Artificial intelligence-generated avatars are an excellent way to showcase the capabilities of AI in creating art. The algorithms used to create these avatars are trained on a vast amount of data, which allows them to learn and develop their own style. This means that no two avatars created using AI are the same, making them truly unique and personalised.
Social media platforms have become a part of our daily lives, and we use them to communicate with friends, family, and colleagues. Avatars have become an integral part of this process, as they allow users to express themselves in a way that is more personal and meaningful. However, the traditional method of creating avatars involves users uploading a photo of themselves, which is then used as their avatar.
AI-generated avatars, on the other hand, have the potential to transform the way users express themselves on social media. These avatars are designed to be highly accurate and representative of the user's personality, preferences, and style. The algorithms used to create them take into account a wide range of factors, such as facial features, body type, clothing preferences, and favourite colours. As a result, these avatars allow users to showcase their unique identities in a way that traditional avatars cannot.
Furthermore, AI-generated avatars offer a more inclusive representation of users on social media. Traditional avatars often have limitations, especially when it comes to representing individuals from diverse cultural backgrounds. However, AI-generated avatars can capture a wider range of physical features, clothing styles, and cultural expressions, making them a great way to create a more diverse and inclusive social media environment.
Another advantage of AI-generated avatars is that they can help users maintain their privacy. Often, users are hesitant to share their personal photos on social media platforms, for fear of being judged or facing negative comments. AI-generated avatars, on the other hand, offer users a level of anonymity, allowing them to express themselves without revealing their true identities.
The use of AI-generated avatars is not just limited to personal expression. They can also be used by businesses to promote their brands on social media. For example, a business could create an AI-generated avatar that represents their brand, which can then be used to interact with customers on social media platforms. This avatar could be designed to match the brand's colour scheme, logo, and messaging, making it a powerful tool for building brand awareness and engagement. Currently, social media platforms use user data to target ads to specific users. With AI-generated avatars, it is possible to create ads that are specifically targeted to individual avatars, based on their unique preferences and personality traits. This could lead to a more personalised and engaging advertising experience for users, which could, in turn, drive higher engagement rates and conversion rates for advertisers.
However, there are also some challenges associated with the use of AI-generated avatars on social media. One major concern is the potential for these avatars to perpetuate harmful stereotypes or biases. For example, if the algorithms used to generate these avatars are not trained on a diverse dataset, they may inadvertently perpetuate biases against certain ethnic or cultural groups. Therefore, it is important to ensure that the data used to train these algorithms is diverse and inclusive.
AI-generated avatars also have the potential to revolutionise the way we interact with each other on social media. Currently, the majority of interactions on social media are based on text-based communication. However, with the advent of AI-generated avatars, it is possible to create a more immersive and interactive experience. For example, users could interact with each other using avatars that are designed to mimic facial expressions and body language, making conversations more natural and engaging.
There are, of course, some concerns about the use of AI-generated avatars on social media. For example, some experts have raised concerns about the potential for these avatars to be used for nefarious purposes, such as identity theft or fraud. However, these concerns can be addressed through the development of robust security measures that protect users' personal information.
All in all, the use of AI-generated avatars on social media is a fascinating development that has the potential to revolutionise the way we interact with each other online. These avatars are a powerful tool for personal expression, brand promotion, and immersive communication. As the technology continues to develop, we can expect to see more and more applications of AI-generated avatars on social media, which will undoubtedly enhance our online experiences.
]]>Artificial Intelligence has been one of the most rapidly advancing technologies in recent times and is expected to continue its growth in 2023. According to Market.us, the Global Artificial Intelligence Market was valued to be worth USD 129.28 billion in 2022. From 2023 to 2032, it is estimated to reach USD 2967.51 billion growing at a CAGR of 36.8%.With the rise of various AI-powered applications and services, AI has become an integral part of modern society. In this article, we'll be taking a look at some of the biggest AI trends that are expected to shape 2023.
AI-powered personalization: Personalization has been a hot topic in the AI industry for a while now, and it is only set to grow in 2023. With AI technologies such as machine learning and deep learning, businesses are now able to personalize customer experiences in a way that was not possible before. AI algorithms can analyze large amounts of customer data to determine preferences, and use that information to provide personalized recommendations, advertisements, and other experiences.
Edge AI: Edge AI refers to AI that is performed at the edge of the network, rather than in the cloud. Edge AI is becoming more popular as it reduces latency and provides faster response times for AI-powered devices and applications. With the increasing demand for AI in IoT and other real-time applications, Edge AI is expected to become a major trend in 2023.
Explainable AI: Explainable AI (XAI) refers to AI systems that are transparent and can provide a clear understanding of how they make decisions. With the increasing use of AI in critical applications such as healthcare and finance, there is a growing demand for XAI systems that can provide a clear understanding of how decisions are made. In 2023, we can expect to see a rise in XAI technologies that are designed to increase transparency and accountability in AI systems.
AI-powered automation: Automation has been a key driver of the AI industry and it is expected to continue its growth in 2023. AI technologies such as robotic process automation and natural language processing are enabling businesses to automate routine tasks, freeing up employees to focus on more valuable work. In 2023, we can expect to see an increased adoption of AI-powered automation in various industries, including finance, healthcare, and retail.
AI-powered cybersecurity: With the growing number of cyber attacks, AI-powered cybersecurity is becoming increasingly important. AI technologies such as machine learning and deep learning can analyze large amounts of data to detect and prevent cyber threats in real-time. In 2023, we can expect to see a rise in AI-powered cybersecurity solutions that are designed to provide more effective protection against cyber attacks.
AI for sustainability: AI is increasingly being used to address global sustainability challenges such as climate change, resource depletion, and environmental degradation. AI technologies such as machine learning and computer vision can be used to monitor and analyze environmental data to identify trends and make predictions. In 2023, we can expect to see an increased use of AI in sustainability initiatives aimed at reducing waste, improving energy efficiency, and mitigating environmental impacts.
