Google DeepMind team up to solve the Navier-Stokes million-dollar problem
10 months ago
- #Mathematics
- #Millennium Prize Problems
- #Artificial Intelligence
- Spanish mathematician Javier Gómez Serrano collaborates with Google DeepMind to solve the Navier-Stokes equations, a Millennium Prize Problem offering a $1 million reward.
- The Navier-Stokes equations, formulated in the 19th century, describe fluid motion and remain unsolved regarding their regularity or potential for sudden behavioral changes.
- A team of 20 researchers, including geophysicists and mathematicians, has been working discreetly for three years, leveraging AI to refine solutions and predict fluid behavior.
- Gómez Serrano's team uses machine learning neural networks to analyze singularities in fluid dynamics, with progress suggesting a solution may be imminent within five years.
- Other competing teams include Thomas Hou's group in California and Diego Córdoba's team in Madrid, each approaching the problem with different strategies.
- Gómez Serrano also contributed to AlphaEvolve, an AI system that solves complex mathematical problems with a 95% success rate, potentially revolutionizing mathematical research.
- Google DeepMind's Demis Hassabis predicts artificial general intelligence (AGI) could emerge by 2030, though Gómez Serrano remains cautiously optimistic about AI's future impact.