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Demis Hassabis

04/25/25

@ Queens' College Cambridge

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.

Video

Sir Demis Hassabis - The Future of AI and Scientific Discovery

@ Queens' College Cambridge

Sir Demis Hassabis - The Future of AI and Scientific Discovery

04/25/25

Related Takeaways

Demis Hassabis

04/25/25

@ Queens' College Cambridge

Multidisciplinary research will be crucial in the next decade, combining expertise in areas like AI or machine learning with fields such as biology, chemistry, or mathematics.

Patrick Hsu

04/15/25

@ Sequoia Capital

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.

Max Jaderberg

04/29/25

@ Sequoia Capital

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.

Robin Sloan

11/30/17

@ Y Combinator

I've been really interested in machine learning, particularly its creative applications, and how it can transform the economy and interact with words, pictures, and sounds.

Andrew Ng

08/30/23

@ Stanford Online

I've realized that my focus should be solely on AI, as trying to master multiple fields like maritime shipping or healthcare is overwhelming and inefficient.

Robin Sloan

11/30/17

@ Y Combinator

I think the creative applications of machine learning are fascinating and present opportunities for artists to explore new forms of expression.

Neri Oxman

09/02/23

@ Lex Fridman

Every new project must incorporate simultaneous complexity and novelty across synthetic biology, material science, robotics, engineering, and computational design to create something truly innovative.

Patrick Hsu

04/15/25

@ Sequoia Capital

My vision extends beyond just creating better drugs; I aim to build a comprehensive understanding of biology at all scales.

Patrick Hsu

04/15/25

@ Sequoia Capital

At Arc Institute, we are focused on applying high-throughput scalable technologies to understand multi-system interactions, particularly at the neuro-immune interface.