In conclusion, 2023 is expected to be a year of continued growth for the AI industry. With the rise of AI-powered personalization, edge AI, explainable AI, automation, cybersecurity, and sustainability initiatives, we can expect to see AI technologies impacting our lives in new and exciting ways. The future of AI is looking bright, and we can expect to see continued advancements in the coming years.
All of this has sparked intense philosophical discussion about the future of photographers, designers, and artists, with some individuals fearing that these technologies may eventually supplant human creators. Now, to further feed the argument, someone recently took first place in a fine art competition using an AI-generated artwork, and conventional artists are upset.
Jason Allen's Théâtre D'opéra Spatial (image above) took first place in the digital art division of the fine arts competition at the Colorado State Fair. It's a grand sci-fi fantasy scene where it appears like women dressed elaborately are peering out of a large circular doorway. However, Allen's use of the AI art generator Midjourney was only revealed after the prize was given out.
The board game firm Incarnate Games' creator and primary developer, Allen, claimed that his works were computer-generated, which is why they were classified as "Digital Art." They undoubtedly now understand, but they're choosing to remain with their choice and are appreciative of the "wonderful discussion" the event this year has sparked.
The usage of an AI art generator in an art competition has sparked outrage from both artists and non-artists alike. In response to the tweet from the Colorado State Fair, one individual wrote: "That is absurd. reduces the prestige of your whole art competition to the point where it is absurd." "Wow, someone can purchase software, modify a prompt, and label the result as art. I'll make sure to do it the next year so I can act like an artist "Added someone else.
Allen defended his submission in a Discord thread and on Twitter. He also emphasises that employing an AI art generator to produce a prize-winning work of art isn't as quick and simple as many reviewers seem to believe, noting that it took him weeks to create hundreds of photographs, edit them, and choose only three to submit to the competition.
However, a sizable portion of Twitter is still unconvinced. One commenter remarked, "This stinks for the exact same reason we don't allow robots compete in the Olympics." While someone another questioned, "Jeez… Will creatives have to begin "presenting their work" like it's a math class?"
But is it dishonest?
The first competition victory of AI-generated art has undoubtedly fueled the discussion around AI art. Some people compare it to the day Deep Blue defeated Gary Kasparov in a chess match, although there are differences. Instead of making their own decisions, AI art generators take their cues from the prompt writer. Many of the people employing AI art generators to produce art are artists, while many others aren't. There will undoubtedly be discussion over whether an AI prompt writer is an artist.
One may argue that an AI art generator is a tool in the same way that a paintbrush is. So, employing an AI art generator to create art for a competition is it unethical? As the world's largest community-driven AI art marketplace, we think it is not unethical and encourage the Colorado State Fair organisers to add a category for AI art the following year.
Evidently, they are thinking about it. In order to increase your chances of winning, understand more about AI art.
To determine which tool you prefer, you might also wish to examine the top AI art generators. See our selection of art created by AI artists on out platform! Looking into buying AI paintings for your home or office? Discover thousands of original AI artworks created by hundreds of AI creators at AI Art Shop. If you want to become an AI artist yourself and start listing your AI artworks for sale for free on our platform, you can register in under 2 mins here.
]]>Machine learning was used in recent projects to recover Rembrandt and Klimt paintings. These projects raise questions about how computers can comprehend art.
Fire claimed three Gustav Klimt's most controversial paintings in 1945. The "Faculty Paintings", as they were called, were commissioned in 1894 by the University of Vienna. They were unlike any other Austrian symbolist's work. They were immediately rejected by critics who were shocked at their radical departure from the original aesthetics. Klimt quit the project after the university professors rejected them. The works were soon accepted into other collections. They were stored in a castle north Vienna during World War II for safekeeping. However, the castle was destroyed and the paintings probably went with it. Today, only a few black-and-white photos and writings are left. They are staring at me.
The paintings are not what they seem. Franz Smola, a Klimt expert and Emil Wallner (a machine learning researcher), spent six months combining their skills to restore Klimt's work. It was a tedious process that began with black-and-white photographs and then included artificial intelligence and scores more information about Klimt's art in an effort to recreate the lost paintings. These are the results that Wallner and Smola are showing me, and even they are stunned by the stunning technicolor images produced by the AI.
Let's be clear: This AI is not bringing back Klimts original works. Smola quickly points out that "it's not a process to recreate the actual colors, but it is recolorizing the photos." "The medium of photography has already been an abstraction from the actual works." Machine learning provides a glimpse into something that was thought to have disappeared for many decades.
Wallner and Smola find this charming, but not all people support AI filling these voids. Machine learning is able to recreate lost or damaged works, but this idea is controversial, just like the Faculty Paintings. Ben Fino-Radin, an art conservator, says that machine learning in conservation is his main concern. "This is because of the many ethical and moral questions that have plagued the machine learning field."
There are many questions surrounding the technology used to revive human art. No algorithm can generate authorial intent, even if it was perfect AI. This topic has been debated for centuries. Before Klimt's paintings were damaged, Walter Benjamin, an essayist, opposed mechanical reproduction.
Yet, AI has a lot of potential. Klimt's growth as an artist was influenced by the Faculty Paintings. They were a bridge between his earlier, more traditional paintings and his later, more radical works. However, the mystery surrounding what they looked like in full colour has remained. This was the problem Wallner and Smola were trying to solve. Their project was not about creating perfect reproductions, but about showing a glimpse at what was missing.
Wallner created and trained a three-part algorithm to accomplish this. The algorithm was first fed a hundred thousand images from the Google Arts and Culture library. This enabled it to understand composition, artwork, and objects. The next step was to study Klimt's artworks. Wallner says that this creates a bias towards Klimt's colors and his motifs of the period. Finally, the AI was given color clues that pointed to particular parts of the paintings. These clues were not based on color references. Smola, a Klimt expert, was amazed at the amount of detail that the writings from the time revealed. The paintings were so bizarre and egregious that critics were compelled to write detailed descriptions of them, down to the artist’s choice of colors. Simon Rein, project manager, says that it is an irony in history. The fact that the paintings were rejected and caused scandal puts us in a better place to restore them, because we have so much documentation. These data points can be fed into the algorithm to create a more accurate picture of the way these paintings looked at the time.
