Yann LeCun's advice for young students wanting to go into AI (www.businessinsider.com)

Yann LeCun, a prominent figure in AI and professor at NYU, has advised aspiring computer science majors to prioritize foundational subjects like mathematics and engineering over fleeting trends in technology. In a recent discussion, he stressed that a shallow understanding of math could leave students ill-prepared for rapid technological changes, suggesting that knowledge with a "long shelf life" is crucial for adapting to the evolving AI landscape. LeCun highlighted that students should invest in courses that provide deep mathematical insights, as theseare essential for advanced concepts in AI. His comments resonate within a broader debate on the direction of computer science curricula in the age of AI, where job readiness presents new challenges. Notable voices in the field, including Geoffrey Hinton, have echoed the importance of critical thinking and foundational knowledge, such as statistics and linear algebra. By drawing on engineering principles and advanced mathematics, students can gain valuable skills that are more relevant to AI development, rather than merely focusing on programming skills that may become obsolete. LeCun's insights serve as a crucial reminder of the importance of a strong academic foundation for future innovators in AI and machine learning.