Serving as co-chairs for the occasion had been Aude Oliva, MIT director of the MIT-IBM Watson AI Lab and a principal investigator within the Laptop Science and Synthetic Intelligence Laboratory (CSAIL); Invoice Aulet, the Ethernet Inventors Professor of the Apply on the MIT Sloan College of Administration and director of the Martin Belief Heart; and Dina Katabi, the Thuan (1990) and Nicole Pham Professor within the Division of Electrical Engineering and Laptop Science, director of the Heart for Wi-fi Networks and Cell Computing, and a CSAIL principal investigator.
Twelve groups of scholars and postdocs had been competing for numerous prizes, together with 5 MIT Ignite Flagship Prizes of $15,000 every, a particular first-year undergraduate scholar crew Flagship Prize, and runner-up prizes. All prizes had been supplied by the MIT-IBM AI Watson Lab. Groups had been judged on their venture’s modern purposes of generative AI, feasibility, potential for real-world affect, and the standard of presentation.
After the 12 groups showcased their expertise, its potential to handle a problem, and the crew’s capacity to execute the plan, a panel of judges deliberated. Because the viewers waited for the outcomes, remarks had been made by Mark Gorenberg ’76, chair of the MIT Company; Anantha Chandrakasan, dean of the MIT College of Engineering and the Vannevar Bush Professor of Electrical Engineering and Laptop Science; and David Schmittlein, the John C. Head III Dean and professor of promoting on the MIT Sloan College of Administration. The coed winners included:
MIT Ignite Flagship Prizes
eMote (Philip Cherner, Julia Sebastien, Caroline Lige Zhang, and Daeun Yoo): Typically figuring out and expressing feelings is tough, notably for these on the alexithymia spectrum; additional, remedy could be costly. eMote’s app permits customers to determine their feelings, visualize them as artwork utilizing the co-creative strategy of generative AI, and replicate on them by journaling, thereby aiding faculty counselors and therapists.
LeGT.ai (Julie Shi, Jessica Yuan, and Yubing Cui): Authorized processes round immigration could be sophisticated and expensive. LeGT.ai goals to democratize authorized information. Utilizing a platform with a big language mannequin, immediate engineering, and semantic search, the crew will streamline a chatbot for completion, analysis, and drafting of paperwork for companies, in addition to enhance pre-screening and preliminary consultations.
Sunona (Emmi Mills, Selin Kocalar, Srihitha Dasari, and Karun Kaushik): About half of a health care provider’s day is consumed by medical documentation and medical notes. To deal with this, Sunona harnesses audio transcription and a big language mannequin to rework audio from a health care provider’s go to into notes and have extraction, affording suppliers extra time of their day.
UltraNeuro (Mahdi Ramadan, Adam Gosztolai, Alaa Khaddaj, and Samara Khater): For about one in seven adults, spinal wire harm, stroke, or illness will induce motor impairment and/or paralysis. UltraNeuro’s neuroprosthetics will assist sufferers to regain a few of their every day skills with out invasive mind implants. Their expertise leverages an electroencephalogram, sensible sensors, and a multimodal AI system (muscle EMG, laptop imaginative and prescient, eye actions) educated on hundreds of actions to plan exact limb actions.
UrsaTech (Rui Zhou, Jerry Shan, Kate Wang, Alan He, and Rita Zhang): Training at present is marked by disparities and overburdened educators. UrsaTech’s platform makes use of a multimodal giant language mannequin and diffusion fashions to create classes, dynamic content material, and assessments to help academics and learners. The system additionally has immersive studying with AI brokers for energetic studying for on-line and offline use.
First-12 months Undergraduate Pupil Staff MIT Ignite Flagship Prize
Alikorn (April Ren and Ayush Nayak): Drug discovery accounts for vital biotech prices. Alikorn’s giant language model-powered platform goals to streamline the method of making and simulating new molecules, utilizing a generative adversarial community, a Monte-Carlo algorithm to vet essentially the most promising candidates, and a physics simulation to find out the chemical properties.
Runner-up Prizes
Autonomous Cyber (James “Patrick” O’Brien, Madeline Linde, Rafael Turner, and Bohdan Volyanyuk): Code safety audits require experience and are costly. “Fuzzing” code — injecting invalid or sudden inputs to disclose software program vulnerabilities — could make software program considerably safer. Autonomous Cyber’s system leverages giant language fashions to routinely combine “fuzzers” into databases.
Gen EGM (Noah Bagazinski and Kristen Edwards): Making knowledgeable socioeconomic growth insurance policies requires proof and information. Gen EGM’s giant language mannequin system expedites the method by analyzing and analyzing literature, after which produces an proof hole map (EGM), suggesting potential affect areas.
Mattr AI (Leandra Tejedor, Katie Chen, and Eden Adler): Datasets which might be used to coach AI fashions typically have problems with variety, fairness, and completeness. Mattr AI addresses this with generative AI with a big language mannequin and secure diffusion fashions to enhance datasets.
Neuroscreen (Andrew Lu, Chonghua Xue, and Grant Robinson): Screening sufferers to probably be part of a dementia medical trial is dear, typically takes years, and principally leads to an ineligibility. Neuroscreen employs AI to extra rapidly assess sufferers’ dementia causes, resulting in extra profitable enrollment in medical trials and therapy of situations.
The Information Provenance Initiative (Naana Obeng-Marnu, Jad Kabbara, Shayne Longpre, William Brannon, and Robert Mahari): Datasets which might be used to coach AI fashions, notably giant language fashions, typically have lacking or incorrect metadata, inflicting concern for authorized and moral points. The Information Provenance Initiative makes use of AI-assisted annotation to audit datasets, monitoring the lineage and authorized standing of knowledge, enhancing information transparency, legality, and moral issues round information.
Theia (Jenny Yao, Hongze Bo, Jin Li, Ao Qu, and Hugo Huang): Scientific analysis, and on-line dialogue round it, typically happens in silos. Theia’s platform goals to convey these partitions down. Generative AI expertise will summarize papers and assist to information analysis instructions, offering a service for students in addition to the broader scientific group.
After the MIT Ignite competitors, all 12 groups chosen to current had been invited to a networking occasion as a direct first step to creating their concepts and prototypes a actuality. Moreover, they had been invited to additional develop their concepts with the assist of the Martin Belief Heart for MIT Entrepreneurship by StartMIT or MIT Fuse and the MIT-IBM Watson AI Lab.
“Within the months since I’ve arrived [at MIT], I’ve realized rather a lot about how MIT people take into consideration entrepreneurship and the way it’s actually constructed into all the pieces that everybody on the Institute does, from first-year college students to school to alumni — they’re actually motivated to get their concepts out into the world,” stated President Kornbluth. “Entrepreneurship is an important component for our objective of organizing for constructive affect.”
