to help MIT Sloan faculty responsibly integrate generative AI tools into their teaching.
Class 2: FinTech and Artificial Intelligence, Machine Learning, and Deep Learning
MIT OpenCourseWare
This course is for students wishing to explore the ways in which new technologies are disrupting the financial services industry—driving material change in business models, products, applications and customer user interface.
Machine Learning with Python: from Linear Models to Deep Learning
MicroMasters program in Statistics and Data Science.
An in-depth introduction to the field of machine learning, from linear models to deep learning and reinforcement learning, through hands-on Python projects. – Part of the MITx MicroMasters program in Statistics and Data Science.
Deep Learning Basics: Introduction and Overview
An introductory lecture for MIT course 6.S094 on the basics of deep learning including a few key ideas, subfields, and the big picture of why neural networks have inspired and energized an entire new generation of researchers. For more lecture videos on deep learning, reinforcement learning (RL), artificial intelligence (AI & AGI), and podcast conversations, visit our website or follow TensorFlow code tutorials on our GitHub repo.
Towards a Theory of Mind for Artificial Intelligence Agents
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
In the growing fervor around artificial intelligence (A.I.) old questions have resurfaced regarding its potential to achieve human-like intelligence and consciousness. July 24, 2023
The Human Intelligence Enterprise
Electrical Engineering and Computer Science
This course analyzes seminal work directed at the development of a computational understanding of human intelligence, such as work on learning, language, vision, event representation, commonsense reasoning, self reflection, story understanding, and analogy. From 2019
App Building Guides for the Youth Mobile Power Series
MIT App Inventor
MIT App Inventor and YR Media (formerly Youth Radio) have teamed up to present the Youth Mobile Power series. YR teens produce stories highlighting how young people use their phones in surprising and powerful ways. MIT App Inventor has developed a series of App Building Guides to help you get busy. Includes guides and corresponding experience levels.
MIT: Artificial Intelligence in Pharma and Biotech
The MIT Abdul Latif Jameel Clinic for Machine Learning in Health
This six-week online course from MIT Sloan provides insights into the current state and potential applications of AI and machine learning in the pharmaceutical and biotech industry, enabling participants to understand how these technologies can be leveraged for drug discovery, clinical trials, and patient stratification, ultimately helping them stay ahead in an industry undergoing rapid innovation.
OpenAI and MIT - Aleksander Madry | Collective Intelligence Ep 1
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
ThomasTJoshi is joined by Aleksander Madry from OpenAI, on-leave from MIT, who has held the Director of MIT’s Center for Deployable Machine Learning, Co-Lead of MIT AI Policy Forum, and Professor of MIT CSAIL. He has delivered testimonies to Senate Subcommittee hearings on topics ranging from Human Rights and the Law to AI Alignment.
Podcast: In Machines We Trust
MIT Technology Review
The award-winning podcast In Machines We Trust thoughtfully examines the far-reaching impact of artificial intelligence on our daily lives.
Using Artificial Intelligence to Thrive in Challenging Times
MIT Sloan Management Review Connections
This webinar will explore how organizations can begin AI journeys that will help them not only survive — but thrive — in turbulent times. (2020 VIDEO)
Full MIT Generative AI Week 2023 Playlist (55 Video Presentations)
MIT Schwarzman College of Computing
Massachusetts Institute of Technology
MIT Open Learning
MIT Generative AI Week, featuring the “MIT Generative AI: Shaping the Future” symposium on November 28, 2023, and four thematic symposia on November 29-30, brought together MIT experts, researchers, and diverse stakeholders to explore the foundations, applications, and ethical implications of generative AI across various domains, including education, health, creativity, and commerce, through keynotes, panel discussions, demonstrations, and interactive sessions. All 55 presentations are included here.
Preparing Your Organization for a Generative Future
MIT Sloan Management Review
Although GenAI promises to transform many processes, companies also need to balance the long-term promise with current capabilities. (Jan 2024! VIDEO)
Robust artificial intelligence tools to predict future cancer
MIT News
Researchers created a risk-assessment algorithm that shows consistent performance across datasets from US, Europe, and Asia. MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Jameel Clinic demonstrated a deep learning system to predict cancer risk using just a patient’s mammogram. Jan 2021
Strategic Alignment With AI and Smart KPIs
MIT Sloan Management Review
When organizations create forward-looking smart KPIs with AI, they see increased strategic alignment.
Responsible AI Enables the Kind of Innovation That Matters
MIT Sloan Management Review
MIT Sloan Management Review and Boston Consulting Group (BCG) have assembled an international panel of AI experts that includes academics and practitioners to help us gain insights into how responsible artificial intelligence (RAI) is being implemented in organizations worldwide.
