This semester, students and postdocs from across MIT were invited to submit ideas for the first MIT Ignite: Generative ai Enterprise Competition. More than 100 teams submitted proposals for startups using generative ai technologies to develop solutions across a wide range of disciplines, including human health, climate change, education and workforce dynamics.
On October 30, 12 finalists presented their ideas in front of a panel of expert judges and a packed house at the Samberg Conference Centre.
“MIT has a responsibility to help shape a broadly beneficial future of ai innovation, and to achieve that, we need a lot of great ideas. So, we turned to a pretty reliable source of great ideas: MIT’s highly entrepreneurial students and postdocs,” 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 proposed by Kornbluth. This fall, across the Institute, researchers and students are exploring opportunities to contribute their knowledge of 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 innovate in generative matter. ai.
Co-chairs of the event were Aude Oliva, director of the MIT-IBM Watson ai Lab and principal investigator of 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 and Computer Engineering, director of the Center for Wireless Networks and Mobile Computing and principal investigator of CSAIL.
Twelve teams of students and postdocs competed for a series of prizes, including five MIT Ignite Flagship Awards of $15,000 each, a special Flagship Prize for teams of first-year undergraduates, and second-place prizes. All awards 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 the presentation.
After the 12 teams showcased their technology, its potential to address a problem, and the team’s ability to execute the plan, a panel of judges deliberated. As the audience awaited the results, Mark Gorenberg ’76, president of the MIT Corporation, gave remarks; Anantha Chandrakasan, dean of the MIT School of Engineering and Vannevar Bush Professor of Electrical and Computer Engineering; and David Schmittlein, John C. Head III dean and professor of marketing at the MIT Sloan School of Management. Winning students included:
MIT Ignite Flagship Awards
eMote (Philip Cherner, Julia Sebastien, Caroline Lige Zhang and Daeun Yoo): Sometimes identifying and expressing emotions is difficult, especially for those on the alexithymia spectrum; Additionally, therapy can be expensive. The eMote app allows users to identify their emotions, visualize them as art using the co-creative process of generative ai, and reflect on them through journaling, thus helping school counselors and therapists.
LeGT.ai (Julie Shi, Jessica Yuan and Yubing Cui): Immigration-related 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 optimize a chatbot to complete, research, and draft documents for businesses, as well as improve prescreening and initial queries.
Sunona (Emmi Mills, Selin Kocalar, Srihitha Dasari and Karun Kaushik): About half of a doctor’s day is consumed by medical documentation and clinical notes. To address this, Sunona leverages audio transcription and a large language model to transform audio from a doctor visit into notes and feature extraction, giving providers more time in their day.
ultraneuro (Mahdi Ramadan, Adam Gosztolai, Alaa Khaddaj, and Samara Khater): In approximately one in seven adults, a spinal cord injury, stroke, or illness will induce motor impairment and/or paralysis. UltraNeuro neuroprostheses will help patients regain some of their daily abilities without invasive brain implants. Its technology leverages an electroencephalogram, smart sensors, and a multimodal artificial intelligence system (muscle EMG, computer vision, eye movements) trained on thousands of movements to plan precise limb movements.
Ursa tech (Rui Zhou, Jerry Shan, Kate Wang, Alan He and Rita Zhang): Today’s education is marked by disparities and overburdened educators. UrsaTech’s platform uses a multimodal large language model and broadcast models to create lessons, dynamic content, and assessments to support teachers and students. The system also features immersive learning with ai agents for active learning for online and offline use.
College Freshman Team MIT Ignite Badge Award
Alikorn (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 screen the most promising candidates, and a physical simulation to determine the 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. “Fuzzy” code (injecting invalid or unexpected input to reveal software vulnerabilities) can make software significantly more secure. Autonomo Cyber’s system leverages large language models to automatically integrate “fuzzers” into databases.
Generation EGM (Noah Bagazinski and Kristen Edwards): Making informed socioeconomic development policies requires evidence and data. Gen EGM’s large language model system speeds up the process by examining and analyzing the literature, and then producing an evidence gap map (EGM), which suggests potential areas of impact.
Mattr ai (Leandra Tejedor, Katie Chen, and Eden Adler): Data sets used to train ai models often have diversity, fairness, and integrity issues. Mattr ai addresses this with generative ai with a large language model and stable diffusion models to augment data sets.
Neurodisplay (Andrew Lu, Chonghua Xue, and Grant Robinson): Screening patients to join a dementia clinical trial is expensive, often takes years, and in most cases results in ineligibility. Neuroscreen employs ai to more quickly assess the causes of patients’ dementia, leading to more successful clinical trial enrollment and disease treatment.
The data provenance initiative (Naana Obeng-Marnu, Jad Kabbara, Shayne Longpre, William Brannon and Robert Mahari): Data sets used to train ai models, particularly large language models, often have missing or incorrect metadata, raising concerns for legal and ethical reasons. The Data Provenance Initiative uses ai-assisted annotations to audit data sets, trace the lineage and legal status of data, improve transparency, legality and ethical concerns around data.
teia (Jenny Yao, Hongze Bo, Jin Li, Ao Qu and Hugo Huang): Scientific research and the online dialogue around it often occur in silos. Theia platform aims to tear down these walls. Generative ai technology will summarize articles and help guide research directions, providing a service to both academics and the broader scientific community.
Following 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 life. Additionally, they were invited to further develop their ideas with the support of the Martin Trust Center for MIT Entrepreneurship through StartMIT or MIT Fuse and the MIT-IBM Watson artificial intelligence laboratory.
“In the months since I arrived (at MIT), I have learned a lot about how people at MIT think about entrepreneurship and how it is really embedded in everything that everyone at the Institute does, from freshmen to seniors. teachers and alumni. — are really motivated to spread their ideas to the world,” said President Kornbluth. “Entrepreneurship is an essential element to our goal of organizing for positive impact.”
