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How does this music make you feel?
这音乐让你感觉如何？
Do you find it beautiful? Is it creative?
你觉得好听吗？有创意吗？
Now, would you change your answers if you learned the composer was this robot?
那么如果现在告诉你作曲家是一个机器人，你会改变刚才自己的回答吗？
Believe it or not, people have been grappling with the question of artificial creativity,
信不信由你，人们一直在试图攻克人工创意
alongside the question of artifcial intelligence, for over 170 years.
以及人工智能这两大难题，为此研究了一百七十多年。
In 1843, Lady Ada Lovelace, an English mathematician considered the world's first computer programmer, wrote that
1843年，阿达·洛芙莱斯女士，一位被誉为世界上第一个电脑程序员的英格兰数学家写道，
a machine could not have human-like intelligence as long as it only did what humans intentionally programmed it to do.
如果人们只让机器按照所编写的程序去做，那么机器不会有人类一样的智慧。
According to Lovelace, a machine must be able to create original ideas if it is to be considered intelligent.
洛芙莱斯女士称，一个机器必须要能够创造新的想法才算是智能。
The Lovelace Test, formalized in 2001, proposes a way of scrutinizing this idea.
2001年形成的洛芙莱斯测试，提出了一个检测这个想法的方法。
A machine can pass this test if it can produce an outcome that its designers cannot explain based on their original code.
如果机器所创造出的作品，是它的设计师无法用程序解释的，就代表这部机器具有智慧。
The Lovelace Test is, by design, more of a thought experiment than an objective scientific test.
就实验设计来看，洛芙莱斯测试比较象是思想实验，而不属于客观的科学实验。
But it's a place to start.
但这是一个起点。
At first glance, the idea of a machine creating high quality, original music in this way might seem impossible.
乍看之下，机器似乎不可能创作出高质量的原创音乐。
We could come up with an extremely complex algorithm using random number generators,
我们可以用复杂的算法，结合随机产生的变量、
chaotic functions, and fuzzy logic to generate a sequence of musical notes in a way that would be impossible to track.
混沌公式和模糊逻辑，来产生一连串的音符，这个过程无法从原始程序解读、追踪。
But although this would yield countless original melodies never heard before,
虽然这会产生无数的、未曾听过的原创旋律，
only a tiny fraction of them would be worth listening to.
但是其中只有一小部分是令人觉得悦耳的。
With the computer having no way to distinguish between those which we would consider beautiful and those which we won't.
目前计算机仍然无法分辨人们认为好听的音乐以及不好听的音乐。
But what if we took a step back and tried to model a natural process that allows creativity to form?
但是，如果我们退一步来想，试着模拟出形成创意的自然过程呢？
We happen to know of at least one such process
目前，我们已经知道至少一种以上的过程，
that has lead to original, valuable, and even beautiful outcomes: the process of evolution.
它可以产生出原创的、有价值的甚至是悦耳的音乐作品，这个过程称为演化。
And evolutionary algorithms, or genetic algorithms that mimic biological evolution,
包括进化式算法，或是模仿生物进化的基因算法，
are one promising approach to making machines generate original and valuable artistic outcomes.
都是可能的研究方向，能让机器产生出具原创性而且有价值的艺术作品。
So how can evolution make a machine musically creative?
那么，什么样的演化过程，能使机器拥有创作音乐的能力？
Well, instead of organisms, we can start with an initial population of musical phrases,
不同于一般生物的演化，我们先以乐句作为演化的初始群体，
and a basic algorithm that mimics reproduction and random mutations
然后用基本的算法来模仿复制与随机变异，
by switching some parts, combining others, and replacing random notes.
例如将乐曲的某些部分进行交换、互相组合以及随机取代某些音符。
Now that we have a new generation of phrases,
现在，我们产生了新的乐句，
we can apply selection using an operation called a fitness function.
接着我们用适应函数来进行选择。
Just as biological fitness is determined by external environmental pressures,
正如同生物的适应性是由外在环境的压力来决定，
our fitness function can be determined by an external melody chosen by human musicians, or music fans,
我们的适应函数是根据音乐家或音乐爱好者所挑选出的乐曲旋律来决定，
to represent the ultimate beautiful melody.
这些代表了人们认为最优美的旋律。
The algorithm can then compare between our musical phrases and that beautiful melody,
然后，通过算法将机器创作出来的乐句与人们所挑选的优美旋律进行比较，
and select only the phrases that are most similar to it.
并选出相似性最高的乐句。
Once the least similar sequences are weeded out,
淘汰掉那些相似性较低的乐句之后，
the algorithm can reapply mutation and recombination to what's left,
算法会将剩下的部分再次进行突变和重组，
select the most similar, or fitted ones, again from the new generation, and repeat for many generations.
然后再次从新一代的乐句当中选出相似性或适应性最高的部分，这样的步骤会重复进行数个循环。
The process that got us there has so much randomness and complexity built in that the result might pass the Lovelace Test.
在这个创作过程中有许多的随机性和复杂性，所以能够通过洛芙莱斯的测试。
More importantly, thanks to the presence of human aesthetic in the process,
更重要的是，在创作的过程中结合了人类的审美观，
we'll theoretically generate melodies we would consider beautiful.
所以根据理论，我们能够产生出让人觉得优美的旋律。
But does this satisfy our intuition for what is truly creative?
但是，这是否符合人们直觉上所认为的“真正的创意”？
Is it enough to make something original and beautiful,
这样的创作方式是否能得到原创而且优美的作品？
or does creativity require intention and awareness of what is being created?
创作者在过程当中是否要有目的、能自我察觉，才能够称为创意？
Perhaps the creativity in this case is really coming from the programmers, even if they don't understand the process.
也许在这种情况下，创意是来自于程序设计师，但是他们并不了解整个创作过程。
What is human creativity, anyways?
究竟，什么是人类的创造力？
Is it something more than a system of interconnected neurons developed by biological algorithmic processes
也许，创意并不仅仅是一个由生物演算过程所发展而成、相互连结的神经元系统，
and the random experiences that shape our lives?
也不仅仅是形成我们的生活的一些随机经验。
Order and chaos, machine and human.
秩序与混乱，机器和人类。
These are the dynamos at the heart of machine creativity initiatives
这些共同构成了机器创作的核心动力，
that are currently making music, sculptures, paintings, poetry and more.
使得机器能创作出音乐、雕塑、绘画、诗歌和更多的作品。
The jury may still be out as to whether it's fair to call these acts of creation creative.
我们仍然无法定论机器创作是否可以算是具有创意。
But if a piece of art can make you weep, or blow your mind, or send shivers down your spine,
但是如果一件艺术作品能够令人感动，或是令你毕生难忘，甚至是令你觉得毛骨悚然，
does it really matter who or what created it?
究竟作者是人还是机器，真的重要吗？