That accuracy is possible by combining the algorithm with Smola’s expertise. He discovered that Klimt's work from this time period has strong patterns and consistency. The Faculty Paintings were a study of Klimt's paintings before and after they were completed. This provided clues as to the common themes and colors that were prevalent in his work. Historical evidence supports even the surprising discoveries Wallner and Smola made. Critics noted Klimt's use of a rare red in Klimt's palette when he first displayed his paintings. The Three Ages of Woman was painted shortly after the Faculty Paintings. It boldly uses a red that Smola believes is the same as the one that caused a stir when it was first shown in the Faculty Paintings. A number of writings from that time raise concerns about the green sky in a Faculty Painting. Combining these writings and Smola’s knowledge about Klimt’s specific palette of greens is what created one of the most surprising images from the AI.
Klimt is not the only work that is being revived by AI. Robert Erdmann is a senior scientist at Rijksmuseum Amsterdam who uses machine learning to solve the mystery surrounding Rembrandt van Rijn’s 1642 masterpiece The Night Watch. This is part of an ongoing conservation and research program called Operation Night Watch. The current painting measures approximately 15 feet in width and 12 feet high, but it is much smaller than Rembrandt van Rijn's original. To fit into a new place, it was trimmed on four sides in 1715. The deepest cut was two feet from the left. Erdmann believed machine learning could help Rembrandt to decode the original vision of the painting. However, they were not found.
Erdmann's strongest data point was a Gerrit Lundens 17th-century copy. This painter is known for faithfully reproducing old masters and included Rembrandt parts that were missing. Erdmann used three neural networks in his design. Erdmann used the first to map out visually matching points across the two paintings. The Rembrandt was faithfully represented by the Lundens when they were viewed side-by-side and scaled to the exact same size. Erdmann switched between the digital overlays of the two paintings to see how much distortion and stretching were in the copy. This is where the second network comes in. The second network warped Lundens' image by stretching and compressing some parts, until the majority of the spatial distortion was gone.
The Rembrandt and the Lundens were thus very closely linked. These are two works that were created by artists who have their own style. Rectifying this required a third step, which Erdmann calls "sending the neural net to art school". Through backpropagation, it learned to render Lundens in Rembrandt's style. Iteration after iteration was made, moving closer to its goal until it reached its plateau. It was a perfect match. It wasn't a perfect match.
AI and machine-learning raise ethical and usage questions, just like any new technology. This includes decades-old artworks. Richard Rinehart is the director of Bucknell University's Samek Art Museum. He points out that technology has been used to determine our social contracts. AI may be unique in this aspect. He says that although techno-social contracts have been made unilaterally so far, AI might be able negotiate for itself. Technology has been at the core of conservation for centuries, in all material sciences, chemistry and color science. Rinehart says that although AI may be a significant change, the idea of applying technology to art is an accepted part of conservation, and self-criticism is a healthy part.
Fino-Radin, an art conservator, would love to see more self-criticism within the industry. But their concerns go deeper. While they are excited about the new creative possibilities this technology offers, they are concerned that it could be confused with conservation and restoration. Fino-Radin states that AI is not a restoration process. It's more like bringing back the art to life. This kind of work belongs to the field of Digital Art History.
Wallner and Smola are well aware of criticisms and will explain the Klimt project's limitations and scope. Wallner says, "We used the photos exactly as they were to ensure that we didn't depart too much from the original paintings." Erdmann explains that his reconstruction had the purpose of letting the public see Rembrandt's original composition. He emphasizes that "When I translate the Lundens copy to the style of Rembrandt the AI doesn’t have the ability put the life and genius that Rembrandt back into a painting." I'm not trying. It's not something I want to do. What you see today at the Rijksmuseum is the cropped Rembrandt painting. The extended composition printouts were temporarily displayed at the Rijksmuseum from June 2021 to October 2021. They were placed in front of Rembrandt's painting and not flush with it so that no one could mistake them for the original.
Both projects, according to Rinehart, are excellent case studies in how artificial intelligence might be used effectively in the art industry. Instead of being afraid of what the future holds for this technology, he wants increased participation from everyone—curators, conservators, museums, and the general people. "What's crucial is to invite the public to follow museums down that continuum," he argues, "so that we may learn to discern the shades of nuance and utility between 'real' and 'simulacrum.'"
Is the aura of the art or artist diminished when technology provides credible answers to age-old mysteries? If you ask the staff at Google Arts and Culture, the answer is a simple and pragmatic "no." If anything, they believe their work draws attention to the Faculty Paintings and adds to the enigma surrounding Klimt, a revolutionary painter best renowned for his less rebellious Golden Period. Erdmann's AI reconstruction allows viewers to see Rembrandt's night watchman's original and dynamic vision. This ability to see what has been lost is unquestionably a net profit.
Perhaps everything comes down to the aura. Many holes in art history can be filled using AI, but it cannot duplicate masterpieces. Nothing is possible for me. "There is no binary option between 'genuine original' and 'false synthetic' in Aura," argues Reinhart. Standing in front of a painting or gazing at it on a computer screen can both be enjoyable, but they are two quite different experiences on multiple levels. It's how we feel when we see them that matters.
]]>This study examines who is most recognized in the creation of AI art and what role humanization plays in this process.
Intelligent algorithms can be used to create art, poetry, and music. A study done by an international team of researchers at the Massachusetts Institute of Technology (MIT) and the Max Planck Institute for Human Development's Center of Humans and Machines, found that people view artificial intelligence (AI), as either the creator of art or a tool used by artists. It all depends on how the information is presented about AI art. These results were published in iScience.
Artificial intelligence makes it easy to see the obvious. It was sold by Christies Auction House for over 430,000 US Dollars in 2018. The creator of the painting has been identified through a scientific investigation.
