Navigating the AI Era: Embracing Foundamentals and Cross-Disciplinary Learning

In the fast-paced world of AI development, the anxiety of being left behind is real for many. The arrival of tools like ChatGPT initially sparked excitement, leading individuals without a coding background, like myself, to join the AI learning trend. However, the rapid evolution in AI technology often renders one's efforts obsolete almost as soon as they begin. This phenomenon is particularly common in developer communities, where advancements like ChatGPT updates swiftly replace recently developed applications.

Reflecting on a video I created a year ago on seizing the opportunities brought by ChatGPT, the concept of natural language programming was shared, encouraging users to dive into AI and become super learners. Yet, in an era where AI understands almost everything and evolves faster than humans, the question arises – what should we learn to remain relevant?

The emergence of OpenAI's video generation model, Sora, blurs the lines between virtual and real, prompting a new wave of AI revolution. Besides enhancing video generation capabilities, Sora signifies a deeper understanding and simulation of the fundamental nature of the physical world, offering solutions for tasks like autonomous driving, bridging AI with the physical realm, and accelerating AGI development.

As a video creator, the implications of these advancements are significant. While aspiring towards grand goals, the reality might be that Sora's initial impact could target individuals like me - creators potentially replaced by AI before achieving these lofty ambitions.

Even before the AI boom, knowledge workers constantly faced the challenge of identifying what to learn, a trend noted by mathematician Richard Hamming in his book "The Art of Doing Science and Engineering." Hamming highlighted the exponential growth of knowledge, making it difficult for scientists to keep pace. He emphasized the importance of focusing on fundamentals and developing the ability to learn new fields – advice that remains relevant today.

Embracing Hamming's wisdom, in the AI era, one should prioritize "going basic" by mastering the fundamental, leverageable big ideas, and venture into cross-disciplinary learning to become a proficient novice in other domains. This approach ensures a strong foundation in core concepts and the ability to adapt and innovate across diverse fields.

In a world where AI is touted as an enabler, the key lies not in mastering the latest tools and technologies but in storytelling and understanding the core processes of video production. As AI progresses, technical expertise becomes less critical, while ideas and creativity take center stage. However, the term "ideas" must be redefined; true value lies not in simplistic concepts but in profound, fundamental insights derived from a deep understanding of a subject.

Many videos advocating AI-fueled wealth generation often promote cheap ideas, overlooking the execution challenges and the essence of genuine, high-value ideas rooted in core knowledge and understanding. While AI can streamline execution, the crux remains in conceiving valuable ideas, which require experience, active thinking, and a profound understanding of foundational principles.

In an AI-driven world, the leverage point for empowerment lies in grasping the fundamental, core knowledge across industries. This shift towards foundational learning, coupled with cross-disciplinary exploration, equips individuals with the leverage needed to thrive in the evolving landscape.

While AI accelerates cross-disciplinary learning, individuals must bridge the gap between their expertise and diverse fields to thrive in a rapidly changing environment. The support from AI in acquiring knowledge is immense, yet the challenge of active thinking remains crucial for understanding complex, high-order concepts.

Ultimately, in an AI-dominated future, the shift from domain-focused execution to cross-disciplinary decision-making and creation is imperative for survival. Embracing foundational knowledge, exploring big ideas, and venturing into diverse fields will define success in the era of AI evolution.