This, that you see right here, is an artwork I produced using AI. First creating a person that doesn’t exist at all, with a GAN model (check https://www.thispersondoesnotexist.com/ to get one yourself!). Then, creating the painting artwork by using a styling model.

最近，我碰巧遇到了一件艺术品，使我想起了著名的“墙上的香蕉”作品。 只是这次，它才是对动物的虐待，而实际上是在使用标签。

The reason I came across that image was that recently I been reminded about the huge problem in social platforms related to abusive and violent content. Especially towards animals, who sadly don’t have the same rights in all countries. Like for example, Hungary, Finland, Romania, and even some states of the United States. I consider leaving that topic about animal rights and social media, for another time.

我遇到该图像的原因是，最近我被提醒有关社交平台中与滥用和暴力内容有关的巨大问题。 特别是对于动物，可悲的是，在所有国家/地区，动物都没有同样的权利。 例如，匈牙利，芬兰，罗马尼亚，甚至美国的某些州。 我考虑再讨论一次有关动物权利和社交媒体的话题。

When I saw that image I was outraged, I only thought about the millions of animals that are oppressed by our society in the dairy industry, meat industry, leisure industry with bullfights, and now in the art field.

当我看到那幅图像时，我很生气，我只想到了奶业，肉类行业，休闲斗牛行业以及当今艺术界受到我们社会压迫的数以百万计的动物。

I called out the situation, speaking my mind and opinion in a, maybe for some, exaggerated way. One of the responses I got, from one of the artist’s friend, was that I didn’t understand art, and if I considered this not to be art is because I don’t have a brain. The rest of the “arguing” in the responses was mainly about how I look, and other of my physical characteristics. They wouldn't reply whether or not they are supporting/promoting animal abuse through this type of “art”. But instead, every time I asked about it, this person only changed the topic back to my looks and content, complaining that what I do and this field is useless and no one sees value from it.

我大声疾呼，以某种夸张的方式表达了我的想法和见解。 我从一位艺术家的朋友那里得到的回应之一是我不了解艺术，如果我认为这不是艺术，那是因为我没有大脑。 回复中其余的“争论”主要是关于我的外表和其他身体特征。 他们不会通过这种“艺术”来回答是否支持/促进对动物的虐待。 但是，相反，每次我问这个问题时，此人只会将主题改回我的外观和内容，抱怨我所做的事情，而这个领域毫无用处，没有人看到它的价值。

I thought about it, while I was doing endless homework for university and work. And I thought how different some people can see automation, technology, and their inevitable influence in the future.

当我为大学和工作做无休止的作业时，我考虑了一下。 我认为有些人对自动化，技术及其未来不可避免的影响会有不同的看法。

Perhaps some people thought that algorithms could never be better than them as artists, as painters, sculptors, or scriptwriters. And perhaps they are right.

也许有人认为算法永远不会比作为艺术家，画家，雕塑家或脚本作者的算法更好。 也许他们是对的。

Or maybe one day AI will be able to recreate a "Banana on the wall", and understand art without the need of having a human brain.

也许有一天，人工智能将能够重新创建“墙上的香蕉”，并且不需要人脑就能理解艺术。

What I can be sure about, is that there is still a long long way for tech to continue surprising us in all the professional and non-professional fields known by men, today.

我很乐意与您分享一些免费的在线工具，供您尝试使用AI生成艺术品：

• Runway ML — An easy, code-free tool that makes it simple to experiment with machine learning models in creative ways. Our overall staff pick.

  Runway ML —一个简单，无代码的工具，使您可以轻松地以创造性的方式尝试机器学习模型。 我们的整体员工选择。

• GANBreeder — Breed two images to create novel new ones using GANBreeder. (Note that GANbreeder was renamed ArtBreeder, with several AI models to manipulate photos).

  GANBreeder —使用GANBreeder繁殖两个图像以创建新颖的图像。 (请注意，GANbreeder被重命名为ArtBreeder，具有用于处理照片的几种AI模型)。

• Magenta — An open-source research project exploring the role of machine learning as a tool in the creative process. (Coding skills required).

  洋红色-一个开源研究项目，探讨机器学习在创作过程中作为工具的作用。 (需要编码技能)。

• Processing — A flexible software sketchbook and language for learning how to code within the context of the visual arts. Includes p5js (Processing for Javascript) and Processing.py (Processing for Python). [Processing does not use AI, but is a great tool for generative visual art].