Brains, Minds And Machines Summer Course
McGovern Institute for Brain Research
This course explores the problem of intelligence—its nature, how it is produced by the brain and how it could be replicated in machines—using an approach that integrates cognitive science, which studies the mind; neuroscience, which studies the brain; and computer science and artificial intelligence, which study the computations needed to develop intelligent machines. Summer 2015
Machine Vision
Electrical Engineering and Computer Science
This course is an introduction to the process of generating a symbolic description of the environment from an image. From 2020
What Leaders Should Know About Measuring AI Project Value
MIT Sloan Management Review
What Leaders Should Know About Measuring AI Project Value. Most AI/machine learning projects report only on technical metrics that don’t tell leaders how much business value could be delivered. To prevent project failures, press for business metrics instead.
How Encouraging AI Use Will Benefit Your Organization
MIT Sloan Management Review
When individuals derive value from AI, their organizations benefit as well. (Nov 23 2022, VIDEO)
AI 101
Electrical Engineering and Computer Science
The workshop starts with a summary of key concepts in AI, followed by an interactive exercise where participants train their own algorithm. | Machine vision. Data wrangling. Reinforcement learning. What do these terms even mean? In AI 101, MIT researcher Brandon Leshchinskiy offers an introduction to artificial intelligence that’s designed specifically for those with little to no background in the subject. Fall 2021
ATMSeer: Increasing Transparency and Controllability in Automated Machine Learning
MIT Data to AI Group
To relieve the pain of manually selecting machine learning
algorithms and tuning hyperparameters, automated machine
learning (AutoML) methods have been developed to automat-
ically search for good models.
Exploring Fairness in Machine Learning for International Development | Exploring Fairness In Machine Learning For International Development
MIT OpenCourseWare
In an effort to build the capacity of the students and faculty on the topics of bias and fairness in machine learning (ML) and appropriate use of ML, the MIT CITE team developed capacity-building activities and material. | In an effort to build the capacity of the students and faculty on the topics of bias and fairness in machine learning (ML) and appropriate use of ML, the MIT CITE team developed capacity-building activities and material. Spring 2020
Cognitive Robotics
Aeronautics and Astronautics
This is a class about applying autonomy to real-world systems. The overarching theme uniting the many different topics in this course will center around programming a cognitive robotic. This class takes the approach of introducing new reasoning techniques and ideas incrementally. From 2016
Tackling AI’s Climate Change Problem
MIT Sloan Management Review
The AI industry could soon be one of the largest contributors to carbon emissions, if current trends continue.
Cyber Network Data Processing; AI Data Architecture
MIT Lincoln Laboratory
This lecture started with anomaly detection and data conditioning in machine learning and later continued to explore the AI data architecture in data processing.
Getting Started with AI-Enhanced Teaching: A Practical Guide for Instructors
MIT Sloan School of Management
Welcome to our guide to leveraging generative AI for teaching at MIT Sloan. The fundamentals of great teaching haven’t changed with the emergence of new AI tools.
Beyond AI Exposure: Which Tasks are Cost-Effective to Automate with Computer Vision?
MIT-IBM Watson AI Lab
The faster AI automation spreads through the economy, the more profound its potential impacts, both positive (improved productivity) and negative (worker displacement). (2023/2024) Working Paper
Knowledge-Based Applications Systems
Electrical Engineering and Computer Science
This course covers the development of programs containing a significant amount of knowledge about their application domain. The course includes a brief review of relevant AI techniques; case studies from a number of application domains, chosen to illustrate principles of system development; a discussion of technical issues encountered in building a system, including selection of knowledge representation, knowledge acquisition, etc.; and a discussion of current and future research. The course also provides hands-on experience in building an expert system (term project) From 2005
Artificial Intelligence: Implications for Business Strategy
MIT Sloan Executive Education
This six-week online program from MIT Sloan and CSAIL provides business leaders with a practical understanding of AI technologies, such as machine learning, natural language processing, and robotics, and their potential applications in business, enabling them to strategically implement AI solutions and transform their organizations for the future.
Mathematics Of Machine Learning
Mathematics
Broadly speaking, Machine Learning refers to the automated identification of patterns in data. As such it has been a fertile ground for new statistical and algorithmic developments. A Course from 2015
AI-generated characters for supporting personalized learning and well-being
MIT Media Lab
Advancements in machine learning have recently enabled the hyper-realistic synthesis of prose, images, audio and video data, in what is referred to as artificial intelligence (AI)-generated media. These techniques offer novel opportunities for creating interactions with digital portrayals of individuals that can inspire and intrigue us.
The future of AI’s impact on society (Dec 2019)
MIT Technology Review
As artificial intelligence continues its rapid evolution, what influence do humans have?
Artificial Intelligence
Electrical Engineering and Computer Science
This course introduces students to the basic knowledge representation, problem solving, and learning methods of artificial intelligence. From 2010
Data Curation for LLMs
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
The lecture video and slides are linked above; lecture notes + lab assignment coming soon!
