理解
The concept of polynomial-time reduction is central to understanding the structure of NP-complete problems.
The essence of computational complexity is to understand the limits of what can be computed efficiently.
The best way to understand something is to try to change it.
If you don’t strive to uncover what is unseen and understand its nature, you will be ill prepared to lead.
The beauty of biology lies in its ability to explain the diversity of life through simple principles.
The complexity of life is not a barrier to understanding, but a gateway to deeper insights.
The key to understanding life is to understand the interactions between its components.
The real challenge is not just to collect data, but to make sense of it.
The future of biology is in understanding the complexity of living systems.
The challenge of the future is not just to store more data, but to make sense of it.
The key to successful data management is understanding the data. If you don't understand your data, you can't manage it effectively.
Understanding the limits of computation is as important as understanding its possibilities.
The study of algorithms is not just about solving problems, but about understanding the limits of what is computationally possible.
The key to innovation is not just in creating new technologies, but in understanding how to apply them to solve real-world problems.
Cryptography is the art of transforming information into a form that is unintelligible to anyone who does not possess the key to unlock it.
UNIX is very simple, it just needs a genius to understand its simplicity.
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.