Two weeks of intense research, coding and testing came to a peak in the Arrillaga Alumni Center on Friday for the second annual Sushi Hackathon. Sixteen teams made live presentations with closing pitches to compete for a $30,000 grand prize. 

GDX Co. Ltd., a Japanese e-commerce company, partnered with the Stanford Shorenstein Asia-Pacific Research Center (APARC) to host the event, which invited participants to develop innovative artificial intelligence (AI) projects for supporting productive and sustainable fishing. Project groups included students from Stanford and universities nationwide, as well as engineers from leading technology companies including Nvidia, Google and OpenAI. 

“I believe deeply in the power of collaboration across borders, where diverse ideas and perspectives come together to create long-lasting engagement,” GDX Co. Ltd. COO Kenjiro Ikawa said. 

With more than double the number of applicants seeking to compete at the Sushi Hackathon compared to last year, Ikawa acknowledged the growing urge to tackle current-day problems through AI.

Ikawa said that fishers and sushi chefs face a multitude of challenges, including declining fish captures, poor quality of catches, climate change and supply chain inefficiencies. He hoped that the hackathon would bring engineers ready to confront obstacles in the fishing industry and help GDX Co. Ltd. “maximize opportunity to find treasure” and innovative solutions.

Throughout the day, teams rose to present and answer questions from the audience and six judges. Projects included dashboards for Peruvian fishing co-operatives to plan trips, market analysis of fish prices and on-board voice assistants that used machine learning to read sonar data aloud to fishers. 

Attendees reconvened in the evening to hear the announcement of the top three prizes. After nearly four hours of presentations and judging, Sushinnovation was awarded the top prize.

The winning team, which was comprised of four students from the University of California (UC) Santa Cruz, UC Davis and San Jose State University (SJSU), used a sensor installed on fishing boats to detect signals indicating potential signs of engine failure or mechanical issues. Their project, Polaris, is a machine learning program designed to interpret these warning signals, notify fishers about problems and guide them through the repair process. The Sushinnovation team used transformer architecture, similar to the backbone of large language models (LLMs) like ChatGPT, to create Polaris. 

Rome Drori, a senior from SJSU, likened the feeling of winning to “relief.” The team faced a variety of technical challenges, even in the minutes leading up to their live presentation. 

This year’s win was also a story of redemption for the team: during the first Sushi Hackathon in 2024, Sushinnovation finished in second place. 

The team said that this year, they focused on fishers’ needs first by driving to Half Moon Bay to meet with fishers before conceptualizing their idea. From there, they decided to solve a problem many fishers faced: dealing with mechanical failures that prevented them from spending time fishing. 

“I listened to a series of great presentations with creative, innovative ideas and cool, cool demos,” Kiyoteru Tsutsui, sociology professor and APARC director, said.

Tsutsui described Sushinnovation’s reaction to winning — leaping into the air with loud cheers — as “pure joy.”

The members of Sushinnovation plan to continue their studies, with many saying they would use their split of the grand prize for their tuition. Drori said he would soon return to studying for his midterm — but only after attending a sushi dinner hosted for the winners. 

Team Pill Snap, composed of UC San Diego students Brian Liu, Shawn Pana, Caylin Canoy and Reagan Hsu, earned third place. They focused on addressing the health and mobility of fishermen. “I was very shocked to learn that one in three fishers experience carpal tunnel syndrome,” Liu said. 

“We believe that for the welfare of fishers, we care not only just about the income they make, but also their health in general,” Canoy said. Their collective concern for the fishers’ nerve conditions motivated them to build a specialized glove that reduces risk of carpal tunnel syndrome. 

“Knowing the needs of fishers in their daily life from their requests is something that should be taken more seriously, especially in AI solutions,” said Zijian (Carl) Ma, a first-year Stanford Ph.D. candidate in bioengineering and first-time hackathon participant. 

The event also featured highlighted speakers who presented on the broader implications of AI on global public speech, economy and democracy. 

“You are the first generation, if you are a young person, to be born in an environment of very high PPM,” said Audrey Tang, a former minister of digital affairs in Taiwan and keynote speaker of the event. PPM, she explained, stands for “polarization per minute.” 

Tang emphasized the importance of “public, portable and pluralistic” developments in AI as the technology becomes increasingly integrated in everyday life. 

She contrasted the “vertical alignment” of companies using AI to drive up engagement and clicks with the need for “horizontal alignment,” which emphasizes strengthening people’s relationships with each other, AI and the natural world. 

“Are we building AI systems to supercharge profit, or are we building it to foster cooperation?” Tang said. 

Tang also acknowledged the surging energy demands of massive LLMs like Claude or ChatGPT, which can require up to 10 times as much energy as a traditional search. The solution, she said, may lie in using much smaller models specialized for certain tasks, like language translation. These models would demand significantly less energy and could be more accurate than those built for a wide range of general tasks. 

Tsutsui shared that learning about the hackers’ solutions “gave [him] hope that the future will be filled with a lot of new innovations that take advantage of and leverage generative AI.” 

“When we see machine learning, let’s make it collective learning,” Tang said to participants at the end of her keynote. “When we see user experience, let’s make it about human experience.”