Edit: So sleepy Peaches.
New Zhiyuan Guide] Basic mathematics has been elevated to the only way to study AI! UC Berkeley professor launched the latest initiative, 31 AI bigwigs signed a joint letter, and Musk and Altman reached an agreement.
Just now, JELANI Nelson, a professor at UC Berkeley EECS, co-launched an initiative that emphasizes that a solid mathematical foundation is essential for artificial intelligence .
Address: While Elon Musk and Sam Altman have disagreed on many issues lately, they both agree that AI is built on solid mathematical foundations such as algebra and calculus. 」
At present, 31 industry bigwigs have signed their names on it.
If you want to do AI well, you must let your child learn math well
Artificial intelligence is about to profoundly change the face of society as we know it. In order to embrace this future, it is even more important to equip the workforce of the future with the knowledge to build and deploy AI technologies.
At the heart of modern AI innovation are core mathematical concepts such as algebra, calculus, and probability theory. Therefore, to get involved in the development of these technologies, students must build a solid foundation in mathematics.
We particularly applaud the University of California's recent clarification of its math admission requirements, ensuring that they must meet the state's standard definition of college readiness.
While current advances may seem like obsolescence in traditional mathematical topics such as calculus or algebra, the reality is quite the opposite.
In fact, modern AI systems are deeply rooted in mathematics, and a deep understanding of mathematics is essential for those working in this field.
The core of deep learning's algorithms—gradient descent—is an example of combining calculus and linear algebra.
Vectors and matrices form the basis of neural networks, and growth models on a logarithmic scale are essential for the science of neural network training.
Trigonometric functions and the Pythagorean theorem are far from obsolete , they are the basis for key tools in data science such as the Fourier transform and least squares.
Studying these core topics at the high school level is the best way to prepare for further study in machine learning, data science, or any STEM field, and we prefer to recruit students who have mastered the fundamentals rather than those who only know a thing or two about the latest tools or software.
If mathematics curriculum standards in public education are not maintained, the gap between public and private schools, especially in under-resourced areas, will widen, which will hinder efforts to diversify STEM fields.
All California children – not just those in private education – deserve a top-notch math education that will give us a strong foundation for our future.
We urge California policymakers to do their utmost to ensure that all children have access to such educational opportunities.
UC Berkeley clarifies the admission requirements for mathematics
A document published at UC Berkeley clearly sets out the requirements for applicants to take a math course.
Address: The focus of the task force is on the criteria for which courses can be substituted for the Algebra II and Math III requirements required for admission to the University of California, as well as the level of courses that applicants should be recommended to take in their fourth year of math.
Two main recommendations were made in the report.
First of all, in order to replace the Algebra II Math III course, it must also be a course that requires advanced algebra knowledge.
Therefore, a statistics course is not a substitute for a basic course in advanced algebra.
The Working Group made this recommendation because an in-depth understanding of algebra is fundamental to a variety of quantitative methods, and requiring an advanced algebra course would best prepare students for admission to the widest range of majors at university.
In the second proposal, applicants are required to take a fourth-year mathematics course in addition to the completion of three basic courses (Algebra I-Geometry-Algebra II or Mathematics I-II-III).
This fourth year of the course is designed to expand the knowledge of mathematics beyond the basic curriculum.
Therefore, for certain categories within Area C, the Working Group recommends a distinction between advanced mathematics courses and basic or mathematics elective courses.
By encouraging applicants to take the most rigorous high school math courses, Boars believes they will be better prepared for college-level quantitative courses.