朱迪亞·珀?duì)?/span>
概率推理和因果推理的先驅(qū)
The future of AI lies in understanding causality, not just correlation.
人工智能的未來(lái)在于理解因果關(guān)系，而不僅僅是相關(guān)性。
The causal revolution is about empowering machines to think like humans.
因果革命是關(guān)于賦予機(jī)器像人類一樣思考的能力。
The ability to imagine counterfactuals is what distinguishes humans from machines.
想象反事實(shí)的能力是區(qū)分人類和機(jī)器的關(guān)鍵。
The language of causality is the language of science.
因果關(guān)系的語(yǔ)言是科學(xué)的語(yǔ)言。
The essence of causal inference is to go beyond the data and ask what would happen if we intervene.
因果推斷的本質(zhì)是超越數(shù)據(jù)，詢問(wèn)如果我們干預(yù)會(huì)發(fā)生什么。
Data are profoundly dumb; they tell you nothing about causes and effects.
數(shù)據(jù)是非常愚蠢的；它們不會(huì)告訴你任何關(guān)于因果關(guān)系的信息。
The ladder of causation has three rungs: seeing, doing, and imagining.
因果關(guān)系的階梯有三個(gè)梯級(jí)：觀察、行動(dòng)和想象。
To understand is to know what causes what.
理解就是知道什么導(dǎo)致什么。
Causality is the fabric of the universe, and probability is its language.
因果關(guān)系是宇宙的結(jié)構(gòu)，概率是其語(yǔ)言。
The purpose of computation is insight, not numbers.
計(jì)算的目的是洞察，而不是數(shù)字。