This semester, MIT students and postdocs were invited to submit ideas for the first-ever MIT Ignite: Generative AI Entrepreneurship Competition. More than 100 teams submitted startup proposals using generative AI technologies to develop solutions across a wide range of disciplines, including human health, climate change, education and workforce dynamics artwork.
On October 30, 12 finalists presented their ideas in front of a panel of expert judges and a packed room at the Samberg Conference Center.
“MIT has a responsibility to help shape a future of AI innovation that is broadly beneficial – and to do that, we need a lot of good ideas. So we turned to a pretty reliable source of great ideas: the highly entrepreneurial students and postdocs at MIT,” said MIT President Sally Kornbluth in her opening remarks at the event.
The MIT Ignite event is part of a broader focus on generative AI at MIT presented by Kornbluth. This fall, across the Institute, researchers and students are exploring opportunities to share knowledge about generative AI, identifying new applications, minimizing risks, and using it to benefit society. This event — co-hosted by the MIT-IBM Watson AI Lab and the Martin Trust Center for MIT Entrepreneurship, and supported by the MIT School of Engineering and the MIT Sloan School of Management — inspired young researchers to contribute to the dialogue and to innovate in the generative field. AI.
The event was co-chaired by Aude Oliva, director of the MIT-IBM Watson AI Lab at MIT and principal investigator at the Computer Science and Artificial Intelligence Laboratory (CSAIL); Bill Aulet, Ethernet Inventors Professor of Practice at the MIT Sloan School of Management and director of the Martin Trust Center; and Dina Katabi, Thuan Professor (1990) and Nicole Pham in the Department of Electrical Engineering and Computer Science, director of the Center for Wireless Networks and Mobile Computing and principal investigator of CSAIL.
Twelve teams of students and postdocs were competing for a number of prizes, including five MIT Ignite Flagship Prizes of $15,000 each, a special Flagship Prize for first-year undergraduate student teams, and prizes for second place. All prices were provided by the MIT-IBM AI Watson Lab. Teams were judged on their project’s innovative applications of generative AI, its feasibility, its potential for real-world impact, and the quality of its presentation.
After the 12 teams presented their technology, its potential to solve a problem and the team’s ability to execute the plan, a jury deliberated. As the audience awaited the results, remarks were made by Mark Gorenberg ’76, president of the MIT Corporation; Anantha Chandrakasan, dean of the MIT School of Engineering and Vannevar Bush Professor of Electrical Engineering and Computer Science; and David Schmittlein, John C. Head III dean and professor of marketing at the MIT Sloan School of Management. Among the winning students are:
MIT Ignite Flagship Awards
eMote (Philip Cherner, Julia Sebastien, Caroline Lige Zhang and Daeun Yoo): Identifying and expressing emotions can be difficult, especially for people on the alexithymia spectrum; Additionally, therapy can be expensive. eMote’s app allows users to identify their emotions, visualize them as art using the co-creative process of generative AI, and reflect on them via journaling, helping school counselors and therapists.
LeGT.ai (Julie Shi, Jessica Yuan and Yubing Cui): Immigration legal processes can be complicated and expensive. LeGT.ai aims to democratize legal knowledge. Using a platform with a large language model, rapid engineering and semantic search, the team will streamline a chatbot for making, searching and writing documents for businesses, as well as improve pre-screening and initial consultations.
Sunona (Emmi Mills, Selin Kocalar, Srihitha Dasari and Karun Kaushik): About half of a doctor’s day is spent on medical documentation and clinical notes. To solve this problem, Sunona leverages audio transcription and an extensive language model to transform audio from a doctor’s visit into notes and feature extraction, giving providers more time in their day.
UltraNeuro (Mahdi Ramadan, Adam Gosztolai, Alaa Khaddaj and Samara Khater): For approximately one in seven adults, a spinal cord injury, stroke or illness will result in motor impairment and/or paralysis. UltraNeuro’s neuroprosthetics will help patients regain some of their everyday abilities without invasive brain implants. Their technology leverages an electroencephalogram, smart sensors, and a multimodal AI system (muscle EMG, computer vision, eye movements) trained on thousands of movements to plan precise limb movements.
UrsaTech (Rui Zhou, Jerry Shan, Kate Wang, Alan He and Rita Zhang): Today’s education is marked by disparities and overworked educators. UrsaTech’s platform uses a large multimodal language model and delivery models to create lessons, dynamic content, and assessments to support teachers and learners. The system also offers immersive learning with AI agents for active learning for online and offline use.
MIT Ignite First-Year Undergraduate Team Flagship Award
Alicorn (April Ren and Ayush Nayak): Drug discovery represents significant biotechnology costs. Alikorn’s large language model-based platform aims to streamline the process of creating and simulating new molecules, using a generative adversarial network, a Monte Carlo algorithm to select the most promising candidates, and physical simulation to determine chemical properties.
Finalist awards
Cyber Autonomous (James “Patrick” O’Brien, Madeline Linde, Rafael Turner and Bohdan Volyanyuk): Code security audits require expertise and are expensive. “Fuzzing” code—injecting invalid or unexpected input to reveal software vulnerabilities—can make software much more secure. Autonomous Cyber’s system leverages large language models to automatically embed “fuzzers” into databases.
EGM Generation (Noah Bagazinski and Kristen Edwards): Developing informed socio-economic development policies requires evidence and data. Gen EGM’s extensive language model system accelerates the process by reviewing and analyzing the literature, then produces an Evidence Gap Map (EGM), suggesting potential areas of impact.
Mattr AI (Leandra Tejedor, Katie Chen and Eden Adler): The datasets used to train AI models often have issues with diversity, fairness and completeness. Mattr AI solves this problem with generative AI with a large language model and stable diffusion models to augment datasets.
Neuroscreen (Andrew Lu, Chonghua Xue, and Grant Robinson): Screening patients for inclusion in a dementia clinical trial is expensive, often takes years, and usually results in ineligibility. Neuroscreen uses AI to more quickly assess the causes of patients’ dementia, leading to more efficient recruitment into clinical trials and treatment of conditions.
The Data Provenance Initiative (Naana Obeng-Marnu, Jad Kabbara, Shayne Longpre, William Brannon and Robert Mahari): Datasets used to train AI models, especially large language models, often have missing or incorrect metadata, leading to raises concerns about legal and ethical issues. The Data Provenance Initiative uses AI-assisted annotation to audit datasets, track data lineage and legal status, improve data transparency, legality and ethical concerns regarding data.
Theia (Jenny Yao, Hongze Bo, Jin Li, Ao Qu and Hugo Huang): Scientific research and the online dialogue surrounding it often take place in silos. Theia’s platform aims to break down these walls. Generative AI technology will summarize papers and help guide research directions, providing a service to academics as well as the broader scientific community.
After the MIT Ignite competition, the 12 teams selected to present were invited to a networking event as an immediate first step in bringing their ideas and prototypes to fruition. Additionally, they were invited to further develop their ideas with support from the Martin Trust Center for MIT Entrepreneurship through StartMIT or MIT Fuse and the Watson AI Lab at MIT-IBM.
“In the months since I arrived (at MIT), I’ve learned a lot about how people at MIT think about entrepreneurship and how it’s really integrated into everything everyone does at the Institute, from first-year students to professors to alumni. — they are truly motivated to share their ideas with the world,” said President Kornbluth. “Entrepreneurship is an essential part of our goal to organize for positive impact. »