MIT Sloan School of Management: Artificial Intelligence: Implications for Business Strategy
edX
This online course from MIT Sloan and CSAIL equips managers, executives, and business leaders with the knowledge and skills to strategically implement AI technologies, such as machine learning, natural language processing, and robotics, into their organizations to drive innovation and efficiency.
Podcast: The MIT Artificial Intelligence Podcast
MIT Laboratory for Information and Decision Systems (LIDS)
Podcast: MIT research scientist Lex Fridman hosts a great podcast on artificial intelligence.
Label Errors and Confident Learning
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
If you’ve ever used datasets like CIFAR, MNIST, ImageNet, or IMDB, you likely assumed the class labels are correct.
Fake Voices: The Ethics of Deepfakes
MIT App Inventor
Educators can use this lesson to introduce students to coding, provide a basic understanding of artificial intelligence and machine learning, and prompt students to predict the possible future use and abuse of synthetic media in society.
Individual AI Use Can Benefit Organizations
MIT Sloan Management Review
When initially asked, 66% of the executives surveyed by MIT Sloan Management Review and Boston Consulting Group (BCG) reported no or minimal use of AI in their jobs. (NOV 2022. VIDEO)
Ballet: A lightweight framework for open-source, collaborative feature engineering
MIT Data to AI Group
Feature engineering source code is submitted incrementally and validated using
extensive software tests and a streaming logical feature selection algorithm
Mathematics Of Big Data And Machine Learning
MIT OpenCourseWare
This course introduces the Dynamic Distributed Dimensional Data Model (D4M), a breakthrough in computer programming that combines graph theory, linear algebra, and databases to address problems associated with Big Data.
Generative AI and Its Business Impact: March 14, 2024
MIT Industrial Liaison Program
Uncover the power of Generative AI in shaping the future of industries. Our expert speakers from MIT and industry will delve into its technology, applications, potential, and real-world impact on businesses.
Seminar: Towards Large Behavior Models: Versatile and Dexterous Robots via Supervised Learning
MIT Embodied Intelligence
Recent advances in machine learning have transformed multiple AI-related fields. Notably, robust general-purpose language and vision models are fast becoming reality and these new capabilities have already begun making their way into consumer-facing technologies where they affect the lives of many millions of people. These same underlying advancements also portend sea-change in robotics.
Introduction To Computational Thinking With Julia, With Applications To Modeling The COVID-19 Pandemic
Mathematics
Electrical Engineering and Computer Science
This half-semester course introduces computational thinking through applications of data science, artificial intelligence, and mathematical models using the Julia programming language.
Five Key Trends in AI and Data Science for 2024
MIT Technology Review
Generative AI sparkles but needs to deliver value. | Artificial intelligence and data science became front-page news in 2023. The rise of generative AI, of course, drove this dramatic surge in visibility.
This is how AI bias really happens—and why it’s so hard to fix
MIT Technology Review
Bias can creep in at many stages of the deep-learning process, and the standard practices in computer science aren’t designed to detect it.
MITx: Introduction to Computer Science and Programming Using Python
edX
This course, part of a two-course sequence with Introduction to Computational Thinking and Data Science, introduces computer science and programming using Python 3.5 to people with no prior experience, providing a broad overview of topics to demonstrate the possibilities of computation in various careers, while maintaining a challenging and rigorous learning environment.
Artificial Intelligence and Business Strategy
MIT Sloan Management Review
The Artificial Intelligence and Business Strategy initiative explores the growing use of artificial intelligence in the business landscape.
Unsupervised Machine Learning: Unlocking the Potential of Data
MIT Sloan School of Management
This six-week online course from MIT Sloan and MIT Schwarzman College of Computing explores the potential of unsupervised machine learning to unlock valuable insights from previously untapped data, enabling participants to develop tailored AI solutions, build accurate models, and responsibly deploy ML within their organizations.
Finding Transformation Opportunities With Generative AI
MIT Sloan Management Review
MIT Open Learning
How generative AI can enhance customer and employee experiences, optimize operations, and lead to new business models. 2024! VIDEO)
Pair People and AI for Better Product Demand Forecasting
MIT Sloan Management Review
A new framework helps leaders orchestrate human and AI agents to accurately forecast product demand.
MITx: Computational Thinking for Modeling and Simulation
edX
This course focuses on computational thinking for modeling the physical world, covering topics traditionally viewed as mathematics, such as algebra and calculus, but with an algorithmic approach. Students will learn about representation, decomposition, discretization, and verification, and gain skills in interpolation, numerical integration and differentiation, and solving systems of equations, with the goal of using computers to expand their own thinking.
