Anima Anandkumar, a prominent AI professor at Caltech and director of AI research at NVIDIA, emphasizes that students interested in AI careers should prioritize curiosity and problem-solving skills over just coding abilities. She argues that while coding is important, it’s becoming increasingly automated, and the future of AI work will require broader skills. Anandkumar suggests that students should focus on developing strong mathematical foundations, critical thinking abilities, and a genuine interest in solving complex problems. She notes that by 2025, AI tools will likely automate many basic coding tasks, making pure programming skills less valuable than the ability to understand and frame problems effectively. The professor particularly emphasizes the importance of mathematics, especially linear algebra and probability, as fundamental building blocks for AI work. She also advocates for interdisciplinary learning, suggesting that combining AI knowledge with expertise in fields like biology, chemistry, or physics can lead to more innovative solutions. Anandkumar warns against the narrow focus on coding bootcamps and certification programs, instead encouraging students to pursue deeper understanding of AI principles and their applications. Her message aligns with the evolving nature of AI work, where problem formulation and creative thinking are becoming increasingly valuable compared to traditional coding skills.