After all, human beings have proven uniquely capable of interpreting the world around us and using the information we pick up to effect change. If we want to build machines to help us do this more efficiently, then it makes sense to use ourselves as a blueprint. Research into applied, specialized AI is already providing breakthroughs in fields of study from quantum physics where it is used to model and predict the behavior of systems comprised of billions of subatomic particles, to medicine where it being used to diagnose patients based on genomic data. Generalized AI is a bit further off—to carry out a complete simulation of the human brain would require both a more complete understanding of the organ than we currently have, and more computing power than is commonly available to researchers.
毕竟, 事实证明, 人类具有独特的能力, 能够解读我们周围的世界, 并利用我们获得的信息来影响变化。 如果我们想要制造机器来帮助我们更有效率地做这件事, 那么应该把我们自己当成目标蓝图。 应用型专业的人工智能研究已经在量子物理领域取得了突破, 模拟和预测了由数十亿亚原子粒子组成的系统的行为, 在医学领域, 用基于基因组数据来诊断病人。 距实现广义的人工智还有些遥远——要对人类大脑进行完整的模拟, 既需要比目前更全面的了解该器官, 也需要拥有比当前研究人员持有的更强大的计算能力。