A Challenge from "Zero AI Knowledge" | Transitioning from a Different Field to the Path of a Data Scientist

At the University of Tokyo's Matsuo-Iwasawa Laboratory (Matsuo Lab), diverse students are carving out their own careers through education in AI and data science. In this interview, we spoke with Mr. Ozaki, who expanded his career by acquiring knowledge in generative AI and deep learning despite having absolutely no prior experience in AI or data science, about the appeal of the GCI (Global Consumer Intelligence) endowed chair program.

*This article is a transcript of an alumni interview video released on the official Matsuo Lab YouTube channel in July 2025.

Q. First, please introduce yourself and tell us about your current activities.

My name is Ozaki. I am currently a second-year master's student at the Graduate School of Engineering, Osaka Metropolitan University (at the time of the interview).
I originally specialized in engine design, but after entering the master's program, I shifted my research focus and began studying generative AI, such as LLMs (Large Language Models) and ChatGPT. Through the Matsuo Lab, I have had various experiences, including taking AI-related lectures and participating in projects to actually develop LLMs.

Q. What was your motivation for taking the GCI course?

I took and completed the GCI course in the summer of 2023. As I mentioned earlier, I originally came from a field completely different from AI and had absolutely no related knowledge. Therefore, I was looking for an opportunity to learn comprehensively from the basics of "what is AI" to data science, machine learning, and further to deep learning, and GCI was exactly the course I was looking for.

Q. How was it to actually take the GCI course?

The content was exactly as I expected, or even better. I look back on it as a very good opportunity to learn data science systematically and comprehensively.

What left a particularly strong impression on me was the final project. The task was to propose a business model utilizing the knowledge we had learned, and the theme allowed us to incorporate not only what we learned in the lectures but also more advanced content. It was a challenging assignment for me, but being able to tackle it by mobilizing everything I had learned up to that point and the applied technologies beyond that was a very meaningful experience.

AI will continue to branch out into various fields, including deep learning, as well as associated Large Language Models and image recognition. I feel that what I learned in GCI is the foundation for all of that, and that this knowledge will be useful in every situation.

Q. Did completing GCI have any impact on your career or research?

Previously, my career options were limited because I came from a non-IT background, but it is significant that after GCI, I became able to envision my career with a broader perspective that includes the IT field.

In my previous field of research, the speed of making new discoveries was a bit unsatisfying, and there were parts I couldn't enjoy. However, after learning about AI and LLMs, I realized that this field is a field that "cross-fields" (fuses) with various other areas, where new knowledge is discovered at a furious pace, and which can contribute to human happiness.
And I was able to realize that I am suited for digging deep into research and making new discoveries within that speed, and that I might have something close to a talent for it. I think it was a big first step toward choosing a "research career" where I can find new knowledge while fusing with various fields.

The trigger for that was undoubtedly participating in GCI and subsequently participating in projects like "GENIAC." It was precisely because I took lectures through GCI and met many people that I was able to seize the opportunity to serve as a team leader and participate in projects. I was very grateful for those opportunities.

Q. Please give a message to those who are considering taking GCI.

Data science is being incorporated into educational curricula, but it is not yet sufficient. However, it is expected that not having the power of data science or the ability to analyze things will put you at a significant disadvantage in the future.

This might be a bit blunt, but I think you should "just take it without saying anything" (laughs). AI and data science knowledge and skills are not taught in school but are necessary when you enter society, and it is a place where you can get everything, including the opportunities gained from the Matsuo Lab community. Why don't you consider taking the course?

Mr. Ozaki, who jumped into the world of AI research from a completely different field. Through his learning at GCI, he was fascinated by the potential of "cross-fields" that combine different fields with AI and the speed of research that carves out the unknown, and he discovered his own new talent. Matsuo Lab's courses are a place where you can solidify your foundation even from outside your specialty and make a big leap to the next stage, such as projects and research. Through taking GCI, why don't you also expand the possibilities of your career?