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Causal Inference & Deep Learning
Max Shen, PhD Student, Computational & Systems Biology
Enrollment: Unlimited: No advance sign-up
Attendance: Participants welcome at individual sessions
The vast majority of machine learning advances concern associative or correlative relationships despite the importance of learning and inferring causal relationships.
In this brief class, we will consider how the successful tool of deep learning can best deliver new insights into fundamental problems regarding causality. We will explore several recent and successful papers describing applications of deep learning to causality, with the big picture goal of understanding fruitful next steps in the research intersection of deep learning and causality.
Please register here for class email updates: https://goo.gl/forms/xOgpVJB5OFsrUB6G3
Contact: Max Shen, MAXWSHEN@MIT.EDU
Computational Law Course
Dazza Greenwood, JD, Visiting Scientist, MIT Media Lab
Enrollment: Request Signup at https://law.mit.edu/learning
Sign-up by 12/08
Limited to 150 participants
Attendance: Participants may miss sessions by prior arrangement.
Prereq: N/A
This course provides a conceptual overview and hands-on projects for understanding and solving legal use cases with data analytics, blockchain and other cryptosystems and a special module on rapid design solutions to the MITLegalForum.org Smart City Challenge. The course includes seminar style lecture/discussion sessions and hands-on, experiential learning through team projects. The course covers:
Legal Analytics, including 1) AI/Machine Learning for solving legal use cases; and 2) Using data-driven visualization including AR for display and interaction with models of complex legal and financial relationships and contexts.
Digital Assets, including: 1) Ownership rights, valuation and provenance of digital property; and 2) Storage and exchange of digital property with electronic contracts, automated transactions and autonomous agents
Digital Identity, including: 1) Technology and architecture for autonomy and control of self-sourced digital identity and personal data; and 2) Using individual identity for valid, verifiable login to apps or services and for providing legal acknowledgement, assent or authorization.
Digital Contracts, including 1) Integrating ordinary digital contracts and blockchain "smart contracts" in automated transactions by individuals or businesses; and 2) Standard open-web stack design patterns for executing multiple digital signatures and electronic notarization on digital legal contracts.
For more info, see: law.MIT.edu/learning
Sponsor(s): Media Arts and Sciences
Contact: Dazza Greenwood, E15-449, 617.500.3644, DAZZA@MEDIA.MIT.EDU
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Jan/16 | Tue | 02:00PM-04:00PM | Online, Use your laptop and smartphone |
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Jan/17 | Wed | 02:00PM-04:00PM | Online, Use your laptop and smartphone |
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Jan/18 | Thu | 02:00PM-04:00PM | Online, Use your laptop and smartphone |
These sessions will take place online. Registered participants will receive connection information. A mix of in-person and online office hours will be available for discussion of class topics and student projects upon request and by appointment before or after class sessions.
Dazza Greenwood, JD - Visiting Scientist, MIT Media Lab
Consciousness, Computation, the Universe
Andrew Kortina, Rob Cheung
Enrollment: Limited: Advance sign-up required
Sign-up by 01/19
Limited to 20 participants
Attendance: Participants must attend all sessions
Prereq: Short readings before each seminar: https://goo.gl/DD6Mqf
This will be a 3 part seminar (roundtable discussion format, not a
lecture). We'll discuss recent work in artificial intelligence and
philosophy, and ask questions like: How can we use principles of software
and computation to better understand our own minds? Is AI an existential
risk? What are its implications for human dignity?
There are selected, short pre-readings for each of the 3 sessions, online.
Sponsor(s): Electrical Engineering and Computer Science
Contact: Andrew Kortina, andrew.kortina@gmail.com
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Jan/17 | Wed | 10:00AM-11:30AM | 36-153 |
What can we understand about consciousness given what we have learned about computation and artificial intelligence? What can we learn about the universe given what we have learned about information theory and computation?