A work of art created by Edmond de Belamie with the aid of an intelligent algorithm was sold at Christie's Auction House for 432,500 USD in October 2018. According to Christie's auction advertisement the portrait was created using artificial intelligence (AI). This was often described by the media as the first piece of art that was not created by humans but by an autonomous machine. The machine was not paid for the proceeds, but Obvious, a collective of French artists. The collective fed the algorithm pictures of paintings created by humans and taught it how to create images on its own. The group then printed a particular picture, gave it a name and promoted it. The programmers of artificial neural networks and algorithms were not mentioned. They also did not receive any proceeds from the sale.
AI art involves many people: programmers, curators, artists and curators alike. There is also a tendency, especially in the media, to give AI human-like characteristics. The reports that you have read indicate that creative AI creates original works of art by itself. Ziv Epstein (a PhD student at MIT Media Lab, and first author of this study), explained that we wanted to see if there was a link between humanization of AI, and who gets credit for AI art.
Artists deserve recognition
The researchers interviewed 600 participants to learn how AI art was created, and then asked them who should be recognized for their work. They also determined how much each participant humanizes AIs. Each person's answers were different. However, on average, AI was perceived as an art form by people who were more humane than the AI tool.
When asked who deserves the most recognition for creating AI art, the first person to be recognized was the artist who created the algorithms and trained them. The curators were then followed by the technicians who programed the algorithms. The "crowd", i.e.,. The "crowd" (i.e., the large number of Internet users who create the data material with AIs is mentioned). Respondents who humanized AI gave greater recognition to the technicians and to the crowd, but less to artists. Similar results are seen when respondents are asked who is responsible for AI artworks that violate copyright. The AIs were also more responsible for this when humans were involved.
AI is influenced by language
One key finding from the study was that people can actively control whether AIs are humanized by changing the language used for reporting on AI systems in art. It is possible to describe the creative process by explaining that AI creates and supports new art works by working alone. The process can also be explained by explaining that AI is an artist who creates the artwork, and that the AI follows simple commands from the artist. These descriptions varied in their humanization, and so participants were able to determine who was responsible for AI art recognition and accountability.
"AI is rapidly affecting our society. We will need to pay closer attention to who is responsible. Every AI is ultimately a product of humans. This is especially true when an AI malfunctions or causes damage, such as in an accident involving an auto-piloted vehicle. It is important to recognize that AI's perceptions are influenced by language. This is why it is so difficult to assign responsibility to AI," says Iyad Rahwan (director of the Center for Humans and Machine, Max Planck Institute for Human Development) and co-author of this study.
]]>After getting lots of requests to offer canvas prints as a product option for customers purchasing our AI-generated art, we started looking for a print partner to help make this possible. That’s when we found Prodigi – a global print on demand platform specialising in fine art prints and NFT printing.
Prodigi’s stunning canvas range perfectly complements our wide selection of AI art. Known for producing fine art prints for prestigious brands like the National Maritime Museum, Natural History Museum and The Royal Society, you can expect your prints to be of the very highest quality.
Fancy owning your very own original digital artwork? All of our AI artwork is 100% original and will be sold only once. Simply browse our AI art gallery and choose your favourite piece. You’ll then be able to tailor your order however you like, from minting your AI painting as an NFT to adding a museum-quality canvas print.
]]>AI is not just for artists! For example, AI can help companies find new customers by analyzing social media feeds. It can also help fashion designers predict the next big fashion trend before anyone else does. Read on to learn how AI can affect your life as a creative professional - and what this means for your career going forward!
]]>AI can help you produce more work in less time - while making sure that all of your creations are of the highest quality. This is because AI can do things like sift through raw material quickly and make calculated decisions on what materials will work best for your project. AI has the ability to analyze information much faster than humans - which means that if you want to create a piece that takes hours or days, AI could finish it in just minutes! Another way that AI can streamline your process is by helping with repetitive tasks like creating patterns. With AI, you won’t have to worry about how your work looks when it’s done because machines will decide if it’s perfect or not. You can simply set up parameters for what you want your piece to look like, and let the machine handle the rest!
The use of artificial intelligence in art production has many benefits for artists - but what does this mean for you as an artist? Well, firstly, as an artist you will eventually be able to spend more time on creative processes and less time on tedious ones. Secondly, as a result of increased production and efficiency, prices may go down and allow more people access to high-quality art at lower prices. Finally, as a result
AI is a trend that won’t be going anywhere anytime soon. In 2016, it’s predicted that AI will have a cumulative economic impact of $1.2 trillion.
Artificial intelligence is already being used by companies to predict the next big fashion trend, and to answer customer service questions without human intervention. In many ways, we are already living in an age of artificial intelligence; we just don’t know it yet!
Designers and artists should take note: AI has the potential to make your career easier and more productive than ever before. That’s because in the near future, artificial intelligence may be able to do everything from design artwork to create sonic landscapes for art installations - all without human input.
First, let’s start by taking a look at how AI impacts your creative process.
Nowadays, many artists use digital tools to create their work. This is because AI has made it easier and more efficient than ever before. AI software can monitor your progress and give you feedback on what you need to change or improve. You can also use software that will automatically adjust the colors and backgrounds of your images for stylistic purposes - making it easier for you to find the perfect balance between creativity and practicality.
AI is not just for artists! For example, AI can help companies find new customers by analyzing social media feeds. It can also help fashion designers predict the next big fashion trend before anyone else does.
Artificial intelligence has the power to revolutionize the creative process. But how will this affect you, as a creative professional? Even if you’re not ready for an entirely automated process, you can still use AI to make your work more efficient. For example, many artists use AI-based image recognition software to identify images of their work that are already on the internet. This way, they can monitor where their work is being used and attribute it accordingly.
AI is also beneficial for the editing process. You may have noticed that programs like Photoshop or Adobe Illustrator are getting more advanced by the day - apps like these will soon be able to edit themselves! When there’s less need for human input, your time can be better spent on higher-level tasks like conceptualizing new projects. And this isn’t just happening with visuals - AI also has applications in music production and even writing!
So what does all of this mean for creatives? The world of art is evolving, and it’s important that creatives are prepared for how technology will change their careers in the future.
