Meet Henry Xie, the 17-year-old Portland student who found a way to make smaller AI models more empathetic using ChatGPT and Gemini without massive computing power

With artificial intelligence becoming a part of our daily lives, making AI sound genuinely understanding remains a challenge. A 17-year-old student from Portland has found a way that could help smaller AI models become better at responding to human emotions. The discovery is striking and different because it does not require the enormous computing resources used by the biggest AI systems.

Henry Xie, a student at Westview High School, created the project as part of the Regeneron Science Talent Search, one of the United States' leading science and mathematics competitions for high school students. His research focuses on a simple but important question: Can the empathy of large AI models be transferred to smaller, faster models?

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Who is Henry Xie?

Henry Xie is a 17-year-old student from Portland who has massive interest in computer science and artificial intelligence. At Westview High School, he leads the computer science club and is also part of the varsity swim team. His interest in technology extends beyond the classroom.

Henry is also the co-founder and president of Youth for Empathetic AI, a nonprofit organization that brings together students and researchers interested in developing ethical and human-centered artificial intelligence.

His work reflects a growing interest in making AI systems not only more capable, but also more considerate in how they communicate with people.

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Why does AI empathy matter?

Large language models (LLMs) can respond to human emotions in caring ways, but require significant computing power. Small language models (SLMs) — used in smartphones and many everyday applications — are faster and cheaper, but often less empathetic. Henry built a two-step model for training SLMs to display more empathy.

Henry developed a two-step approach for training smaller language models. First, he fed them published examples of empathetic responses from LLMs such as Gemini and ChatGPT, grounded in psychological theory. Then he used targeted prompts to help SLMs distinguish stronger empathetic responses from weaker ones.

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Henry used LLMs to judge their responses. Compared to untrained SLMs, the trained SLMs were seen as more empathetic in at least 90% of cases. His approach could make empathetic AI more widely available. The results were striking.

According to the project description, the trained smaller models were judged to be more empathetic than untrained SLMs in at least 90% of cases.

Why Henry's AI project could matter

The significance of the project goes beyond simply making an AI chatbot sound nicer.

If smaller AI models can become more emotionally responsive while retaining their advantages in speed and efficiency, empathetic AI could potentially become more accessible across everyday applications.

Smaller models are particularly useful when computing resources are limited or when applications need quick responses.

That could make techniques for improving their communication particularly valuable as AI becomes increasingly integrated into phones, applications and other consumer technologies.

Henry Xie's cybersecurity achievement

Henry's interest in computer science also includes cybersecurity.

He was a three-time semifinalist in the CyberPatriot National Youth Cyber Defense Competition, described as one of the world's largest youth cybersecurity competitions.

The achievement adds another dimension to his technology background, alongside his work in AI and his leadership of a student organization focused on ethical artificial intelligence.

FAQs

Who is Henry Xie?

Henry Xie is a 17-year-old student from Portland who attends Westview High School. He leads the school's computer science club and varsity swim team and has developed an AI project focused on improving empathy in smaller language models.

What did Henry Xie invent?

Henry developed a two-step training approach designed to help small language models produce more empathetic responses by learning from examples generated by large language models and then using targeted prompts to distinguish stronger responses from weaker ones.

What is Henry Xie's AI project about?

His project explores whether the empathetic behavior of large language models can be transferred to smaller language models that require less computing power.

What are small language models?

Small language models, or SLMs, are AI models designed to operate with fewer computing resources than large language models. Their efficiency makes them useful for devices and applications where speed, cost and computing power matter.

How successful was Henry's approach?

The trained SLMs were judged to be more empathetic than untrained smaller models in at least 90% of cases, according to the project information.

Which AI models did Henry use as examples?

His research used published examples of empathetic responses from large language models including Gemini and ChatGPT, with the examples grounded in psychological theory.

What is Youth for Empathetic AI?

Youth for Empathetic AI is a nonprofit co-founded by Henry Xie. It brings students and researchers together to work toward ethical and human-centered artificial intelligence.

What is CyberPatriot?

CyberPatriot is a major youth cybersecurity competition. Henry was a three-time semifinalist in the competition, adding cybersecurity to his experience in computer science and artificial intelligence.