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Jan/18 | Thu | 10:00AM-11:30AM | 36-153 |
AI is a slippery term, and you could argue that some incredibly complex systems exhibiting emergent order (vs top down organization and planning) are instances of AI. Specifically, we'll talk about macroeconomics and mass media. What lessons can we learn from these systems as we develop new, more powerful forms of software intelligence in the coming decades.
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Jan/19 | Fri | 10:00AM-11:30AM | 36-153 |
In a world where robots and software can perform work (and produce art) far more efficiently and capably than any human, how will our ideas of human dignity evolve?
Hacking Our Digital Future
David Verrill, Executive Director, MIT Initiative on the Digital Economy
Enrollment: Limited: Advance sign-up required
Sign-up by 01/11
Limited to 50 participants
Attendance: Participants must attend all sessions
The MIT Initiative on the Digital Economy (IDE) explores how people and businesses will work, interact, and prosper in an era of profound digital transformation. Major innovations we’ve already glimpsed in the digital age include self-driving cars, additive manufacturing, platform technologies, cryptocurrencies, “fake news”, and beyond.
But in the future, what are the unforeseen, unintended consequences—positive and negative—of these new aspects of the digital age?
We invite students and other members of the MIT community to develop plausible scenarios and narratives of the future in 2030 that expand the thinking of decision-makers and stakeholders to positively impact productivity, employment and equality.
IDE will provide suggested pre-reading articles and host guest lectures from leading futurists, but student teams will be largely self-guided.
Additional program information and materials are available at: https://hacking-our-digital-future.eventbrite.com
Sponsor(s): Sloan School of Management
Contact: Dalton Perras, E94-1518, 617-324-6536, dperras@mit.edu
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Jan/09 | Tue | 03:00PM-06:00PM | 56-154 |
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Jan/11 | Thu | 03:00PM-06:00PM | 56-154 |
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Jan/16 | Tue | 03:00PM-06:00PM | 56-154 |
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Jan/18 | Thu | 03:00PM-06:00PM | 56-154 |
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Jan/23 | Tue | 03:00PM-06:00PM | 56-154 |
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Jan/25 | Thu | 03:00PM-06:00PM | 56-154 |
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Jan/30 | Tue | 03:00PM-06:00PM | 56-154 |
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Feb/01 | Thu | 03:00PM-06:00PM | 56-154 |
Students kick off this 4-week long hackathon with an overview lecture and choose a topic area around which they will develop multiple scenario storylines. Food provided.
IAP Mars Settlement Workshop
Bruce Mackenzie
Enrollment: Unlimited: No advance sign-up
Attendance: Participants welcome at individual sessions
Mars Settlement, a Minimum One-Way Program
Bruce Mackenzie, Mars Foundation
Jan. 29th, Monday 12 noon – 1 pm
Will show a proposal for a very small, relatively inexpensive
manufacturing base for Mars. It starts with just 2 people, and can
grow into a permanent human settlement; a draft design in progress by
the Mars Foundation.
Internships on Mars
Jan. 29th, Monday 4 pm – 5 pm
Interested in an internship on the subject of Mars, or other ways you
can help settlement of space?
This will be an informal discussion of (mostly volunteer) internships
with various non-profit space activist organizations, including the
National Space Society, Mars Society, Moon Society, and Mars
Foundation; and how they might fit your academic and career plans.
Meetings at other times can be arranged.
Overview of Hillside Mars Settlement
Feb. 1st, Thursday, 7pm – 9pm
This “Hillside Settlement” proposal by the Mars Foundation would build
a permanent settlement on Mars, constructed by 12 people from local
materials such as fiberglass and masonry. Preliminary mass and cost
estimates show that we may be able to establish a permanent, growing
settlement for the same launch cost as a program of round-trip
exploratory missions. Members of National Space Society are invited.
Raising the First Children in Space
Feb. 2nd, Friday 12 noon – 1 pm
Open discussion of the safety and ethics of raising children at an
early settlement on Mars or other frontier location.
