问题
In quantum computing, we are not just solving problems faster, we are solving problems that were previously thought to be unsolvable.
In mathematics, the art of proposing a question must be held of higher value than solving it.
Understanding the computational complexity of learning problems is essential for developing efficient algorithms.
The complexity of a learning problem is often determined by the size and structure of the hypothesis space.
"The study of computational complexity teaches us that some problems are inherently difficult, no matter how clever our algorithms are."
"The challenge in theoretical computer science is not just to solve problems, but to understand why they are hard to solve."
"The beauty of computational complexity lies in its ability to reveal the inherent difficulty of problems, regardless of the specific algorithms used to solve them."
Modularity is essential for building large systems, as it allows us to break down complex problems into smaller, more manageable parts.
The real question is not whether machines think but whether men do.
Any problem in computer science can be solved with another layer of indirection.
The Internet is a reflection of our society and that mirror is going to be reflecting what we see. If we do not like what we see in that mirror the problem is not to fix the mirror, we have to fix society.
The Internet is a reflection of our society and that mirror is going to be reflecting what we see. If we do not like what we see in that mirror the problem is not to fix the mirror, we have to fix society.
The real problem is not whether machines think but whether men do.
The study of algorithms is the study of methods for solving problems on a computer.
The question of whether computers can think is like the question of whether submarines can swim.
The intersection of cryptography and complexity theory is where some of the most fascinating problems in computer science reside.
The beauty of theoretical computer science lies in its ability to abstract and solve problems that seem insurmountable.
The key to solving complex problems is to ask the right causal questions.
Abstraction is not just about hiding details; it's about creating a clear and concise model of the problem domain.
Modularity is essential for building large, maintainable systems, as it allows us to break down complex problems into smaller, more manageable parts.