2/15/23 - this subject number was previously 4.s22

The rise of Artificial Intelligence (AI) dates back over 80 years when digital computers were developed during World War II. Using binary code to represent various phenomena made it possible to solve previously unsolvable numerical problems. AI has rapidly become a transformative technology in various fields, including the built environment. This course offers a thorough understanding of AI's role in the built environment, including hands-on examples of utilizing AI to tackle various urban challenges. Through data-driven case studies, this course will explore how emerging data and AI models are changing the assessment of the built environment. The structure of this course focuses on four key areas: 

• Data Analysis in Satellite Imagery
• Fundamental of Graph Theory and its applications in cities
• Computer vision and  image processing
• Theories of Artificial Neural Networks and image data classification. 

In this project-based course, students will work in teams to develop a computational approach that addresses the use of these four methods to solve an urban problem.  
 

2/24/23 - class will now meet in room 5-216

Master/Piece wordshop will study 6 buildings that are considered seminal in contemporary architecture, built by architects that remain active in practice. We will discuss why those works are key and the chain of reactions and trends that detonate in architecture culture, their traces and impact in peers and in other projects. We will focus deep in the conceptual to constructive scales and the masters will join the class to culminate the analysis and conversation.

Visiting masters: Alberto Campo Baeza, Diébédo Francis Kéré & Alejandro Aravena

Note: 1st meeting, T 2/7, 10am on Zoom: https://mit.zoom.us/j/97338571583

The Metropolitan Storage Warehouse was built in 1895, it is one of the oldest buildings in the MIT neighborhood and currently finds itself in the midst of redevelopment as it will become the new home of the School of Architecture and Planning in 2025. Upon completion the MET will provide approximately 110,000 square feet of academic, research, and gathering space including labs and studios for architecture students. As the building finds itself amidst active transformation this workshop will look back on the MET’s past lives, investigate its current working state, and ponder on its future through the tools of phonography, or field recording, to better understand the multiple layers of reality that converge at this site.

The MET Warehouse operated as a storage facility since its construction and its architectural elements– two-foot-thick-stone walls, vaulted ceilings, its medieval crenellations—all stood witness to years of internal life, the drama of the storage facility; the secret life of boxes that end up in secret rooms. In 2015, when the MET closed, much more than boxes were revealed to have occupied the nearly 1,500 internal units: private offices, satellite walk-in closets, a wine collection dating back to the mid-90’s, a saxophonist’s recording studio, extension art storage for Boston museums, the list goes on.  The MET Warehouse, like many other storage spaces, was a territory of exchange and protection for belonging(s): material, capital, life. How might the past lives of this building effect its future life as repository and vessel for a community of architects, designers, and thinkers (both academic and not, institutional and extra institutional)? In listening to the building might we learn more about its expansive ability to hold, archive, and safekeep and challenge our expectations for what forms of belonging might take place here next?

2/15/23 - this subject number has been changed to 4.s23

The rise of Artificial Intelligence (AI) dates back over 80 years when digital computers were developed during World War II. Using binary code to represent various phenomena made it possible to solve previously unsolvable numerical problems. AI has rapidly become a transformative technology in various fields, including the built environment. This course offers a thorough understanding of AI's role in the built environment, including hands-on examples of utilizing AI to tackle various urban challenges. Through data-driven case studies, this course will explore how emerging data and AI models are changing the assessment of the built environment. The structure of this course focuses on four key areas: 

• Data Analysis in Satellite Imagery
• Fundamental of Graph Theory and its applications in cities
• Computer vision and  image processing
• Theories of Artificial Neural Networks and image data classification. 

In this project-based course, students will work in teams to develop a computational approach that addresses the use of these four methods to solve an urban problem.