Artificial intelligence is changing the game in the art industry. And while the future of AI is still uncertain, there are plenty of ways it will impact the way creative professionals work in the future.
If you’re concerned about how AI might affect your creative practice, the good news is that it’s not something to fear. AI will provide new opportunities for artists and creatives to make unique, engaging work. But in order to take advantage of this technology, you need to understand what it means for your creative process.
It’s time to start thinking about how AI will change the way you work—and start exploring how you might want to harness its power.
]]>This project is called Oxia Palus. It was started in 2019 by Anthony Bourached, George Cann. Their goal is to restore lost artifacts, promote responsible AI use by creative industries, arts education centres and create the jobs of the future.
They used X-Ray fluorescent images from Rusinol and The Crouching Beggar to reconstruct Picasso's artwork. They created a 3D height map to re-layer paint onto the canvas. This captured the artist's style and texture. They can use spectroscopic imaging and AI to create visible traces of an older painting in an artwork. This is important for the conservation of historical art.
These are not future events, but they do point to the possibility of AI and art converged.
Bourached argued instead of using AI for new creative ideas, they are looking backwards. AI's future is more than a tool for creation. It can also be used to preserve the environment.
AI is constantly evolving and artists create art based on machine learning and algorithms. The next step in AI art would be for computers to recognize emotions. AI will be able to recognize emotions in visual culture, which would allow experts to create computers with more emotional intelligence and thus, more human-like machines.
AI can only form opinions as well as data. It is therefore necessary to provide a lot of information to enable a machine understand emotions in art. This is what a group of researchers from Stanford University and Ecole Polytechnique did.
The team created a ArtEmis dataset, which includes machine learning models that aim to understand the relationship between emotion, language and visual content. This set contains over 80,000 images as well as over 400,000 emotional attributes.
Volunteers were asked to describe the emotion they felt about an artwork in one sentence. The algorithm then categorizes artworks into one of eight emotion categories and then explains why the emotion is important.
ArtEmis has shown great promise. In some cases, captions were created to reflect the abstract concept in the artwork. This goes beyond what is possible with a computer.
ArtEmis is a system that the team behind hopes will be used by artists to help them evaluate their work and to ensure that it has the emotional impact they desire.
An article in The Gradient by Fabien Offit argues that artists could shift their focus from AI's aesthetic exploration to its potential for critical analysis. He believes that AI art will be a catalyst for innovation through its ability to critique itself.
AI art, like other forms of innovation will be evaluated in terms of its utility in the real world. The goal is not aesthetic anymore. It will be critical to open up new opportunities or divergent ideas.
The future normalization of AI art will make machine learning a collection of tools that solves many philosophical problems.
]]>Artificial intelligence systems are gradually being introduced to our daily lives. These include social media, telephone assistants and online searches. Self-driving cars can perform many tasks automatically.
The use of algorithms to create art has increased in recent years. This opens up new opportunities for AI artists. There were claims in 2019 that we are entering a "Gold Rush" of AI art. This was primarily driven by who sold the first AI artwork at an auction for $432,000.
The painting - Portrait Of Edmond Belamy was part of a collection of portraits of the fictional Belamy families by a Paris-based collective called Obvious.
Obvious, Hugo Caselles Dupre and Pierre Fautrel were founded by researchers and artists who are interested in exploring the creative potential of Artificial Intelligence.
The collective has now joined Kamel Mennour in order to sell three NFT video portraits.
The GAN algorithm was used to create the Portrait of Edmond Belamy. It consists of two networks, a Generator as well as a Discriminator. The data set included over 10,000 portraits from the 14th through the 20th centuries. While the Generator creates new images from this set, the Discriminator detects the differences between the Generator's image and the human-made one. This was done to convince the Discriminator that the new portraits were real-life.
Christie's, which was the auction house that organized the sale, stated that new technologies will have a profound impact on the art market. AI algorithms are influencing art history and visual culture .
Sotheby's entered the AI art market for 2019 after it sold a work called Memories Of Passerby I by Mario Klingemann. The work was purchased for $51,000.
Klingemann is a pioneer in the AI art movement. He questions the inner workings and seeks to understand human perception. He trained a neural network to produce surreal images using a set of portraits dating from the 17th through the 19th centuries. This was in order to create Memories of Passerby I. The installation consisted of two screens that showed two portraits that could morph into various faces. The viewer can see the paintings as they are being created.
AI art was founded by artists such as Frieder Nake and Georg Nees. It is now being led in large part by a community of artists who work across many disciplines to explore creativity using a technological outlet.
Sougwen is an award-winning artist. Her work combines machine-made and hand-made marks to explore the dynamics between humans, systems and each other. Her relationship with the AI allowed her to ask questions about authorship and control, as well as analyze our interactions.
Memo Akte is another prominent figure in the AI art scene. His AI projects focus on creating reflections about ourselves and understanding how the world works.
One of his most well-known pieces, Deep meditations is an hour-long sound/video installation that serves as both a celebration and a spiritual journey. The viewer is invited to recognize and appreciate their experience as part of the universe through the work.
Discover unique one-of-a-kind AI art in different artistic styles such as Contemporary, Impressionism, Expressionism just to name a few with new AI paintings added to the gallery every week.
]]>Max Bense, a German philosopher, developed his Information Aesthetics theory between the late 1950s to the early 1960s. This groundbreaking concept focused on the development of scientific measures that would bring objectivity to aesthetics. He was able to link art and rationality by applying mathematics to his theory. This opened the door to a new understanding about digital art.
Bense's theory provided a new framework in which art could be objective and not externally influenced. Frieder Nake and Georg Nees were scientist-artists. Bense's Information Aesthetics influenced Michael Noll as they explored how algorithms could be used to create visual art.
Nees was the first to exhibit publicly his "computer art" at a 1965 seminar organized by Bense: The Institute of Philosophy and Theory of Knowledge.
Digital art began to rise beyond aesthetic theories at this point.
Harold Cohen was a British artist who lived in California in the 1970s. He developed the AARON program - a computer program that creates visual images automatically.
