In the Age of AI Art, What Can Originality Look Like? | Eileen Isagon Skyers | TED
81,257 views ・ 2023-08-11
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翻译人员: Shea Zhang
校对人员: Yip Yan Yeung
00:04
I want you to envision
a single piece of artwork
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我想请你想象一件
由人工智能生成的艺术品。
00:08
generated by artificial intelligence.
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00:11
When most of us think of AI art,
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大多数人想到 AI 艺术的时候,
00:14
I bet we're imagining something like this.
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我相信我们想到的是这样的东西。
00:19
We're all probably picturing
something totally different.
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我们可能都在想
一些完全不同的东西。
00:24
Today, with machine learning models like
DALL-E, Stable Diffusion and Midjourney,
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如今,借助 DALL-E、Stable Diffusion
和 Midjourney 等机器学习模型,
00:29
we've seen AI produce everything
from strange life forms
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我们已经看到 AI 生成了
奇怪的生命体、
00:35
to imaginary influencers
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虚拟网红
00:38
to entirely foreign,
curious kinds of imagery.
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和各种陌生的、奇怪的图像,
00:42
AI as a technology is fascinating to us
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AI 这项技术令我们着迷,
00:45
because we're inherently drawn
to things we cannot understand.
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因为我们天生
就会被无法理解的事物所吸引。
00:50
And with neural networks processing data
from thousands of other images
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神经网络可以处理上万张图片的数据,
00:54
made by people from every possible
generation, every art movement,
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来自每一代人、每一场艺术运动,
01:01
millions of images in one simple scan,
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数百万张图像
仅凭“一键扫描”即可完成,
01:06
they can produce visuals
that are so familiar
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它也可以生成我们既熟悉
01:08
yet strikingly unfamiliar.
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又非常陌生的图像。
01:11
More poetically, AI mirrors us.
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更诗意地说,
AI 是我们的一面镜子。
01:16
The world is beginning to change
right before our very eyes,
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世界在我们眼前变化,
01:19
and it's basically divided
into two schools of thought.
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现在分裂成两个思想流派。
01:24
There are pessimists who think AI poses
a great threat to human creativity.
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悲观主义者认为
AI 对人类的创造力构成了巨大威胁。
01:30
And then optimists who see it
as an extension of our creativity.
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乐观主义者
视 AI 为人类创造力的延伸。
01:35
So is it even possible to be truly
original as an artist anymore?
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作为一名艺术家,
是否还有可能真正做到原创?
01:41
How do we begin to critically engage
with artworks made by machines?
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我们又该如何开始深入
接触机器制作的艺术品?
01:48
We can start by looking at some metaphors,
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我们可以从真正突破
AI 界限的艺术家
01:51
narratives and insights from artists
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所使用的一些隐喻、
01:54
who are truly pushing
the boundaries of AI.
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叙事和见解开始。
01:58
Let's look to these moments
of delight, surprise,
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让我们来看看这些
充满欢乐、惊喜、
02:01
confusion and wonder
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困惑和惊奇的时刻 ,
02:03
that give us just one small glimpse
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它们让我们瞥见了
02:05
into the possibilities of encounter
with this technology.
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与这项技术接触的不同可能性。
02:09
Because as we've seen,
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正如我们现在所见,
02:10
this is a very moral and ethical encounter
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这是一次道德和伦理的相遇,
02:13
as much as an aesthetic one.
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也是一次美学上的遇见。
02:18
Mario Klingemann sold this piece
on auction in 2019.
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马里奥·克林格曼(Mario Klingemann)
在 2019 年拍卖会上出售了这件作品。
02:23
It is running an AI model
trained on thousands of portraits
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这个 AI 模型的训练材料是
02:27
from the 17th to 19th centuries.
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17 至 19 世纪的数千幅肖像画。
02:31
The model constantly reveals uncanny
interpretations of the human face.
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该模型不断呈现着
对人脸的诡异诠释。
02:37
Each one is unique,
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每一个都是独一无二的,
02:38
generated in real time
as the machine reads its own output.
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在计算机读取自己的输出时实时生成。
02:44
For the viewer, it's almost like peering
into the machine's hallucinations
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对于观众来说,
每生成一张新肖像,
02:48
as it conjures each new portrait.
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就像是在窥见这台机器的幻觉。
02:53
Sofia Crespo's series "Neural Zoo"
uses neural network interpretations
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索非亚·克雷斯波(Sofia Crespo)
《神经动物园》系列,
利用神经网络对现实世界的认知
02:58
of the real world
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02:59
to generate unreal sea creatures
and diverse biological forms.
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生成虚构的海洋生物
和各种生物形态。
03:05
Frogs look like flowers.
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像花一般的青蛙。
03:07
Translucent jellyfish
have vivid internal organs.
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半透明的水母
有着清晰可见的内脏器官。
03:11
There’s no one real creature
in these images,
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这些图像中没有真实的生物,
03:13
but AI allows us to envision otherworldly
lifeforms in impossible detail.
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AI 使我们能够以不受限的细节
设想不同寻常的生命。
03:22
This abstract piece by Sara Ludy
began as a digital painting.
