理解
The most important thing in computer graphics is to understand light and how it interacts with surfaces.
"The progress in AI is not just about algorithms and data, but also about understanding the nature of intelligence itself."
"We are moving towards a world where machines will be able to understand and interpret the world in a way that is similar to how humans do."
"The future of AI is not just about making machines smarter, but also about making them more human-like in their understanding and interaction."
"Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts."
The brain is a complex system, and we are just beginning to understand how it works.
We need to understand the brain to build better AI.
The future of AI is in understanding how the brain works.
"We are still in the early days of understanding how to build truly intelligent systems."
"The future of AI lies in making machines that can understand and reason about the world."
"The key to AI is understanding how to build systems that can learn from data."
A well-designed system should be easy to use, easy to understand, and easy to modify.
The key to understanding cryptography is understanding that it's not just about keeping secrets, but about managing trust.
The development of robust learning algorithms requires a deep understanding of the underlying data distribution.
The challenge in computational learning theory is to understand the capabilities and limitations of learning algorithms.
To understand the future of secure communication, one must first understand the limitations of current cryptographic methods.
The causal model is the key to making sense of the world.
The causal approach is about understanding the mechanisms that generate the data.
The causal revolution is not just about AI; it's about rethinking how we understand the world.
The future of AI lies in understanding causality, not just correlation.