Adopting AI: Picking the Right Problems to Solve
MIT Sloan Management Review
Executives in most industries have heard about artificial intelligence’s potential to transform their businesses, but many aren’t sure where to start — or how to gain the most value from efforts already underway. (Dec 2020) VIDEO
Are Responsible AI Programs Prepared for Third-Party and Generative AI?
MIT Sloan Management Review
New research from MIT SMR and BCG reveals that most organizations are not prepared for the risks posed by generative AI tools. (Nov 2023)
Principles Of Autonomy And Decision Making
MIT OpenCourseWare
This course surveys a variety of reasoning, optimization and decision making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their application, taken from the disciplines of artificial intelligence and operations research. Course from 2010
AI & Machine Learning Lectures
This page is a collection of select recorded lectures on AI given by Lex Fridman and others. Covering Deep learning, Privacy, Self Driving Cars, etc. All lectures are free and are from 2017-2020.
Interpretability in Data-Centric ML
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
Interpretability is the degree to which a human can understand the cause of a decision of an ML model.
Tiny machine learning design alleviates a bottleneck in memory usage on internet-of-things devices
MIT Hardware Accelerated Neural-Nets Lab
News Article: New technique applied to small computer chips enables efficient vision and detection algorithms without internet connectivity.
Intro to Data-Centric AI: Data Privacy and Security (2023) (link to full course)
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
Machine learning models are sometimes trained on sensitive data, such as healthcare records, and often times, these models are made publicly available, even though the data they are trained on is sensitive and not suitable for release.
Class 3: Artificial Intelligence in Finance
MIT OpenCourseWare
This course is for students wishing to explore the ways in which new technologies are disrupting the financial services industry—driving material change in business models, products, applications and customer user interface.
Use Open Source for Safer Generative AI Experiments
MIT Sloan Management Review
Integrating artificial intelligence into the daily workflow of employees across organizations, from upper management to front-line workers, holds the promise of increasing productivity in tasks such as writing memos, developing software, and creating marketing campaigns. Nov 2023
From the MIT GenAI Summit: A Crash Course in Generative AI
AI (Artificial Intelligence) and ML (Machine Learning) Club
In this talk, Ellie Pavlick provides an overview of generative AI, explaining how language models work, their potential applications, and the significant risks associated with their use, such as hallucination, bias, reward hacking, and lack of interpretability, emphasizing the need for caution and flexibility as the technology rapidly advances.
MIT Hardware Accelerated Neural-Nets Lab
This course: “TinyML and Efficient Deep Learning Computing” by MIT HAN lab tackles this core obstacle. It introduces methods to optimize AI models, ensuring their viability in real-world scenarios. | Large generative models (e.g., large language models, diffusion models) have shown remarkable performances, but their enormous scale demands significant computation and memory resources.
Data-Centric AI vs. Model-Centric AI
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
When you learn Machine Learning in school, a dataset is given to you that is fairly clean & well-curated (e.g. dog/cat images), and your job is to produce the best model for this dataset.
Learning on the edge
MIT News
News Article: A new technique enables AI models to continually learn from new data on intelligent edge devices like smartphones and sensors, reducing energy costs and privacy risks.
Cyber Network Data Processing; AI Data Architecture
MIT Lincoln Laboratory
MIT RES.LL-005 Mathematics of Big Data and Machine Learning, IAP 2020 Instructor: Jeremy Kepner, Vijay Gadepally • MIT RES.LL-005 Mathematics of Big Data.This lecture started with anomaly detection and data conditioning in machine learning and later continued to explore the AI data architecture in data processing.
Ethics of AI Bias
Chemical Engineering
This video aims to delve into the human problems brought out by issues in artificial intelligence, specifically with respect to bias. It is suitable for classroom use or as a standalone video for those who wish to understand the issue more deeply than is conventionally covered. For classroom use, we recommend watching the video (ideally more than once) with book in hand and discussing the issues raised in class
AI Cures Conference: April 1 2024
The MIT Abdul Latif Jameel Clinic for Machine Learning in Health
Large Conference: AI in Medicine: Building on the combined expertise of MIT and MGB in AI and clinical practice, the MIT-MGB AI Cures Conference showcases ongoing collaborative projects in clinical AI, highlighting cutting-edge research and their impact on patient care.
Improve Key Performance Indicators With AI
MIT Sloan Management Review
Organizations that use AI to improve existing KPIs or create new ones realize more business benefits than organizations that adjust their KPIs without AI. (July 2023)
MITx: Machine Learning with Python: from Linear Models to Deep Learning
edX
An in-depth introduction to the field of machine learning, from linear models to deep learning and reinforcement learning, through hands-on Python projects.
Encoding Human Priors: Data Augmentation and Prompt Engineering
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
This lecture covers encoding human priors into machine learning models through data!
