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AI ART
SATHYAPRIYA SB
RA2011008020021
SRM Institute of Science and Technology,
Ramapuram Campus
Introduction
What is AI art?
AI Art tools
Applications
Impact on artists
Future outlook
Conclusion
CONTENTS
AI Art is a current trend in the world of art that
is gaining popularity day-by-day. The concept is based
around the idea that machine learning algorithms are
capable of producing original images as output, when
appropriately trained using large computational resources
on a vast amount of image data.
After countless hours of training, the model, based
on what it learnt during the training process, is then
able to generate something completely new, something that
has never been drawn before – original AI art.
INTRODUCTION
It is beautiful how technology has advanced to the point where it is
able to engage in art creation. Only 15 years ago, this was barely
considered a possibility and today AI Art Shop displays a collection of
over 50 AI Portraits. AI algorithms, with appropriate training, are indeed
able to generate original images, however a lot of the output, even with a
lot of training, is either noise or art that believe me you would not like
to see.
So, this is where human involvement comes in. There needs to be a
team of people who understand art and are able to select and classify only
the best images. The next step once the paintings have been classified
and named, is to use a different group of AI algorithms to increase the
resolution of every selected image to allow for the best quality of
paintings.
INTRODUCTION
AI art refers to art generated with the assistance
of artificial intelligence. AI is a field of computer
science that focuses on building machines that mimic
human intelligence or even simulate the human brain
through a set of algorithms.
AI can construct novel works through machine
learning, using various self-learning algorithms that
derive knowledge from data. AI art is the result of a
collaboration between an artist and an AI system, but
the level of autonomy can vary considerably, and the
outcome relies heavily on the quality of the data the
AI learns from.
WHAT IS AI ART?
AI ART TOOLS
Google Deep Dream
WOMBO Dream
GauGAN2
ml5.js
Midjourney
DALL·E 2
DeepDream, released by Google
in 2015, is one of the more well-
known AI art tools. Initially, it
was invented to help scientists and
engineers to visualize patterns
learned by a neural network, a type
of machine learning algorithm.
Later the algorithm has become
a new form of abstract art due to
the dream-like psychedelic
appearance of the deliberately over-
processed images.
GOOGLE DEEP DREAM
Mike Tyka, eural net, Archival print, 2016
A neural network’s ability to recognize what’s in an image
comes from being trained on an initial data set. In Deep Dream’s
case, that data set is from ImageNet, a database created by
researchers at Stanford and Princeton who built a database of 14
million human-labeled images. But Google didn’t use the whole
database. Instead, they used a smaller subset of the ImageNet
database released in 2012 for use in a contest… a subset which
contained “fine-grained classification of 120 dog sub-classes.”
In other words, Google’s Deep Dream sees dog faces everywhere
because it was literally trained to see dog faces everywhere.
GauGAN2 is NVIDIA Research’s new AI model, named after post-
Impressionist painter Paul Gauguin creates photorealistic images
from simple elements a user can draw with simple graphic tools
like a paintbrush or paint bucket. Artists can also combine
sketches with a short text to design their own landscapes.
GauGAN2 is a widely used creative tool for visualizing concepts
or creating simulated photos based on nearly any input of the
creative mind.
GAUGAN2
Photorealistic AI art
tool powered by the
GauGAN2 AI model,
Courtesy NVIDIA
Another simple way to create
AI art is with the mobile and
browser application called WOMBO
Dream. The app creates generative
art from a descriptive text in
various pre-determined styles.
The app uses two machine
learning technologies that combine
a neural network to generate images
and an algorithm that interprets
text descriptions. Both algorithms
learn from each iteration, meaning
that every request generates a
unique outcome.
WOMBO DREAM
Example of AI-generated art made
with WOMBO Dream
Applications
Stock photography (customized)
Product photography
Creation of images for self-made card games,
tabletop games, comics,[46] book covers and album
art
Animations and videos (text-to-video)
High definition art from low-resolution images
(such as pixel art/retrogame characters or blurred
images) or sketches or low-quality images (such as
children's drawings) or "breathing life into a
'basic' scene" or refining details
Inpainting, Outpainting
IMPACT ON ARTISTS
If a machine can do only what it was programmed to do,
how can its behavior ever be called creative?
