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关于理解的名人名言哲理格言警句语录 - 每日文摘
理解
Lisp is worth learning for the profound enlightenment experience you will have when you finally get it; that experience will make you a better programmer for the rest of your days, even if you never actually use Lisp itself a lot.
Lisp is worth learning for the profound enlightenment experience you will have when you finally get it; that experience will make you a better programmer for the rest of your days, even if you never actually use Lisp itself a lot.
Mathematics is not just about numbers, equations, computations, or algorithms: it is about understanding.
In the end, the goal of computer science is not just to build faster machines, but to deepen our understanding of the universe.
The challenge in theoretical computer science is not just to solve problems, but to understand the nature of problem-solving itself.
Understanding the limits of computation is as important as pushing its boundaries.
The quest for efficient algorithms is, at its core, a mathematical endeavor that challenges our understanding of complexity and computability.
Understanding the limits of computation requires a deep dive into the mathematical foundations that underpin algorithmic complexity.
Mathematics is not just about numbers and equations; it's about understanding the patterns and structures that underlie everything in the universe.
The true power of mathematics lies in its ability to simplify the complex, making the incomprehensible understandable.
Mathematics is the language of the universe, and through it, we can understand the fundamental principles that govern our world.
Algorithms are not just for solving problems; they are also for understanding the world.
The Internet is the first thing that humanity has built that humanity doesn't understand, the largest experiment in anarchy that we have ever had.
The study of computational complexity is not just about classifying problems; it is about understanding the nature of computation itself.
In mathematics, as in life, the most elegant solutions often arise from a deep understanding of the problem.
Understanding the limits of computation is as important as expanding its capabilities.
In quantum computing, we are not just pushing the boundaries of technology, we are pushing the boundaries of our understanding of the universe.
The challenge of quantum computing is not just in building the hardware, but in understanding the new algorithms that can take advantage of it.
Mathematics is not about numbers, equations, computations, or algorithms: it is about understanding.
Understanding the computational complexity of learning problems is essential for developing efficient algorithms.