Can robots be creative

機(jī)器人可以發(fā)揮創(chuàng)造力嗎

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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.

這音樂讓你感覺如何？

你覺得好聽嗎？

有創(chuàng)意嗎？

那么如果現(xiàn)在告訴你作曲家 是一個機(jī)器人，

你會改變剛才自己的回答嗎？

信不信由你，

人們一直在試圖攻克人工創(chuàng)意

及人工智能這兩大難題，

為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

一位被譽(yù)為世界上第一個 電腦程序員的英格蘭數(shù)學(xué)家

寫道機(jī)器不會有人類一樣的智慧。

如果人們只讓機(jī)器按照所編程程序它們的，

根據(jù)Lovelace，

一個機(jī)器必須要能夠創(chuàng)造新的想法

才算是聰明。

2001年形成的Lovelace測試提出了一個檢測這個想法的方法。

如果機(jī)器能夠形成程序員無法根據(jù)原代碼所解釋的

輸出才可以通過檢測。

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.

根據(jù)設(shè)計(jì)，Lovelace測試更像是思想實(shí)驗(yàn)

而非客觀的科學(xué)檢測。

但是這是一個起點(diǎn)。

乍一看

機(jī)器創(chuàng)作高質(zhì)量，原版的音樂的想法

看起來不可能。

我們可以想出一個使用隨機(jī)生成數(shù)字，

混亂的函數(shù)和模糊的邏輯來創(chuàng)造一系列音符的，

極為復(fù)雜的算法，

使其不可能理解。

但是即使這樣能夠產(chǎn)生無數(shù)的，沒人聽過的原版旋律，

只有一小部分值得一聽。

電腦是無法區(qū)分

我們覺得好聽

或者不好聽的旋律。

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.

但是如果我們退一步

然后嘗試塑造一個自然的創(chuàng)意形成過程會怎樣？

我們恰巧知道至少一個

可以帶來原創(chuàng)，寶貴甚至美麗的結(jié)果：

進(jìn)化。

算法的進(jìn)化，

或者模仿物種進(jìn)化的基因算法，

是有希望讓

機(jī)器產(chǎn)生原創(chuàng)的，珍貴的藝術(shù)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.

因此計(jì)劃是如何讓一個機(jī)器音樂創(chuàng)新？

相比生物，

我們可以從最初的一些樂段

和一個基礎(chǔ)的

通過調(diào)換有些部分，結(jié)合另一些

和替換一些隨機(jī)的音節(jié)

來模仿生育和隨機(jī)變異的

算法來完成。

現(xiàn)在我們有一個新的音段創(chuàng)作，

我們可以使用一個叫適應(yīng)函數(shù)的運(yùn)算。

就像生物的適應(yīng)是由外界壓力所導(dǎo)致，

我們的適應(yīng)函數(shù)可以由音樂人或歌迷們

所選擇的外界旋律所定，

以此來表現(xiàn)最終的，動聽的旋律。

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.

算法可以比較我們的樂段和

動聽的旋律

從而選擇最相似的樂段。

一旦最不相似的組合被淘汰，

算法可以再次替換和組合剩下的，

在從新的組合選擇最接近的，或者最適合的，

然后在許多的組合重復(fù)。

這個過程有那么多的隨機(jī)性和復(fù)雜性

以至于結(jié)果可能可以通過Lovelace測試。

更重要的，多虧在這個過程中人類的審美，

我們理論上可以產(chǎn)生我們覺得動聽的旋律。

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?

但是這能滿足我們對真正創(chuàng)新的直覺嗎？

這足夠產(chǎn)生原創(chuàng)而美好的東西嗎？

創(chuàng)新需要意圖和意識嗎？

也許這樣的創(chuàng)新其實(shí)源于程序員，

即使他們不能理解過程。

什么才算是人類的創(chuàng)新？

是什么比一個互相連接的，

由生物算法過程演變的神經(jīng)元系統(tǒng)

以及隨機(jī)發(fā)生的，塑造我們生活的經(jīng)驗(yàn)還要多的嗎？

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?

秩序與混亂，機(jī)器與人類。

現(xiàn)在有些創(chuàng)意機(jī)器的核心

正在創(chuàng)造音樂，雕塑，圖畫，詩歌等等。

評委可能會質(zhì)問

是否因當(dāng)把這些創(chuàng)造行為叫做有創(chuàng)意。

但是如果一枚藝術(shù)品能讓你落淚，

能讓你大開眼界，

或讓你全身一顫，

誰創(chuàng)造的還重要嗎？