Putting AI into the hands of people with problems to solve
Alumni-founded Pienso has developed a user-friendly AI builder so domain experts can build solutions without writing any code.
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Alumni-founded Pienso has developed a user-friendly AI builder so domain experts can build solutions without writing any code.
Innovative AI system from MIT CSAIL melds simulations and physical testing to forge materials with newfound durability and flexibility for diverse engineering uses.
Researchers developed a simple yet effective solution for a puzzling problem that can worsen the performance of large language models such as ChatGPT.
Exploiting the symmetry within datasets, MIT researchers show, can decrease the amount of data needed for training neural networks.
Atacama Biomaterials, co-founded by Paloma Gonzalez-Rojas SM ’15, PhD ’21, combines architecture, machine learning, and chemical engineering to create eco-friendly materials.
Although artificial intelligence in health has shown great promise, pressure is mounting for regulators around the world to act, as AI tools demonstrate potentially harmful outcomes.
MIT CSAIL researchers develop advanced machine-learning models that outperform current methods in detecting pancreatic ductal adenocarcinoma.
A multimodal system uses models trained on language, vision, and action data to help robots develop and execute plans for household, construction, and manufacturing tasks.
MIT researchers propose “PEDS” method for developing models of complex physical systems in mechanics, optics, thermal transport, fluid dynamics, physical chemistry, climate, and more.
MIT researchers introduce a method that uses artificial intelligence to automate the explanation of complex neural networks.