You would be surprised at the number of domains where AI-based approaches are used. From optimal industrial control, process management and optimization, to business rules and financial modeling, to text analysis, machine translation, search engines...
Almost anywhere humans have been used to take complex decisions based on data, the amount of data modern electronic communications and acquisitions methods produce has become too much to handle without software. And only "intelligent" (or at least, less single-mindedly stupid) software can handle the complexity of the data, the complexity of the rules, and the numerous failure modes.
I know one software company in my city is using AI, that was developed as a Masters in Engineering project, to detect fraudulent bank/financial transactions. It's pretty interesting stuff. They look for strange recurring payments, or compare account numbers based on known terrorist organizations ...etc. I'm not sure how many people are doing similar work, but i'm sure with the lock-down on financial institutions these days these types of applications will become more prevalent (it's working for them).
Aside from direct application - AI people also are usually hardcore algorithms people by nature, and that kind of knowledge is sought after everywhere.
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您会对使用基于人工智能的方法的领域数量感到惊讶。 从最佳工业控制、流程管理和优化，到业务规则和财务建模，到文本分析、机器翻译、搜索引擎……
人类几乎在任何地方都被用来根据数据、现代电子通信的数据量做出复杂的决策如果没有软件，收购方法的产生已经变得难以处理。 并且只有“智能”（或者至少不是一心一意的愚蠢）软件才能处理数据的复杂性、规则的复杂性以及众多的故障模式。
You would be surprised at the number of domains where AI-based approaches are used. From optimal industrial control, process management and optimization, to business rules and financial modeling, to text analysis, machine translation, search engines...
Almost anywhere humans have been used to take complex decisions based on data, the amount of data modern electronic communications and acquisitions methods produce has become too much to handle without software. And only "intelligent" (or at least, less single-mindedly stupid) software can handle the complexity of the data, the complexity of the rules, and the numerous failure modes.
教授人工智能课程。 ;)
Professor for Artificial Intelligence courses. ;)
对我来说最明显的答案是游戏。
我认为游戏对人工智能来说是一个非常有趣的挑战，因为你本质上是玩输了，但是以一种有趣的方式 。
The most obvious answer to me are games.
I think games present a very interesting challenge for AI, because you're essentially playing to lose but in a fun way.
我知道我所在城市的一家软件公司正在使用人工智能（该人工智能是作为工程硕士项目开发的）来检测欺诈性银行/金融交易。 这是非常有趣的事情。 他们寻找奇怪的经常性付款，或根据已知的恐怖组织等比较帐号。 我不确定有多少人在做类似的工作，但我确信随着这些天金融机构的封锁，这些类型的应用程序将变得更加普遍（它对他们有用）。
I know one software company in my city is using AI, that was developed as a Masters in Engineering project, to detect fraudulent bank/financial transactions. It's pretty interesting stuff. They look for strange recurring payments, or compare account numbers based on known terrorist organizations ...etc. I'm not sure how many people are doing similar work, but i'm sure with the lock-down on financial institutions these days these types of applications will become more prevalent (it's working for them).
除了直接应用之外，人工智能人本质上也是硬核算法人，这种知识到处都受到追捧。
Aside from direct application - AI people also are usually hardcore algorithms people by nature, and that kind of knowledge is sought after everywhere.