Cohen began his research by looking for ways to apply AI to fine arts. He continued to work on AARON after it was created. The program could be used to make better decisions, such as selecting colours or composition. Originally, AARON could only produce monochrome line drawings. It evolved to create digital prints of coloured shapes such as human figures and foliage.
Bense's argument that art should be developed according to rational ideas stated that rationality is our primary defense against fascism. In the early days of computer art, computer artists were focused on creating generative aesthetics. This theory is based upon removing subjectivity from artistic process and creating an aesthetic perspective that is supported by science.
In the interview below Nake also defends the idea of generative aesthetics. He comments on how computer arts are not intended to create masterpieces, but rather to produce a series of designs. These designs do not focus on artistic craft but rather rational aesthetic coherence.
Harold Cohen was a British artist who lived in California in the 1970s. He developed the AARON program - a computer program that creates visual images automatically.
Cohen began his research by looking for ways to apply AI to fine arts. He continued to work on AARON after it was created. The program could be used to make better decisions, such as selecting colours or composition. Originally, AARON could only produce monochrome line drawings. It evolved to create digital prints of coloured shapes such as human figures and foliage - the first instances of AI art.
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]]>An NFT token (nonfungible token), is a digital certificate that guarantees the authenticity and gives exclusive rights to its holder. This idea is a result of the cryptocurrency world.
Non-fungible tokens are not able to be replaced, duplicated, or substituted. This system can be used to secure rights to unique objects such as a work or art, piece of real property, or digital artifacts from computer games.
Every record in the digital blockchain is a token is a record in the digital ledger. All tokens or records in an open blockchain can be viewed as equal, fungible coins with the same monetary denomination. Cryptocurrencies are based on the concept of fungibility. This means that a bitcoin can be replaced easily by another bitcoin without affecting the overall portfolio value or position. Any bitcoin is the exact same as any other bitcoin.
The Non Fungible Token technology (NFT), however, is a game-changer and works in a completely new way. Non-fungible tokens are digital coins that can't be replaced with another token, without changing its value or essence.
NFTs, much like cryptocurrency, are created on the blockchain. The blockchain acts as a recorder for all transactions. The blockchain ensures that non-fungible tokens are authenticated. The blockchain guarantees that digital items (e.g. The person who mints the NFT actually owns the digital item (e.g. This system allows anyone to check the authenticity and historical history of any NFT via the blockchain.
The NFT token is essentially a purchase of a certificate that can be used to create a work or other physical item. The NFT item does not travel anywhere. It is permanently stored on the InterPlanetary File System, which is a peer to peer file storage network. The NFT (or certificate) is essentially a string of codes that confirms that the token's owner actually owns the object. An NFT token can be thought of as a painting that is owned by a gallery, museum or individual. However, the audience might still view it in a catalog, exhibition or catalogue. Even if someone downloads an image of this painting from NFT, they still own the rights to the original piece of art.
NFT tokens can be sold on online marketplaces similar to Amazon, except that all payments are made using cryptocurrencies and are transparently registered on blockchain. These NFT marketplaces are where NFT creators can sell their creations (e.g. OpenSea, Solsea, Rarible etc.) Wait for buyers to offer.
NFT technology was initially developed in 2017 based upon Ethereum smart contracts. However, smart contracts that are based on other cryptocurrency such as Solana have been expanded to include NFT technology.
Banksy's 2007 black-and-white drawing Morons was the first piece of art to be made into an NFT token. Injective Labs, a company that provides decentralised financial solutions, purchased the painting and burned it. They then created an NFT token, a virtual asset linked to the digital image of the original piece of art.
DJ 3LAU was first to convert his album into NFT. The album was limited edition and sold for $11.6 million.
Grimes, a well-known singer and ex-girlfriend of Elon Musk sold 400 NFT tokens in March 2021. These tokens were linked to four drawings that she and her brother had created, grossing Grimes $5.8million.
NFT, in general, is a way for creatives and entrepreneurs to monetize their talents and expand their audiences. Artists can sell their art digitally by using NFTs because they eliminate the logistical problems of shipping and receiving physical paintings.
We will discuss AI Art NFTs on our platform in our next post. This is a new trend worth your attention.
]]>You may have read on the news that Christie’s became the first company to put AI-generated art on auction. Created through the use of a generative adversarial network (GAN) trained to form new images trained on a dataset of 15,000 portraits painted between the fourteenth and twentieth centuries, the piece sold for $432,500 - over forty times its $10,000 estimate - prompting widespread speculation regarding whether or not AI might be behind the next successful art movement.
Although there’s a 30-year history of artists using algorithms and computation in their practices, this spike in modern AI art, pioneered by artist/software engineers like Robbie Barrat and Google’s Mike Tyka, has occurred within the last 5 years roughly, made doable by recent breakthroughs in machine learning like GANs. The way GANs are trained is to some extent similar to a human brain with created AI paintings increasingly more and more difficult to tell apart from those created by human artists. Also important to the present development of machine learning and art is Google’s DeepDream which was created in 2014. It uses a convolutional neural network to search out and enhance patterns in pictures.
But while technically marvellous, can we conclusively say these artworks are any good? Well, as always, the answer is subjective and depends on the point of view. At this year’s AI-focused Christie’s Art + tech Summit, Jason Bailey, father of art analytics web site Artnome, argued that if what separates our generation from its predecessors is the invention of computers, then AI or machine art is essentially our generation’s most significant art invention. In theory, his statements are reasonable and sensible, however there is still a lot of input required from humans in terms of art selection. For instance, with our current algorithms our art experts diligently select only about 1-5% of the paintings into our AI art collections.
Mike Pepi, who has commented extensively on the intersections between art, culture and technology, remains critical of AI art. ‘I guess I’m simply terribly annoyed with these technical school individuals indiscriminately attempting to use GAN networks in art’ he says. ‘I think there are some artists do that and the results are simply not superb.’