Some artists in 2022 have raised concerns about the
impact AI art could have on their ability to earn money,
particularly if AI art is used to replace artists working
in illustration and design. According to British trade
union Equity, "65% of performers think the development of
AI technology poses a threat to employment opportunities in
the performing arts sector."
IMPACT ON ARTISTS
Digital artist R. J. Palmer has stated that "I could
easily envision a scenario where using AI a single artist
or art director could take the place of 5-10 entry level
artists... I have seen a lot of self-published authors and
such say how great it will be that they don’t have to hire
an artist," adding that "doing that kind of work for small
creators is how a lot of us got our start as professional
artists."
Polish digital artist Greg Rutkowski has stated that
"it's starting to look like a threat to our careers,"
adding that it has gotten more difficult to search for his
work online many of the images returned by search engines
are generated by AI that was prompted to mimic his style.
FUTRE OUTLOOK
In the context of art creation and production, AI technologies
are starting to have an ever more important role. Not only in terms
of digitally and AI produced art, but also in all the aspects of
curation, exhibition and sale of traditional art as well. Having in
mind the rapid shift of attention towards online platforms and
digital showrooms due to the current global pandemic, the ongoing
circumstances contributed to the already rising interest in crypto
art and blockchain technologies which have the potential to
significantly impact and transform the art market.
Current trends indicate that AI technologies will become more relevant in
the analysis and production of art. We can expect that this will intensify the
methodological shift from traditional towards digital research practices in
the humanities, as well as result in a growing number of innovative research
projects that apply large scale quantitative methods to study art-related
historical questions. From the perspective of computer vision, there are still
many practical challenges that need to be solved in order to assist
researchers working on cultural digital archives.
With the development of AI models that can generate content which very
convincingly imitates human textual, visual or musical creations, many of our
traditional, as well as contemporary, theoretical and practical understandings
of art might become challenged
CONCLUSION
THANK YOU!

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AI Art

  • 1. AI ART SATHYAPRIYA SB RA2011008020021 SRM Institute of Science and Technology, Ramapuram Campus
  • 2. Introduction What is AI art? AI Art tools Applications Impact on artists Future outlook Conclusion CONTENTS
  • 3. AI Art is a current trend in the world of art that is gaining popularity day-by-day. The concept is based around the idea that machine learning algorithms are capable of producing original images as output, when appropriately trained using large computational resources on a vast amount of image data. After countless hours of training, the model, based on what it learnt during the training process, is then able to generate something completely new, something that has never been drawn before – original AI art. INTRODUCTION
  • 4. It is beautiful how technology has advanced to the point where it is able to engage in art creation. Only 15 years ago, this was barely considered a possibility and today AI Art Shop displays a collection of over 50 AI Portraits. AI algorithms, with appropriate training, are indeed able to generate original images, however a lot of the output, even with a lot of training, is either noise or art that believe me you would not like to see. So, this is where human involvement comes in. There needs to be a team of people who understand art and are able to select and classify only the best images. The next step once the paintings have been classified and named, is to use a different group of AI algorithms to increase the resolution of every selected image to allow for the best quality of paintings. INTRODUCTION
  • 5. AI art refers to art generated with the assistance of artificial intelligence. AI is a field of computer science that focuses on building machines that mimic human intelligence or even simulate the human brain through a set of algorithms. AI can construct novel works through machine learning, using various self-learning algorithms that derive knowledge from data. AI art is the result of a collaboration between an artist and an AI system, but the level of autonomy can vary considerably, and the outcome relies heavily on the quality of the data the AI learns from. WHAT IS AI ART?
