As we branch out into subjects like math and music, the biggest challenge is creating a learning experience that is as engaging and effective as our language courses.

The way we educate mathematics often fails to accommodate different learning styles, leading many to abandon the subject before finding their unique approach.

My parents emphasized the importance of education and pushed for my academic advancement, which led me to excel in math and eventually skip grades in school.

The mathematical community is a collective intelligence that surpasses any individual mathematician, as seen in collaborative platforms like MathOverflow, where diverse expertise contributes to solving complex problems.

DeepSeek's training pipeline focuses on assembling problems with verifiable outputs, particularly in math and coding, allowing the model to learn to think critically and produce correct answers without external examples.

In my classes, I encourage students to question everything and think critically, starting with intuitive questions rather than just focusing on mathematical equations.

To solve a difficult math problem, first find a version that simplifies the problem by turning off most difficulties, focusing on just one at a time.

Even small models can boost their performance in tasks like math with a small amount of reinforcement learning training.

Theoretical math requires a different way of thinking, where you need to sit with a problem for a long time, building intuition and discipline to solve it.