Justin Solomon is an associate professor in the MIT Department of Electrical Engineering and Computer Science and a member of the Computer Science and Artificial Intelligence Laboratory who is using geometric techniques to solve complex problems in data science and artificial intelligence, among other areas. These techniques draw upon the geometric structures within datasets to…
Photolithography, the technique of etching features onto a surface using light manipulation, is commonly used in the manufacturing of computer chips and optical devices. However, small deviations during the manufacturing process often impact the performance of the finished product. To address this, researchers from MIT and the Chinese University of Hong Kong have leveraged machine…
Researchers at the Massachusetts Institute of Technology and the MIT-IBM Watson AI Lab have developed an onboarding system that trains humans when and how to collaborate with Artificial Intelligence (AI). The fully automated system learns to customize the onboarding process according to the tasks performed, making it usable across a variety of scenarios where AI…
A group of scholars and leaders from MIT has developed policy briefs to establish a governance framework for artificial intelligence (AI). The briefs are intended to assist U.S. policymakers, sustain the country's leadership position in AI, limit potential risks from new technologies, and explore how AI can benefit society.
The primary policy paper, "A Framework for…
Over 2,000 years after Euclid's groundbreaking work in geometry, MIT associate professor Justin Solomon is using the ancient principles in fresh, modern ways. Solomon's work in the Geometric Data Processing Group applies geometry to solve a variety of problems, from comparing datasets in machine learning to enhancing generative AI models. His work assumes a variety…
Researchers at MIT and the Chinese University of Hong Kong have developed a machine learning tool to emulate photolithography manufacturing processes. Photolithography is commonly used in the production of computer chips and optical devices, manipulating light to etch features onto surfaces. Variations in the manufacturing process can cause the end products to deviate from their…
Researchers at MIT and the MIT-IBM Watson AI Lab have developed a system that teaches users when to trust AI and when to ignore it, and it has already led to an approximately 5% increase in accuracy during image prediction tasks. The researchers designed a customised onboarding process, which is when the user is familiarized…
A group of scholars from the Massachusetts Institute of Technology (MIT) has outlined a governance framework for artificial intelligence (AI). The initiative aims to educate U.S. lawmakers on the implementation of AI regulations that can enhance their leadership in the field, minimize any potential harm, and promote beneficial practices. The main policy paper, titled "A…
Over 2,000 years ago, Euclid, a Greek mathematician often referred to as the father of geometry, fundamentally transformed our understanding of shapes. Today, Justin Solomon, a professor at MIT's Department of Electrical Engineering and Computer Science and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL), employs contemporary geometric approaches to tackle complex…
Photolithography, the process of using light to precisely etch designs onto a surface, is a primary method for creating computer chips and optical devices. However, it's common for slight deviations during manufacturing to cause the final product to diverge from the intended design. To bridge this gap, researchers from MIT and the Chinese University of…
Researchers from MIT and the MIT-IBM Watson AI Lab have developed a system that instructs users when to trust an AI system’s decision-making. In medicine, there might be instances like a radiologist using an AI model for reading X-rays where human intervention can make a difference. However, clinicians are uncertain whether to lean on the…
A committee of leaders and scholars from MIT has developed a series of policy briefs outlining a framework for the governance of artificial intelligence (AI) in the U.S. The goal of these papers is to strengthen U.S. leadership in AI, mitigate potential harm from new technologies, and explore how AI deployment can serve society.
The primary…