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萨拉·卢迪(Sara Ludy)的这幅抽象作品
最初是一幅数字绘画。
03:26
It was augmented to fit a 16-by-9 ratio,
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在 DALL-E 2 扩图的
“撕裂边缘”功能之下,
03:29
using a prompt for "torn edges"
in DALL-E 2's Outpainting.
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它被延展到了 16 x 9 的比例。
03:34
Outpainting allows artists
to extend their creativity
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扩图让艺术家可以通过简单的提示
(例如 “撕裂边缘”)
03:38
beyond the frame using simple
language prompts like "torn edges."
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将创造力扩展到画面之外。
03:46
This piece by Ivona Tau
might read as a photograph,
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伊沃娜·塔乌(Ivona Tau)的作品
看上去像是一张照片,
03:49
but it is also the work of AI.
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但它其实是 AI 的作品。
03:52
It's the result of GAN training
on thousands of images
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这是 GAN (生成对抗网络)接受了
艺术家个人照片集中的数千张图像
03:55
from the artist's personal
photo collection.
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训练后的结果。
03:59
Tau curates from her own photographs,
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塔乌对自己的照片进行整理,
04:01
carefully choosing the inputs
and outputs for the model.
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仔细筛选了模型的输入和输出。
04:06
In many ways, AI art
is a form of curation.
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从某些方面来说,
AI 艺术是一种策展形式。
04:08
It becomes the process of selecting
from hundreds of images at a time.
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它是一次性从数百张图像中
进行筛选的过程。
04:16
This video pulls from models trained
on a massive data set of Tau's photos,
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这段视频由塔乌照片构成的
大型数据集训练的模型制作,
04:22
resulting in a kind of algorithmic memory.
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由此产生了一种算法记忆。
04:27
But she also created a destructed
data set for the model
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但是她还为模型创建了
一个销毁数据集,
04:30
to symbolize forgetting
or fleeting memory.
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代表遗忘或短暂的记忆。
04:36
And finally, we have Claire Silver.
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最后,我们来看看
克莱尔·西尔弗(Claire Silver)。
04:39
Silver has called herself
a “collaborative AI artist”
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西尔弗称自己为
“AI 合作艺术家”,
04:42
in that she works intentionally
with the machine to produce her art.
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因为她有意识地
使用机器创作自己的作品。
04:47
Her process is constantly evolving
as the tools evolve.
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随着 AI 工具的发展,
她的流程也在不断变化。
04:52
She often works
with inpainting techniques,
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她经常使用图像修复技术,
04:54
masking and transforming
just one small piece of an image.
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来掩盖和变换图像中的一小部分。
05:00
For this portrait, she shifted the opacity
of various sections with an Apple pencil,
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这幅肖像中,她用苹果铅笔
改变了各个部分的透明度,
05:05
transforming it bit by bit.
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一点一点转变了它。
05:07
She likens this technique to her version
of glazing in oil painting.
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她把这种技巧比作
在油画中的上釉。
05:15
Silver feeds AI-generated images
from one model into another,
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西尔弗将人工智能生成的图像
输入到一个个模型中,
05:20
effectively creating new forms
of language and understanding
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有效地为机器本身
创造了新的语言和理解形式。
05:24
for the machine itself.
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05:27
Her work is half master painting,
half digital art.
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她的作品一半是大师绘画,
一半是数字艺术。
05:30
Both old and new.
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新旧融合。
05:33
This piece pulls inspiration
from famed artists
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这件作品从约翰·辛格·萨金特、
伊芙琳·德摩根和古斯塔夫·克里姆特
05:37
like John Singer Sargent,
Evelyn De Morgan and Gustav Klimt,
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等著名艺术家那里汲取了灵感,
05:41
almost as an homage.
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几乎是一种致敬。
05:44
Because different AI models are trained
on different sets of information,
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由于不同的 AI 模型是
由不同的信息集训练的,
05:48
it's almost like they're all speaking
different languages.
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所以就像它们说着不同的语言。
05:52
AI is everywhere now.
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如今,AI 无处不在。
05:54
We are all now collectively
co-creating with AI,
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无论我们是否意识到,
我们每个人都在与 AI 共同创作。
05:58
whether we're aware of it or not.
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06:01
If we want to be a part of these worlds,
we cannot design alone.
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如果我们想成为这些世界的一部分,
我们不能孤军奋战地设计。
06:04
If we want to be culturally literate
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如果我们想对这些
新的图像、预测和形式
06:06
in these new kinds of images
and predictions and forms,
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培养一定的理解能力,
06:11
then looking to the work of artists
is a very productive place to start.
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这些艺术家的作品
会是个非常有效的起点。
06:18
We need to brace ourselves
for an increasingly technological future,
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我们要为日益技术化的未来
做好准备,
06:22
which is only going to multiply
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它会增加我们指尖上
06:25
all the creative possibilities
at our fingertips now.
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所有创造性的可能。
06:29
Thank you.
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谢谢。
06:30
(Applause)
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(掌声)
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