人工智能正在迅速发展中，最近它又将触角延伸至艺术领域，试与艺术大咖们比肩。各行各业的你们还好吗？来看看人工智能如何大展神通吧~
Machines might one day replace human laborers in a number of professions, but surely they won't ever replace human artists. Right?
也许某一天，机器会在许多行业取代人类，但它绝对无法将艺术家踢出局。这是真的吗？
Think again. Not even our artists will be safe from the inevitable machine takeover, if a new development in artificial intelligence by a team of researchers from Rutgers University and Facebook's A.I. lab offers information of what's to come. They have designed an A.I. capable of not only producing art, but actually inventing whole new aesthetic styles akin to movements like impressionism or abstract expressionism, reports New Scientist.
且三思——如果罗格斯大学(Rutgers University)和脸书（Facebook）下属人工智能实验室的研究人员再搞出些AI新花样来，透露出未来的发展趋势，那么甚至连艺术家也难以在这机器横扫千行千业的大势中自保。据《新科学家》报道，这些研究人员已经设计出了一款人工智能产品，它不但能够制作艺术品，还能创作与艺术运动（如印象主义或抽象表现主义）类似的美学风格。
The idea, according to researcher Marian Mazzone, who worked on the system, was to make art that is “novel, but not too novel.” It's such an effective system that the art produced by it is already being given the thumbs-up by human critics when presented in public.
研究人员马里安·马佐尼（Marian Mazzone）表示，研究的指导理念是创作“新颖却不过分标新立异”的艺术。这一艺术创作系统成效显著，对外发布后，甚至对此持反对意见的人也对它所制作的艺术品啧啧称赞。
The algorithm at play is a modification of what's known as a generative adversarial network (GAN), which essentially involves two neural nets that play off against each other to get better and better results.
系统中运行的算法基于生成式对抗网络(GAN)进行了修改，GAN从本质上来说指的是两个神经网络相互对抗，寻求更佳结果。
The model used in this project involved a generator network, which produces the images, and a discriminator network, which "judges" whether it's art. The discriminator is programed with knowledge of 81,500 examples of human paintings that either count as art or don't, as well as knowledge of how to categorize art into known styles, and it uses these benchmarks to carry out the judging process.
该研究项目中的模型有两个网络，一是生成图像的生成器网络，二是“判别”图像是否为艺术的判别器网络。判别器的编程中，纳入了81500个艺术或非艺术人类画作样本的相关知识，以及如何将艺术品划分至已知艺术风格的方法，判别器根据这些标准进行判别。
This may seem overly simplistic, but there's a twist. Once the generator learns how to produce work that the distributor recognizes as art, it's given an additional directive: to produce art that doesn't match any known aesthetic styles.
这一过程看似简单至极，但亦存在曲折变化：一旦生成器学会了如何制作判别器认定为艺术品的作品，生成器就会接收到另一指令：制作不与任何已知美学风格相匹配的艺术品。
“You want to have something really creative and striking — but at the same time not go too far and make something that isn't aesthetically pleasing,” explained team member Ahmed Elgammal.
“我们想要制作出真正具有创造性、令人震撼的东西，但它同时又不能太过标新立异，这样会导致美感全无。”团队成员艾哈迈德·埃尔加马尔（Ahmed Elgammal）解释道。
The art that was generated by the system was then presented to human judges alongside human-produced art without revealing which was which. To the researchers' surprise, the machine-made art scored slightly higher overall than the human-produced art.
然后研究人员将这些由系统制作的成品同人工艺术品一并展出，不作任何区分，供观众评判。令他们意外的是，总体上机器制作的艺术品得分稍微高。
Of course, machines can't yet replace the meaning that's infused in works by human artists, but this project shows that artist skillsets certainly seem duplicatable by machines.
当然，机器还无法取代人工艺术品中糅杂的“涵义”，但该项目表明，机器似乎一定能够复制艺术家的创作技巧。
What will it take for machines to produce content that's infused with meaning? That might be the last A.I. frontier. Human artists can at least hang their hats on that domain ... for now.
如何才能使机器制作的产品包含人工艺术品当中的涵义呢？这可能是人工智能发展的最后一道防线了。至少现在看来，人类艺术家还能在这一领域立足。
“Imagine having people over for a dinner party and they ask, ‘Who is that by?’ And you say, ‘Well, it's a machine actually’. That would be an interesting conversation starter,” said Kevin Walker, from the Royal College of Art in London.
“假设邀请人们来参加一场晚宴，他们问，‘宴会是谁举办的呢？’，然后你回答说，‘事实上，是一台机器’。这会是个有趣的话头儿，”来自伦敦皇家艺术学院的凯文·沃尔克（Kevin Walker）说。