  • 6. AI ART TOOLS Google Deep Dream WOMBO Dream GauGAN2 ml5.js Midjourney DALL·E 2
  • 7. DeepDream, released by Google in 2015, is one of the more well- known AI art tools. Initially, it was invented to help scientists and engineers to visualize patterns learned by a neural network, a type of machine learning algorithm. Later the algorithm has become a new form of abstract art due to the dream-like psychedelic appearance of the deliberately over- processed images. GOOGLE DEEP DREAM
  • 8. Mike Tyka, eural net, Archival print, 2016
  • 9. A neural network’s ability to recognize what’s in an image comes from being trained on an initial data set. In Deep Dream’s case, that data set is from ImageNet, a database created by researchers at Stanford and Princeton who built a database of 14 million human-labeled images. But Google didn’t use the whole database. Instead, they used a smaller subset of the ImageNet database released in 2012 for use in a contest… a subset which contained “fine-grained classification of 120 dog sub-classes.” In other words, Google’s Deep Dream sees dog faces everywhere because it was literally trained to see dog faces everywhere.
  • 10. GauGAN2 is NVIDIA Research’s new AI model, named after post- Impressionist painter Paul Gauguin creates photorealistic images from simple elements a user can draw with simple graphic tools like a paintbrush or paint bucket. Artists can also combine sketches with a short text to design their own landscapes. GauGAN2 is a widely used creative tool for visualizing concepts or creating simulated photos based on nearly any input of the creative mind. GAUGAN2 Photorealistic AI art tool powered by the GauGAN2 AI model, Courtesy NVIDIA
  • 11. Another simple way to create AI art is with the mobile and browser application called WOMBO Dream. The app creates generative art from a descriptive text in various pre-determined styles. The app uses two machine learning technologies that combine a neural network to generate images and an algorithm that interprets text descriptions. Both algorithms learn from each iteration, meaning that every request generates a unique outcome. WOMBO DREAM Example of AI-generated art made with WOMBO Dream
  • 12. Applications Stock photography (customized) Product photography Creation of images for self-made card games, tabletop games, comics,[46] book covers and album art Animations and videos (text-to-video) High definition art from low-resolution images (such as pixel art/retrogame characters or blurred images) or sketches or low-quality images (such as children's drawings) or "breathing life into a 'basic' scene" or refining details Inpainting, Outpainting
  • 13. IMPACT ON ARTISTS If a machine can do only what it was programmed to do, how can its behavior ever be called creative? Some artists in 2022 have raised concerns about the impact AI art could have on their ability to earn money, particularly if AI art is used to replace artists working in illustration and design. According to British trade union Equity, "65% of performers think the development of AI technology poses a threat to employment opportunities in the performing arts sector."
  • 14. IMPACT ON ARTISTS Digital artist R. J. Palmer has stated that "I could easily envision a scenario where using AI a single artist or art director could take the place of 5-10 entry level artists... I have seen a lot of self-published authors and such say how great it will be that they don’t have to hire an artist," adding that "doing that kind of work for small creators is how a lot of us got our start as professional artists." Polish digital artist Greg Rutkowski has stated that "it's starting to look like a threat to our careers," adding that it has gotten more difficult to search for his work online many of the images returned by search engines are generated by AI that was prompted to mimic his style.
  • 15. FUTRE OUTLOOK In the context of art creation and production, AI technologies are starting to have an ever more important role. Not only in terms of digitally and AI produced art, but also in all the aspects of curation, exhibition and sale of traditional art as well. Having in mind the rapid shift of attention towards online platforms and digital showrooms due to the current global pandemic, the ongoing circumstances contributed to the already rising interest in crypto art and blockchain technologies which have the potential to significantly impact and transform the art market.
  • 16. Current trends indicate that AI technologies will become more relevant in the analysis and production of art. We can expect that this will intensify the methodological shift from traditional towards digital research practices in the humanities, as well as result in a growing number of innovative research projects that apply large scale quantitative methods to study art-related historical questions. From the perspective of computer vision, there are still many practical challenges that need to be solved in order to assist researchers working on cultural digital archives. With the development of AI models that can generate content which very convincingly imitates human textual, visual or musical creations, many of our traditional, as well as contemporary, theoretical and practical understandings of art might become challenged CONCLUSION