The U.S. National Science Foundation (NSF) announced today an investment of more than $100 million to establish five artificial intelligence (AI) institutes, each receiving roughly $20 million over five years. One of these, the NSF AI Institute for Artificial Intelligence and Fundamental Interactions (IAIFI), will be led by MIT’s Laboratory for Nuclear Science (LNS) and become the intellectual home of more than 25 physics and AI senior researchers at MIT and Harvard, Northeastern, and Tufts universities.
When a natural disaster occurs, on-the-ground emergency response teams act quickly to make life-saving decisions. Reducing the response time in such situations is critical to reduce damage impact and save lives. Helpful efforts are being taken to reduce the burden, such as a damage assessment tool by UNDP, though few automated methods exist. In recent work, MIT is creating tools that can automatically analyze images.
MIT CSAIL and STEMM Global Scientific Community announced that they will gather thought leaders from all over the world at a virtual summit dedicated to AI in Healthcare on October 1-2, 2020. The aim of the summit is to boost effective collaboration among leading AI academics, healthcare experts and business leaders to support innovation in healthcare.
CSAIL will be launching a new initiative focused on machine learning applications. MachineLearningApplications@CSAIL, or “MLA@CSAIL”, will focus on current challenges in machine learning to prepare industry members for digital transformation in their workplaces.
One of the biggest challenges in computing is handling the onslaught of information while still being able to efficiently store and process it. A team from MIT CSAIL believe that the answer rests with something called “instance-optimized systems.”
OpenAI unveiled the largest language model in the world, a text-generating tool called GPT-3 that can write creative fiction, translate legalese into plain English, and answer obscure trivia questions. It’s the latest feat of intelligence achieved by deep learning, a machine learning method patterned after the way neurons in the brain process and store information.
