The Thinking Game

While at Yale Young Global Scholars, I watched the documentary The Thinking Game, which follows Demis Hassabis and DeepMind as they progressed towards breakthroughs in AI. One of the biggest challenges Hassabis and his team encountered was protein-folding. Their solution, AlphaFold, revolutionized research. Scientists went from having a handful of reliable models of proteins to having access to models of every protein imaginable. 

This documentary was especially interesting because I had used AlphaFold before in my own research. I studied the evolutionary relationships between Dipcericin A, Diptericin B, and Diptericin C using phylogenetic trees, and AlphaFold modeling. Before doing this research, I mostly thought of biology and computer science as fields that barely overlapped. However, watching this movie and conducting my own research has taught me that those two fields often help the other advance. In this case, AI transformed research permanently and for the better. 

Research is becoming more interdisciplinary. Biology, computer science, artificial intelligence, and statistics are no longer completely separate fields. In order to study peptides, I utilized programming and AI. Future research will depend on people who can connect different areas of knowledge and scientists will need to understand not only the organism or molecule they are studying, but also the technology being used to study it.

The Thinking Game showed me that AlphaFold represents a larger shift in how scientific research is done. My own project on Diptericin showed me a small example of that shift. By combining biology with technology, I was able to study insect immune peptides in a way that would have been much harder without computational tools. Discoveries like AlphaFold are not just impressive because they use AI, but because they help scientists ask deeper questions about life, evolution, and the structures that make biology possible.