MIT: Deep Learning | Introduction to Deep Learning
Amini Lab | Electrical Engineering and Computer Science
This is 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), and we’ll try to explain everything else along the way! Experience in Python is helpful but not necessary. INCL: Slides and Video
Generative AI Applications: Andrew Lo
MIT Laboratory for Financial Engineering
Andrew Lo, Professor, MIT Sloan School of Management, CSAIL, and Director of the MIT Laboratory for Financial Engineering, talks about how AI can impact finance, including whether large language models can provide sound financial advice.
Ethics For Engineers: Artificial Intelligence
Civil and Environmental Engineering
MIT Department of Mechanical Engineering
Nuclear Science and Engineering
Electrical Engineering and Computer Science
Aeronautics and Astronautics
Artificial Intelligence (AI), and the algorithmic judgment at its core, is developing at breakneck speed. This version of the popular Ethics for Engineers course focuses on the ethics issues involved in the latest developments of computer science.
MIT Hardware Accelerated Neural-Nets Lab
This course covers efficient deep learning computing techniques to enable resource-constrained devices to run large generative models, including model compression, distributed training, application-specific acceleration, and quantum machine learning, while providing hands-on experience deploying large language models on laptops. 23 Lecutres. 2023
Taking AI to School: A Conversation With MIT’s Anant Agarwal (June 2023)
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
In the latest episode of NVIDIA’s AI Podcast, Anant Agarwal, founder of edX and Chief Platform Officer at 2U, shared his vision for the future of online education and the impact of artificial intelligence in revolutionizing the learning experience. Agarwal, a strong advocate for Massive Open Online Courses MOOCs, discussed the importance of accessibility and quality in education. The MIT professor and renowned edtech pioneer also highlighted the implementation of AI-powered features in the edX platform, including the ChatGPT plugin and edX Xpert, an AI-powered learning assistant.
Advanced Confident Learning, LLM and GenAI applications
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
This class has no lecture notes, only video/slides. Notes on Confident Learning are available in the Label Errors lecture notes.
Conversational AI revolutionizes the customer experience landscape
MIT Technology Review
Podcast Episode: In the ever-evolving landscape of customer experiences, AI has become a beacon guiding businesses toward seamless interactions.
Data-Driven Teaching: AI for Pre- and Post-Class Surveys
MIT Sloan School of Management
Effective teaching is an evolving practice, one that benefits greatly from continuous feedback and adjustment. While traditional methods of gathering student feedback can be time-consuming, generative AI tools can make this process easier and more efficient.
Social and Ethical Responsibilities of Computing (SERC)
MIT OpenCourseWare
Social and Ethical Responsibilities of Computing (SERC), a cross-cutting initiative of the MIT Schwarzman College of Computing, works to train students and facilitate research to assess the broad challenges and opportunities associated with computing, and improve design, policy, implementation, and impacts. SPRING 2023
Building Robust RAI Programs as Third-Party AI Tools Proliferate
MIT Sloan Management Review
The risks and failures of AI systems are more palpable and numerous than ever, but organizations are at risk of falling behind.
The Future of AI-Driven Customer Service
MIT Sloan Management Review
Bots are now a key starting point for conversations with customers, so it’s vital that companies think through how they use them. (Apr 2020, VIDEO)
Measuring Autonomy for Life-Like AI
MIT Press
Current success of Artificial Intelligence (particularly in the application of Deep Learning techniques) is bringing some of its methods closer to Artificial Life and re-opening old questions, social fears and envisioned applications.
The Enduring Power of Data Storytelling in the Generative AI Era
MIT Sloan Management Review
Conversations with tools like ChatGPT work great for some decision-making situations, but not all. Here’s how to best deliver data for four key cases.
Affective Computing
Media Arts and Sciences
This course instructs students on how to develop technologies that help people measure and communicate emotion, that respectfully read and that intelligently respond to emotion, and have internal mechanisms inspired by the useful roles emotions play. Fall 2015
Ethics Of AI Bias
Chemical Engineering
This video aims to delve into the human problems brought out by issues in artificial intelligence, specifically with respect to bias. It is suitable for classroom use or as a standalone video for those who wish to understand the issue more deeply than is conventionally covered. For classroom use, we recommend watching the chapterized version of the video and working through the teaching materials provided for each chapter. SPRING 2023
Introduction to Machine Learning: Image Classification
MIT App Inventor
This Introduction to Machine Learning includes tutorial lessons as well as suggestions for student explorations and project work. Students create and image classification program
MIT CSAIL Researcher Explains: AI Image Generators
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
Short Video: MIT CSAIL PhD student Yilun Du discusses the potential applications of generative art beyond the explosion of images that put the web into creative hysterics.