Sponsor(s): Astropreneurship and Space Industry Club
Contact: Bruce Mackenzie, 2-146, 781-249-5437, bmackenzie@alum.mit.edu
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Jan/29 | Mon | 12:00PM-01:00PM | 2-146 |
Will show a proposal for a very small, relatively inexpensive
manufacturing base for Mars. It starts with just 2 people, and can
grow into a permanent human settlement; a draft design in progress by
the Mars Foundation.
Bruce Mackenzie
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Jan/29 | Mon | 04:00PM-05:00PM | 2-146 |
Interested in an internship on the subject of Mars, or other ways you
can help settlement of space?
This will be an informal discussion of (mostly volunteer) internships
with various non-profit space activist organizations, including the
National Space Society, Mars Society, Moon Society, and Mars
Foundation; and how they might fit your academic and career plans.
Meetings at other times can be arranged.
Bruce Mackenzie
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Feb/01 | Thu | 07:00PM-09:00PM | 2-146 |
This ¿Hillside Settlement¿ proposal by the Mars Foundation would build
a permanent settlement on Mars, constructed by 12 people from local
materials such as fiberglass and masonry. Preliminary mass and cost
estimates show that we may be able to establish a permanent, growing
settlement for the same launch cost as a program of round-trip
exploratory missions. Members of National Space Society are invited.
Bruce Mackenzie
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Feb/02 | Fri | 12:00PM-01:00PM | 2-146 |
Open discussion of the safety and ethics of raising children at an
early settlement on Mars or other frontier location.
Bruce Mackenzie
MathWorks: Demystifying Deep Learning - A Practical Approach in MATLAB
JM.Modisette, PhD, Technical Evangelist
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Jan/24 | Wed | 10:00AM-12:00PM | 3-270 |
Enrollment: Register on MathWorks Website (below)
Limited to 119 participants
Prereq: None
Are you new to deep learning and want to learn how to use it in your work? Deep learning can achieve state-of-the-art accuracy in many humanlike tasks such as naming objects in a scene or recognizing optimal paths in an environment.
The main tasks are to assemble large data sets, create a neural network, to train, visualize, and evaluate different models, using specialized hardware - often requiring unique programming knowledge. These tasks are frequently even more challenging because of the complex theory behind them.
In this seminar, we’ll demonstrate new MATLAB features that simplify these tasks and eliminate the low-level programming. In doing so, we’ll decipher practical knowledge of the domain of deep learning. We’ll build and train neural networks that recognize handwriting, classify food in a scene, and figure out the drivable area in a city environment.
For more information and registration at:
https://www.mathworks.com/company/events/seminars/mit-iap-2361872.html
Sponsor(s): Office of Educational Innovation and Technology
Contact: JM.Modisette, JM.Modisette@mathworks.com
MathWorks: Practical Applications of Deep Learning, A Hands-On MATLAB Workshop
JM.Modisette, PhD, Technical Evangelist, MathWorks
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Jan/24 | Wed | 01:00PM-04:00PM | W31-301 |
Enrollment: Register on MathWorks Website (below)
Limited to 30 participants
Are you new to deep learning and want to learn how to apply these techniques it in your work? Deep learning achieves human-like accuracy for many tasks considered algorithmically unsolvable with traditional machine learning. It is frequently used to develop applications such as face recognition, automated driving, and image classification.
