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So this is my niece. Her name is Yahli. She is nine months old.
这是我的侄女。她叫Yahli。她只有九个月大。
Her mum is a doctor, and her dad is a lawyer.
她妈妈是一名医生，爸爸是一名律师。
By the time Yahli goes to college,
等到Yahli上大学的时候，
the jobs her parents do are going to look dramatically different.
像她父母这样的工作将面目全非。
In 2013, researchers at Oxford University did a study on the future of work.
2013年，牛津大学的研究人员做了一项关于未来就业的研究。
They concluded that almost one in every two jobs have a high risk of being automated by machines.
他们得出结论：差不多将近一半的工作都有被机器自动化取代的危险。
Machine learning is the technology that's responsible for most of this disruption.
而机器学习应对这种颠覆负主要责任。
It's the most powerful branch of artificial intelligence.
它是人工智能最强大的分支。
It allows machines to learn from data and mimic some of the things that humans can do.
允许机器从现有数据中学习并模仿人类的所作所为。
My company, Kaggle, operates on the cutting edge of machine learning.
我的公司Kaggle专注于尖端的机器学习。
We bring together hundreds of thousands of experts to solve important problems for industry and academia.
我们召集了成千上万的专家，正为工业和学术界寻找重要问题的答案。
This gives us a unique perspective on what machines can do,
因此，我们可以从独特的视角来观察，
what they can't do and what jobs they might automate or threaten.
机器可以做什么，不可以做什么，哪些工作可以被自动化或受到威胁。
Machine learning started making its way into industry in the early '90s.
机器学习是在90年代初进入人们的视野。
It started with relatively simple tasks.
一开始，它只是执行一些相对简单的任务。
It started with things like assessing credit risk from loan applications,
像评估贷款申请的信用风险，
sorting the mail by reading handwritten characters from zip codes.
通过识别手写的邮政编码来检索邮件。
Over the past few years, we have made dramatic breakthroughs.
在过去几年里，我们取得了突破性进展。
Machine learning is now capable of far, far more complex tasks.
现在，机器学习可以完成非常复杂的任务。