Applied Generative AI for Digital Transformation
MIT Professional Education
This course provides a comprehensive understanding of generative AI, its applications across various domains, and strategies for harnessing its power to address real-world business challenges, making it suitable for professionals from diverse backgrounds, including senior leaders, managers, investors, and those seeking to leverage generative AI for innovation and productivity.
J-WEL test
Jameel World Education Lab
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Artificial Intelligence and Machine Learning
MIT OpenCourseWare
MIT Lincoln Laboratory
This lecture provided an overview on artificial intelligence and took a deep dive on machine learning, including supervised learning, unsupervised learning, and reinforcement learning. 2020
Increasing AI Tool Adoption by Front-Line Workers
MIT Sloan Management Review
AI progress can stall when end users resist adoption. Developers must think beyond a project’s business benefits and ensure that end users’ workflow concerns are addressed. (Sep 8, 2022 VIDEO)
MITx: Probability - The Science of Uncertainty and Data
edX
Build foundational knowledge of data science with this introduction to probabilistic models, including random processes and the basic elements of statistical inference .
Media Literacy in the Age of Deepfakes
MIT OpenCourseWare
Media Literacy in the Age of Deepfakes aims to equip students with the critical skills to better understand the past and contemporary threat of misinformation. Spring 2021
Designing and Building AI Products and Services
MIT xPro
This 8-week program equips technology professionals and entrepreneurs with the knowledge to design AI-based products across various industries by teaching the fundamentals of machine learning algorithms, the stages of AI product design, and the application of AI technologies to solve practical problems and improve organizational processes.
How Developers Can Lower AI’s Climate Impact
MIT Sloan Management Review
AI development can be a power-hungry process, but there are tactics for reducing energy use and carbon emissions. (Jan 2024)
Learn to Make the Most of Your Relationship With AI
MIT Sloan Management Review
Only 11% of organizations achieve significant financial benefits with AI; here’s how they do it. (Jan 2021, VIDEO)
Priming users with different mental models of an AI’s motives significantly influences their perception of the AI’s trustworthiness, empathy, and performance
MIT Media Lab
This study demonstrates that priming users with different mental models of an AI’s motives significantly influences their perception of the AI’s trustworthiness, empathy, and performance, with the effects being more pronounced for sophisticated AI models, highlighting the importance of carefully introducing AI systems to shape user interactions and experiences.
Introduction To Machine Learning
Electrical Engineering and Computer Science
This course introduces the principles, algorithms, and applications of machine learning for modeling and prediction, covering learning problem formulation, representation, over-fitting, and generalization concepts. Students will learn to perform supervised and reinforcement learning with images and temporal sequences through lectures, notes, exercises, labs, and homework problems. Prerequisites include Python programming, calculus, and linear algebra. 2020
2020 Frontiers of AI:ML - Aleksander Madry
MIT Corporate Relations
In this seminar, Aleksander Madry discusses the unreliability and failure modes of machine learning models, exploring the root causes such as misalignment between human and model problem-solving, the impact of backdoor attacks and spurious correlations, and the biases introduced by dataset creation and annotation processes, emphasizing the need for better understanding and alignment with human cognition to improve model reliability and interpretability.
Using Federated Machine Learning to Overcome the AI Scale Disadvantage
MIT Sloan Management Review
A promising new approach to training AI models lets companies with small data sets collaborate while safeguarding proprietary information. Aug 2023
Applied Generative AI for Digital Transformation
MIT Professional Education
This two-week live-virtual course equips professionals with a comprehensive understanding of Generative AI technologies, their applications across various domains, and strategies for harnessing their power to drive digital transformation and enhance productivity within organizations.
Machine Learning and Data Analytics in the Pandemic Era
MIT Sloan Management Review
The COVID-19 pandemic has serious implications for the future of data, analytics, and machine learning. (Dec 17, 2020. VIDEO)
MITx: Introduction to Computational Thinking and Data Science
edX
This course, 6.00.2x, teaches computational problem-solving using Python 3, covering advanced programming concepts, algorithms like dynamic programming and graph optimization, and statistical techniques such as Monte Carlo simulations and curve fitting, through hands-on programming projects that simulate real-world scenarios.
MIT Research Report: How AI Changes the Rules: New Imperatives for the Intelligent Organization (2020)
MIT Sloan Management Review Connections
Many leaders are excited about AI’s potential to profoundly transform organizations by making them more innovative and productive.
Artifical Intelligence in Healthcare
MIT Sloan Executive Education
Develop an understanding of how AI is transforming health care, and explore case studies that reveal how these technologies are being deployed to overcome challenges and optimize processes.
Media Literacy In The Age Of Deepfakes
This learning module equips students with critical media literacy skills to understand and analyze misinformation, particularly deepfake videos, while also exploring how new technologies like AI can be used for civic good through projects in satire, investigative documentary, and public history. The module is centered around the case study of “In Event of Moon Disaster,” an award-winning MIT deepfake art installation about the “failed” Apollo 11 moon landing. Educator resources, including a bibliography, syllabus, and design prompts, are provided to support teachers in adapting the module for their own classes.