Instead, Pepi points to artists like Agnieszka Kurant and Ian Cheng, whom he sees as using AI as a tool with success - they speak regarding the cultural impact of this technology while not fetishising the results. Cheng’s name is oftentimes associated with an artist who creative person has achieved widespread success through meaningful interaction of his projects with algorithmic processes. BOB (Bag of Beliefs) (2018-2019), as one example. The work comprises, in Cheng’s words, ‘an AI creature whose temperament, body and life script evolve across exhibitions.’ The work’s open-ended narrative, that Cheng has likened to PC games like ‘The Sims’ and reality TV show ‘The Real Housewives’, interestingly has an interactive part - throughout exhibitions viewers are able to observe BOB on a 12-foot-high screen and also can alter its reality by creating interacting with the artwork via an app.
Alongside Cheng, another creative person Trevor Paglen has received mainstream attention for his use of AI technology in art. In September of 2019 he created ImageNet Roulette (2019), an AI tool that labeled user-uploaded selfies in quite a freaky way (e.g. newsreader, smoker, femme fatale) went viral once the racial and gender bias of the datasets on which the algorithm had been trained were discovered. ImageNet Roulette wasn’t Paglen’s first work that looked to reveal how machines ‘see’— his 2017 film Sight Machine has a similar idea—but it absolutely was without a doubt the most successful. Furthermore, apart from providing insight into the typically unobserved process of AI image classification, ImageNet ultimately got rid of 600,000 pictures from its online data bank following accusations that came to light through the use of the tool by Paglen and Crawford’s.
One reason for the success of this piece is that it points to the present gap between the application of AI technology and its limits. ‘It is in some way a mistake to treating AI with exceptionality. We want to be realistic regarding its limits - what it can and what it simply cannot do’ says Lachlan Kermode, Forensic Architecture software package development lead.
Although the above-mentioned works are only a few examples, they suggest that some artists may be well positions to make use of AI technology, however to do that well they may need to critically analyse the cultural implications of a tool’s use. As algorithms progressively have an effect on how exactly we see the world, over time it will be key to build strong AI ethics. ‘It’s crucial that artists are able to get their hands on new technology says Kelani Nichole, a design strategist and the founder of TRANSFER - an L.A.-based experimental media gallery.
Our team at AI Art Shop agree, which is why we are always at the forefront of new AI art technologies, developing custom algorithms that enable us to create stunning exclusive AI created paintings for you. Check out our brand new NFT AI art collection 'The Source of Inspiration' here.
]]>Published within the journal Empirical Studies within the Arts by scientist Harsha Gangadharbatla, the study was galvanized by the sale of “Edmond Delaware Belamy”, an AI-generated portrait by the inventive French studio Obvious. Hailed as “the future”, the painting fetched around 10 times the common value for an average artist at auction, going for $432,500 at Christie’s in 2018.
The ballyhoo around “Edmond Delaware Belamy” wasn’t an isolated prevalence, either. A 2017 study that asked individuals to compare a variety of AI artworks against human art, individuals largely most popular the artworks created by machines.
“For me, the fascinating factor was the role of humans in creating art” Gangadharbatla tells Artnet. “I perpetually assumed there was a soul that the human pours into the work. Once a machine creates the work, how do individuals interpret it?
The study consisted of a survey asking respondents to tell apart human artworks from AI art. The human artworks were created by artists Tom Bailey and Steve Johnson – impressionistic landscapes and geometric abstractions – whereas the computer-created artworks were the work of an AI algorithm.
Of the many people that participated in the survey, most were unable to properly identify more than 1 in 5 landscape works created by AI. Over 75% guessed wrong on the remaining four. Individuals were slightly better at telling apart abstract artworks, signalling a potential association of abstraction with AI and objective art with a person's creator.
While Gangadharbatla says that AI making artworks is comparatively harmless, he adds that advertising might be a distinct story. “If computers begin coming up with persuasive messages that appear before individuals,” he asks, “What would be the result of that be?”
In more recent news from the AI art world, AI-DA declared a new exhibition of self portraits, set to travel to a show in London. Earlier this year, OpenAI additionally debuted DALL·E, a neural network which will produce freaky pictures supported by written descriptions.
In case you’re still making an attempt to work out whether or not the pictures at the top of this article were created by humans or AI, they are, in order: AI, human, human, and AI.
]]>In conclusion, with the exception of the very first AI paintings ever made, AI art may not necessarily fit Art Connoisseurs who look for works of famous artists in search of hidden value or meaning in the artist’s work. With that said, our own art experts dedicate a lot of time and effort to trying to decode what the AI wanted to convey in a painting when coming up with a name. We are prepared to provide our written interpretation upon customer request. AI art (once again with the exception of the very first AI art ever made) may also not quite suit people who treat art solely as an investment opportunity no one can predict or let alone guarantee with certainty whether AI paintings will appreciate in value. If you want to learn more about AI art valuation and how we form the price, stay tuned for our next article.
]]>As AI technology has advanced over the last couple of years the quality of AI art has improved and the price has been reduced tremendously.
Above you can see a side-by-side comparison of Obvious’s AI portrait Edmond de Belamy (on the left) and the AI portrait named Amanda created by our team at AI Art Shop (on the right). Objectively, Amanda has a much better resolution (almost 1000 dpi) which when printed onto canvas creates an amazing oil-painting effect. The lines and contours of Amanda’s face are clear and sharp thanks to our vector correction AI algorithms used along with the standard GAN Machine Learning framework. The size of the Edmond de Belamy painting is 71 cm x 71 cm priced at $432,500: an AI painting of the same size in our AI gallery would cost around $150. All in all, Amanda is a much better AI painting in terms of quality and value-for-money compared to Edmond de Belamy. You may think that our conclusion is biased which is why we encourage you to make your own evaluation and leave a comment down below. We would be very much interested to hear your thoughts. Also, if you like our AI painting Amanda, then you should definitely visit our Portraits AI Collection where you can buy amazing portraits created by our AI algorithms.