In this hands-on workshop, you will write code and use MATLAB to:
- Learn the fundamentals of deep learning and understand terms like “layers”, “networks”, and “loss”
- Build a deep network that can classify your own handwritten digits
- Access and explore various pretrained models
- Use transfer learning to build a network that classifies different types of food
- Train deep learning networks on GPUs in the cloud
- Learn how to use GPU code generation technology to accelerate inference performance
Register at: https://www.mathworks.com/company/events/seminars/mit-iap-2361872.html
Sponsor(s): Office of Educational Innovation and Technology
Contact: JM.Modisette, JM.Modisette@mathworks.com
RACECAR (Rapid Autonomous Complex-Environment Competing Ackermann-drive Robotics
Sertac Karaman, Professor, Aeronautics and Astronautics, Michael Boulet, Assistant Group Leader, Lincoln Lab, Ken Gregson, Senior Staff, Lincoln Lab
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Jan/10 | Wed | 02:00PM-04:00PM | 32-081 |
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Jan/12 | Fri | 02:00PM-04:00PM | 32-081 |
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Jan/17 | Wed | 02:00PM-04:00PM | 32-081 |
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Jan/19 | Fri | 02:00PM-04:00PM | 32-081 |
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Jan/22 | Mon | 02:00PM-04:00PM | 32-081 |
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Jan/24 | Wed | 02:00PM-04:00PM | 32-081 |
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Jan/26 | Fri | 02:00PM-04:00PM | 32-081 |
Enrollment: Limited: Advance sign-up required
Sign-up by 01/05
Limited to 30 participants
Attendance: Participants must attend all sessions
Prereq: None
Modern robots tend to operate at slow speeds in complex environments, limiting their utility in high-tempo applications. In the RACECAR course, you will be tasked with pushing the boundaries of unmanned vehicle speed. Participants will work in teams of 4-5 to develop dynamic autonomy software to race a converted RC car equipped with LIDAR, a stereo camera, an inertial measurement unit, and embedded processing around a large-scale, "real-world" course. Working from a baseline autonomy stack, teams will modify the software to increase platform velocity to the limits of stability. The course culminates with a timed competition to navigate a racecourse. Classes will provide lecture overviews of relevant algorithms and lab time with instructor-assisted development. Participants must attend every class and should plan on 4-10 hours per week of self-directed development. Students must have experience with software development. Past exposure to robotics algorithms and/or embedded programming will be useful.
To sign up, preregister on websis and send an e-mail by Jan 5 to racecar-iap-course-subscribe@mit.edu with a brief description of your programming/robotics experience.
Also offered for credit as 6.S184.
Sponsor(s): Electrical Engineering and Computer Science
Contact: Michael Boulet, boulet@mit.edu
Reading the Collective Mind - Deep Learning By Social Signals
Peter Gloor, Qi Wen
Enrollment: Limited: Advance sign-up required
Sign-up by 01/09
Limited to 30 participants
Attendance: Participants welcome at individual sessions
Prereq: none
Find out who and what makes you happy
Find out who likes you best and who is your most creative collaborator
Find out what will be the next big thing on social media
In this course we will try to predict what small teams and entire populations are thinking based on analyzing their communication archives. Using the Condor and Happimeter software developed by the presenters and their team members we will use latest algorithms from machine learning and dynamic semantic social network analysis to read their collective mind.
Using the Happimeter smartwatch software will allow you to automatically measure how happy you are, how much you like others around you, how stressed you are, your fairness, and how much you trust and are trusted by tracking your body signals through the sensors of the smartwatch.
Applying the Condor analysis tool to your own e-mail (or slack, WhatsApp, or Skype log) will show your social network in a virtual mirror, and tell who respects you most, how passionate you and others are, and who your role models and influencers are.
Doing dynamic semantic social network analysis with Condor on Twitter and other global social media data will allow you to automatically measure the influencers and virtual tribes behind fake news, and to decide in which virtual currency to invest.
Sponsor(s): Sloan School of Management
Contact: Peter Gloor, E94-1504D, 617 253-7018, PGLOOR@MIT.EDU
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Jan/11 | Thu | 02:00PM-05:00PM | E62-446, Bring your laptop |
Introduction to Swarm Creativity and COINs (Collaborative Innovation Networks)
Creating a Virtual Mirror of your own mailbox with Condor
Measuring personal happiness and trust with the happimeter
Peter Gloor, Qi Wen
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Jan/12 | Fri | 02:00PM-05:00PM | E62-446, Bring your laptop |
Coolhunting on Social Media with Condor to find trends and trendsetters
Finding fake news and measuring virtual currencies
Measuring altruism with the happimeter
Peter Gloor, Qi Wen
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