Critical Success Factors for Achieving ROI From AI Initiatives
MIT Sloan Management Review
Finding a reliable path to value — not implementing the technology — may be the biggest challenge for organizations seeking to earn a return on investment for their AI initiatives. (Nov 2021 VIDEO)
How to Succeed With AI Augmentation
MIT Sloan Management Review
For all the remarkable things that machine learning and advanced analytics can do, there are scores of things that AI-enabled machines still can’t do — at least not reliably enough on their own in the real world of business. (Oct 21 2022, VIDEO)
AI 101 with Brandon Leshchinskiy
MIT OpenCourseWare
This is a video of Brandon Leshchinskiy’s presentation “AI 101,” which provides an introductory overview of the application of artificial intelligence in solving real-world problems: which tasks machine learning handles well, how it works, and what its shortcomings are.
RAISE (Responsible AI for Social Empowerment and Education)
MIT OpenCourseWare
Responsible AI for Social Empowerment and Education
RAISE (Responsible AI for Social Empowerment and Education) is a new MIT-wide initiative headquartered in the MIT Media Lab and in collaboration with the MIT Schwarzman College of Computing and MIT Open Learning. MIT researchers continually develop curriculum modules and associated teaching materials that are available to all K-12 educators for free under a Creative Commons license. Spring 2022
MITx: Understanding the World Through Data
edX
This introductory course teaches the fundamentals of machine learning, including data exploration and visualization using Python, creating mathematical models to describe relationships between data, understanding the impact of imperfect data on models, and using classification algorithms to predict group membership, providing a hands-on learning experience suitable for beginners with a curiosity about the topic.
MIT Artifical Intelligence Course Lectures Playlist (2010)
MIT OpenCourseWare
Full Course Recordings. 2010.
How Al Spurs Employee Engagement and Innovation at Levi Strauss & Co.
MIT Sloan Management Review
Recent research — and practice — shows AI implementation positively affects organizational culture. (VIDEO March 2022)
MIT GenAI Summit Live Webcast 2023
MIT Schwarzman College of Computing
Massachusetts Institute of Technology
MIT Open Learning
The inaugural Generative AI Summit, where leading experts will come together to talk about GenAI and explore how this technology will impact our lives, work, and the world. From ethical considerations to groundbreaking use cases, the summit will take you on a comprehensive journey through the state of generative AI. Don’t miss this opportunity to network with industry leaders and gain valuable knowledge that will help you stay ahead of the curve in this rapidly evolving field.
Achieving Individual — and Organizational — Value With AI
MIT Sloan Management Review
New research shows that employees derive individual value from AI when using the technology improves their sense of competency, autonomy, and relatedness. Findings from the 2022 Artificial Intelligence and Business Strategy Global Executive Study and Research Project
System brings deep learning to “internet of things” devices
MIT News
News article: Advance could enable artificial intelligence on household appliances while enhancing data security and energy efficiency.
How AI Demands Organizational Change
MIT Sloan Management Review Connections
New research from MIT SMR Connections and SAS finds that organizations that are implementing AI widely have recognized the need to make significant changes in order to enable cross-functional collaboration; provide a more robust and up-to-date IT infrastructure; and manage new risks that can jeopardize trust in AI. (2020 VIDEO)
AI Senses People Through Walls
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
Short video of new advances in AI that can sense where people are through walls
Machine Learning in Business
MIT Sloan School of Management
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
This online short course from MIT Sloan and CSAIL provides business leaders and professionals with a comprehensive understanding of the managerial implications and technical aspects of machine learning, enabling them to develop effective strategies for integrating this technology into their organizations and gain a competitive edge, without requiring coding or programming skills.
The Key to Success With AI Is Human-Machine Collaboration
MIT Sloan Management Review
Companies that emphasize collaboration between AI and human workers are best positioned for success.
Generative AI Shaping The Future Keynote: Refik Anadol
MIT Schwarzman College of Computing
Massachusetts Institute of Technology
MIT Open Learning
Refik Anadol’s presentation at MIT introduced his innovative fusion of digital art, AI, and environmental data, exploring human connections with technology and nature. Through collaborative projects like “Winds of Yawanawá” and immersive installations at MoMA, Anadol transforms vast data sets into dynamic visual experiences, advocating for a deeper, positive engagement with AI and its potential to reshape perceptions of reality and nature.
