Terence Tao: The Potential for AI in Science and Mathematics【獨家中英文字幕完整版】著名數學家陶哲軒牛津講座：人工智慧在科學和數學領域的潛力

The speaker discusses the concept of AI, its potential to change the world, and its underlying mathematics, emphasizing that AI is essentially a guessing machine driven by mundane mathematical processes.

Describes AI as a tool that accelerates tasks using weights and combinations, drawing a comparison to the invention of the jet engine and its transformative impact on travel.

Highlights modern AI tools' creative and untraditional nature, such as language models, which operate without needing precise programming but can lack reliability and predictability.

Discusses AI capabilities through examples like GPT-4's success in solving complex math problems but also its failures in simple arithmetic due to the nature of guessing and lack of internal computation.

Explores AI applications in science, including drug design, material science, and climate modeling, showcasing AI's potential to streamline processes and reduce candidate testing requirements.

Envisions AI's transformative role in mathematics, enabling massive collaboration, automating proofs, and enhancing mathematical reasoning, highlighting the synergy between AI and proof assistance technologies.

Discussing the process of formalizing mathematics through small, pedantic steps and breaking down complex proofs into manageable pieces.

Reflection on the importance of breaking down big concepts into atomic steps, focusing on fundamentals, and understanding basic principles.

Exploring how formal projects decouple high-level conceptual skills from low-level technical skills, allowing for specialization and focusing on specific tasks.

Speculating on the potential involvement of AI in formal projects and the ability of AI to participate in and contribute to mathematical tasks.

Discussing the future of mathematics education, specialization roles in mathematics, and the changing landscape of mathematical research and development.

Considering the evolving role of mathematics in the academic environment, integration with AI technologies, and its impact on various scientific disciplines.

Discussing the need for standardized models in different sciences, central repositories, open-source models, and competitions to drive innovation and progress.

Exploring the application of AI in problem-solving, the role of AI in simplifying complex problems, and the potential scalability of AI techniques in mathematics.