  处理-一种灵活的软件速写本和语言，用于学习如何在视觉艺术环境中进行编码。 包括p5js (Javascript处理)和Processing.py (Python处理)。 [处理过程不使用AI，但它是生成视觉艺术的绝佳工具]。

• ml5.js — ml5.js aims to make machine learning approachable for a broad audience of artists, creative coders, and students through the web.

  ml5.js — ml5.js旨在通过网络使广大艺术家，创意编码人员和学生可以使用机器学习。

• Magenta Studio — A collection of music plugins built on Magenta’s open-source tools and models.

  Magenta Studio-基于Magenta的开源工具和模型构建的音乐插件集合。

• AI Duet — Play with a piano that responds to you.

  AI Duet ( AI二重奏) —播放对您有React的钢琴。

• NSynth Sound Maker — Create your own hybrid sounds and instruments.

  NSynth Sound Maker-创建您自己的混合声音和乐器。

• MuseNet — Generate 4-minute musical compositions with 10 instruments, and combine styles from country to Mozart with MuseNet (also available on GitHub).

  MuseNet —用10种乐器生成4分钟的音乐作品，并使用MuseNet(也可在GitHub上)组合从乡村到莫扎特的风格。

• Pitch Detection — Use a pre-trained pitch detection model to estimate the pitch of sound files through a computer mic.

  音高检测—使用预先训练的音高检测模型通过计算机麦克风估计声音文件的音高。

• Deep Dream Generator — Stylize your images using enhanced versions of Google Deep Dream with the Deep Dream Generator.

  Deep Dream Generator –使用增强版的Google Deep Dream和Deep Dream Generator来风格化您的图像。

• DeepArt.io — Upload a photo and apply different art styles with this AI image generator, or turn a picture into an AI portrait of yourself (also check out DreamScope ).

  DeepArt.io —使用此AI图像生成器上传照片并应用不同的艺术风格，或将图片转换为自己的AI肖像(另请参阅DreamScope)。

• Visionist: Upload and apply AI Art styles to your photos, including abstract filters, cutout portraits, and more (iOS. Made by 3DTOPO Inc.).

  Visionist ：将AI Art样式上载并应用到您的照片中，包括抽象滤镜，抠图人像等(iOS。由3DTOPO Inc.制造)。

• GoArt — Create AI photo effects that make your photos look like famous portrait paintings with this AI image generator. (Web, Android and iOS. Made by Fotor).

  GoArt —使用此AI图像生成器创建AI照片效果，使您的照片看起来像著名的肖像画。 (网络，Android和iOS。由Fotor制造)。

• Deep Angel — Automatically remove objects or people from images. (Web. Made at MIT).

  Deep Angel (深天使) -自动从图像中删除对象或人物。 (网络。在麻省理工学院制造)。

• Google Deep Dream — GitHub repository for implementing Google Deep Dream.

  Google Deep Dream —用于实现Google Deep Dream的GitHub存储库。

• GANBreeder — Merge images together to create new pictures, make hybrid AI portrals and create wild new forms that have never been seen before. (GANbreeder is now called ArtBreeder).

  这幅肖像不是人类思想的产物。 它是由该代数公式定义的带有许多括号的算法创建的。 当它在10月23日至25日在佳士得拍卖行举办的Prints＆Multiples拍卖会上落下帷幕时，Edmond Belamy的肖像以令人难以置信的432,500美元成交，标志着AI艺术进入了世界拍卖舞台。

  The team collected a set of 15,000 portraits from the online art encyclopedia WikiArt, spanning the 14th to the 19th century, and fed them into the GAN algorithm. GAN algorithms have two parts: the generator and the discriminator. The generator learned the ‘rules’ of the portraits, “for example, everything has two eyes and a nose,” Caselles-Dupré says, describing a process that takes about two days. Then it starts to create new images based on those rules. Meanwhile, the discriminator’s job is to review the images and guess which are ‘real’ ones from the dataset and which are ‘fake ones’ from the generator.

  该团队从在线艺术百科全书WikiArt中收集了15,000张肖像，这些肖像跨越14至19世纪，并将其输入GAN算法。 GAN算法有两个部分：生成器和鉴别器。 生成者学会了肖像的“规则”，“例如，所有事物都有两只眼睛和鼻子，”Caselleles-Dupré说，描述了大约两天的过程。 然后，它开始根据这些规则创建新图像。 同时，鉴别者的工作是查看图像并猜测来自数据集的“真实”图像和来自生成器的“虚假”图像。

  It’s hard for us to naturally think that AI can be our ally, instead of our enemy. But that’s why we all should take part in this new, modern revolution.

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