A generative AI tool to inspire creative workers
MIT Sloan School of Management
Study Press Announcement: In a new paper, researchers from MIT, Harvard, and the Toyota Research Institute found that generative AI can help designers come up with new ideas by quickly creating images based on text prompts. Feb 2024
Human Favoritism, Not AI Aversion: People’s Perceptions (and Bias) Toward Generative AI, Human Experts, and Human-GAI Collaboration in Persuasive Content Generation
MIT Sloan School of Management
In this study, AI-generated and AI-augmented content was perceived as higher quality than human-created content, and while revealing the content source reduced this gap, it remained, driven primarily by human favoritism rather than AI aversion.
MIT Report: How Generative AI will Reshape the Enterprise: CIO perspectives on GenAI
MIT Technology Review
This new MIT Technology Review Insights report is based on interviews with the CIOs of Adobe, Shell, DuPont, Cosmo Energy and Kansas City Veterans Affairs Medical Center — as well as an MIT professor and Matei Zaharia, Co-founder and CTO, Databricks. Combined with the results of a global AI survey of 600 CIOs, this report gives you strategic insights on enterprise adoption of generative AI.
MIT AI/Machine Learning Club Youtube Channel
AI (Artificial Intelligence) and ML (Machine Learning) Club
Various videos on Generative AI and AI/ML generally
Machine Learning For Healthcare
Electrical Engineering and Computer Science
This course introduces students to machine learning in healthcare, including the nature of clinical data and the use of machine learning for risk stratification, disease progression modeling, precision medicine, diagnosis, subtype discovery, and improving clinical workflows. From 2019
Podcast: Me, Myself, and AI
MIT Sloan Management Review
Podcast: Why do only 10% of companies succeed with AI? We’re on a mission to figure it out. On Me, Myself, and AI, co-hosts Sam Ransbotham (Boston College) and Shervin Khodabandeh (BCG) talk to the people who are achieving big wins with AI. Sign up to be notified when new episodes are released and let these stories inspire your own work.
Using AI to protect against AI image manipulation
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
Review of using AI to protect agIn this conversation, Hadi discusses the potential risks associated with advanced generative AI models, such as misinformation and blackmail, and introduces PhotoGuard, a research prototype that aims to protect images from AI manipulation using adversarial perturbations, while highlighting the challenges in making such a solution practical and emphasizing the importance of preventing image manipulation rather than just detecting it post-hoc.ainst AI image manipulation
The Future of Robot Learning: MIT 6.S191
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
MIT Introduction to Deep Learning 6.S191: Lecture 10 The Future of Robot Learning Lecturer: Daniela Rus 2023 Edition. Includes links to all lectures, slides, and lab materials
New AI model could streamline operations in a robotic warehouse
MIT-Amazon Science Hub
By breaking an intractable problem into smaller chunks, a deep-learning technique identifies the optimal areas for thinning out traffic in a warehouse. Feb 2024
Deep Learning State of the Art (2020)
Lecture on most recent research and developments in deep learning, and hopes for 2020. This is not intended to be a list of SOTA benchmark results, but rather a set of highlights of machine learning and AI innovations and progress in academia, industry, and society in general.
Growing or Compressing Datasets
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
For supervised learning applications where training data have been annotated by humans, labeling is time-consuming and expensive.
Data-centric Evaluation of ML Models
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
This lecture will focus on step 5, the foundation for improving ML performance.
Generative AI for smart grid modeling
MIT Laboratory for Information and Decision Systems (LIDS)
MIT LIDS awarded funding model and test new smart grid technologies for use in rural areas. The article highlights the potential of AI, specifically generative models, in transforming the energy sector by creating realistic, synthetic customer load data that can augment limited datasets and predict various scenarios, enabling better planning, testing, and deployment of smart grid technologies in the Appalachian region.
Using Generative AI to cultivate positive emotions and mindsets for self-development and learning
MIT Media Lab
The arrival of new generative AI tools is creating waves. Here are some ideas for how we could channel them for supporting self-development and learning.
The Impact of chatGPT on Physics Education (2023) - Prof. Max Tegmark (MIT)
MIT Department of Physics
The Impact of chatGPT and other large language models on physics research and education (2023)
Making Strategic Technology Decisions for Successful Enterprise AI
MIT Sloan Management Review Connections
IT and business leaders who want to speed their organization’s AI-fueled ambitions have an unprecedented opportunity that requires informed, strategic platform and architecture decisions. (2020 VIDEO)
CSAIL Embodied Intelligence
MIT Embodied Intelligence
The main Embodied Intelligence (AI + Robots) seminar series consists of talks from researchers doing research in ML, robotics and related fields. Recorded talks are posted to our Youtube Channel. All seminars are also posted to the EI Seminar Calendar and this semester’s schedule can be found here. ALL LINKS HERE.
Prediction: Machine Learning And Statistics
MIT Sloan School of Management
Prediction is at the heart of almost every scientific discipline, and the study of generalization (that is, prediction) from data is the central topic of machine learning and statistics, and more generally, data mining. Course from 2012
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