Can robots be creative

机器人可以发挥创造力吗

来源视频

How does this music make you feel?

Do you find it beautiful?

Is it creative?

Now, would you change your answers

if you learned  the composer was this robot?

Believe it or not,

people have been grappling with the question of artificial creativity,

alongside the question  of artifcial intelligence,

for over 170 years.

这音乐让你感觉如何？

你觉得好听吗？

有创意吗？

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？

信不信由你，

人们一直在试图攻克人工创意

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 a machine could not have human-like intelligence

as long as it only did what humans intentionally programmed it to do.

According to Lovelace,

a machine must be able  to create original ideas

if it is to be considered intelligent.

The Lovelace Test, formalized in 2001, proposes a way of scrutinizing this idea.

A machine can pass this test if it can produce an outcome

that its designers cannot explain  based on their original code.

1843年，Ada Lovelace夫人

一位被誉为世界上第一个 电脑程序员的英格兰数学家

写道机器不会有人类一样的智慧。

如果人们只让机器按照所编程程序它们的，

根据Lovelace，

一个机器必须要能够创造新的想法

才算是聪明。

2001年形成的Lovelace测试提出了一个检测这个想法的方法。

如果机器能够形成程序员无法根据原代码所解释的

输出才可以通过检测。

The Lovelace Test is, by design, more of a thought experiment

than an objective scientific test.

But it's a place to start.

At first glance,

the idea of a machine creating  high quality, original music in this way

might seem impossible.

We could come up with an extremely complex algorithm

using random number generators, chaotic functions, and fuzzy logic

to generate a sequence of musical notes

in a way that would be  impossible to track.

But although this would yield countless original melodies never heard before,

only a tiny fraction of them would be worth listening to.

With the computer having no way to distinguish

between those which we would consider beautiful

and those which we won't.

根据设计，Lovelace测试更像是思想实验

而非客观的科学检测。

但是这是一个起点。

乍一看

机器创作高质量，原版的音乐的想法

看起来不可能。

我们可以想出一个使用随机生成数字，

混乱的函数和模糊的逻辑来创造一系列音符的，

极为复杂的算法，

使其不可能理解。

但是即使这样能够产生无数的，没人听过的原版旋律，

只有一小部分值得一听。

电脑是无法区分

我们觉得好听

或者不好听的旋律。

But what if we took a step back

and tried to model a natural process that allows creativity to form?

We happen to know of at least one such process

that has lead to original, valuable, and even beautiful outcomes:

the process of evolution.

And evolutionary algorithms,

or genetic algorithms that mimic biological evolution,

are one promising approach

to making machines generate original and valuable artistic outcomes.

但是如果我们退一步

然后尝试塑造一个自然的创意形成过程会怎样？

我们恰巧知道至少一个

可以带来原创，宝贵甚至美丽的结果：

进化。

算法的进化，

或者模仿物种进化的基因算法，

是有希望让

机器产生原创的，珍贵的艺术品。

So how can evolution make  a machine musically creative?

Well, instead of organisms,

we can start with an initial population of musical phrases,

and a basic algorithm

that mimics reproduction  and random mutations

by switching some parts,

combining others,

and replacing random notes.

Now that we have  a new generation of phrases,

we can apply selection using  an operation called a fitness function.

Just as biological fitness is determined by external environmental pressures,

our fitness function can be determined by an external melody

chosen by human musicians, or music fans,

to represent the ultimate  beautiful melody.

因此计划是如何让一个机器音乐创新？

相比生物，

我们可以从最初的一些乐段

和一个基础的

通过调换有些部分，结合另一些

和替换一些随机的音节

来模仿生育和随机变异的

算法来完成。

现在我们有一个新的音段创作，

我们可以使用一个叫适应函数的运算。

就像生物的适应是由外界压力所导致，

我们的适应函数可以由音乐人或歌迷们

所选择的外界旋律所定，

以此来表现最终的，动听的旋律。

The algorithm can then compare between our musical phrases

and that beautiful melody,

and select only the phrases that are most similar to it.

Once the least similar sequences are weeded out,

the algorithm can reapply mutation and recombination to what's left,

select the most similar, or fitted ones, again from the new generation,

and repeat for many generations.

The process that got us there has so much randomness and complexity built in

that the result might  pass the Lovelace Test.

More importantly, thanks to the presence  of human aesthetic in the process,

we'll theoretically generate melodies we would consider beautiful.

算法可以比较我们的乐段和

动听的旋律

从而选择最相似的乐段。

一旦最不相似的组合被淘汰，

算法可以再次替换和组合剩下的，

在从新的组合选择最接近的，或者最适合的，

然后在许多的组合重复。

这个过程有那么多的随机性和复杂性

以至于结果可能可以通过Lovelace测试。

更重要的，多亏在这个过程中人类的审美，

我们理论上可以产生我们觉得动听的旋律。

But does this satisfy our intuition for what is truly creative?

Is it enough to make something original and beautiful,

or does creativity require intention and awareness of what is being created?

Perhaps the creativity in this case is really coming from the programmers,

even if they don't understand the process.

What is human creativity, anyways?

Is it something more than a system of interconnected neurons

developed by biological  algorithmic processes

and the random experiences  that shape our lives?

但是这能满足我们对真正创新的直觉吗？

这足够产生原创而美好的东西吗？

创新需要意图和意识吗？

也许这样的创新其实源于程序员，

即使他们不能理解过程。

什么才算是人类的创新？

是什么比一个互相连接的，

由生物算法过程演变的神经元系统

以及随机发生的，塑造我们生活的经验还要多的吗？

Order and chaos, machine and human.

These are the dynamos at the heart of machine creativity initiatives

that are currently making music,  sculptures, paintings, poetry and more.

The jury may still be out

as to whether it's fair to call  these acts of creation creative.

But if a piece of art can make you weep,

or blow your mind,

or send shivers down your spine,

does it really matter  who or what created it?

秩序与混乱，机器与人类。

现在有些创意机器的核心

正在创造音乐，雕塑，图画，诗歌等等。

评委可能会质问

是否因当把这些创造行为叫做有创意。

但是如果一枚艺术品能让你落泪，

能让你大开眼界，

或让你全身一颤，

谁创造的还重要吗？