There's significant potential for breakthroughs by merging different subject areas, and I've always aimed to be multidisciplinary in my own work, integrating neuroscience, machine learning, and computer science.

Building a multidisciplinary team is challenging because there are more people in machine learning and biology than those who are truly bilingual in both fields.

The future landscape of AI may involve a combination of large models and smaller, specialized models that work in parallel, leveraging different areas of expertise.

The rapid advancements in AI are expected to solve major challenges in mathematics and science within the next decade, fundamentally changing our understanding of these fields.

Building a diverse team of experts in AI, chemistry, and biology is essential for questioning traditional approaches and fostering innovation in drug design.

The next decade will see profound changes in computing, driven by advancements in AI and the transition from traditional software to AI-driven solutions.

In the future, the pharmaceutical industry will integrate AI into drug design, making it an essential tool for biology and chemistry.

In the next 5 to 10 years, AI will discover new science, which could dwarf all other advancements.

The intersection of drug design and machine learning is a new field, and we need to bring together experts from both areas to drive breakthroughs.