In conclusion, with the exception of the very first AI paintings ever made, AI art may not necessarily fit Art Connoisseurs who look for works of famous artists in search of hidden value or meaning in the artist’s work. With that said, our own art experts dedicate a lot of time and effort to trying to decode what the AI wanted to convey in a painting when coming up with a name. We are prepared to provide our written interpretation upon customer request. AI art (once again with the exception of the very first AI art ever made) may also not quite suit people who treat art solely as an investment opportunity no one can predict or let alone guarantee with certainty whether AI paintings will appreciate in value. If you want to learn more about AI art valuation and how we form the price, stay tuned for our next article.
AI art is purposed for dynamic people who are open to fresh unconventional ideas, who like to try new things and challenge the widely accepted art standards. Finally, AI art is best suited for art enthusiasts who are genuinely looking for a stunning and affordable piece of art that would fit nicely on their wall and with their home interior, bringing them happiness every day. In addition, every AI painting sold on aiartshop.com is 100% original and comes with a digital certificate of authenticity registered in the Blockchain. You get an amazing looking piece of art in your home knowing that nobody else in the world has the same painting.
Businesses and corporates are another group of our clients. Property developers, hotels, bars, restaurants, gyms, etc., need to create a particular look for their spaces. With the help of AI Art Shop AI algorithms, we are able to create a series of artworks with a myriad of options exactly to our customer’s specifications.
We hope you have found this overview of AI art interesting and look forward to welcoming you to our growing list of happy clients!
If you are interested in buying art for your home or work space, then look no further - we have something for everyone! Choose from a wide range of AI art categories: Contemporary AI Art, Expressionism AI, Impressionism AI, Portraits AI and Landscapes AI.
Portraits AI and City AI.For the full AI gallery experience, make sure to visit our Virtual Reality Showroom to visually appreciate how AI art looks in a 3D space.
]]>If we take the Scream by Edvard Munch which was last sold for approximately $120 million and compare it to a painting by Leonid Afremov; the Scream by Edvard Munch is literally speaking 5 thousand times more expensive that a painting by Leonid Afremov, but certain people may nevertheless find Leonid Afremov’s work more appealing. This brings me to the next point. This will come as no surprise to anyone but art is a subjective concept. Before, answering the question: “What is the value of AI Art?”, we first need to define “value” in the broader context of art. A good way to objectively conceptualise the value of art is to consider the views of several groups of people on what actually constitutes value.
Group #1: Art Enthusiasts.
These are people who are interested in art, are well cultured, occasionally visit art galleries and museums but do not really want or feel the need to invest in mega expensive works of art with famous artist names written all over them. Instead, they treat art as a means to bring new styles to their home, as something that would look great in their living room, bedroom or study. These people buy art because they like it without trying to read too much into the painting in hopes of finding some hidden meaning. So, often art lovers in these category end up buying amazing high quality art created by art companies like ours or emerging artists that have not become famous yet. This approach works quite well for price conscious customers that want to have a stunning painting on their wall that would fit their interior design and breathe new life into the room.
Group #2. Art Connoisseurs.
People that belong to this group are obsessed (in a good way) with art dedicating a lot of time to visiting museums and art galleries, learning about new art movements, biographies of different artists, history of countless artworks as well as critiquing works of art presented by emerging artists. These art experts will usually have an art-related university degree, a masters or doctorate specialising in a certain niche art movement or artistic style. For these people, art is their life. This means that at first sight a visually strange painting of a famous artist with a high price tag may reveal much more to these people than a what may seem as a more visually appealing artwork by a less famous artist to an art enthusiast. The point is, true art connoisseurs buy paintings sometimes not because of their visual appeal but because they see a story behind each stroke, each layer, each colour combination on canvas; an idea, a hidden meaning that the artist wanted to convey to the world.
Group #3. Art Investors.
Some investors in art do not care too much about the name of the artist or art as a concept altogether. Instead, they prefer to invest their money in art investment funds that host experts (potentially art connoisseurs) who then invest on the behalf of their investors in works of art that they think will appreciate in value and present good return opportunities.
Group #4. Corporations Buying Art.
This group of people are usually businesses who are looking to mass purchase art for various reasons. These could be art galleries purchasing famous art for display in art exhibitions; or corporations looking to purchase art both as an investment and a status-boosting office decoration; or finally smaller businesses simply looking to buy art to decorate the interior of their work spaces.
Therefore, depending on the budget, type of organisation and industry, businesses can invest in a lot of different art categories: from relatively inexpensive good-looking artworks from graphic design companies and emerging artists to famous works of art of international calibre.
In the second part of this blog post, coming soon, we explain where AI art fits into all of this. Stay tuned and be sure to share and comment if you liked the post. In the meantime, we invite you to check our Featured AI Art Collection.
]]>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. These machine learning algorithms are based on the technology called General Adversarial Networks or GANs for short.
This seemingly simple process is actually more complicated than one might think since it is highly dependent on the size and what’s most important – quality of the dataset as well as time spent on training the algorithm. All of these variables, in turn, depend on the power of the graphics cards used (we use a grid of industrial grade GPUs), e.g. – the more computational power, the larger the dataset and the lesser the time it takes for every model to train. In our context, “training the model”, in simple terms, means that the algorithm continuously generates images through the generator component and the other component of the model called the discriminator “decides” whether the output of the generator is close to the original dataset or not. Hopefully, you are not too much bored by the slightly technical terminology.
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.
Fascinating, isn’t it?
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 with human faces so realistic that it is almost impossible to tell the difference between a human-made portrait and an AI portrait. So, are we entering the new era where robots are going to completely replace human artists? The answer is probably no, at least in the near future. 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.
We can see that there is definitely a degree of human involvement, but the creative process is done completely by Artificial Intelligence. As of the time of writing of this article, we offer custom made one-off exclusive AI canvas prints. Our AI paintings are brought to life using a state-of-the-art Giclee Print technology with an Ink Jet machine, guaranteeing 99% colour accuracy as well as outstanding colour depth and longevity. One interesting trait of AI paintings is that on some of them we are able to observe brush strokes and certain 3D elements that the AI overlaid on certain parts of the painting. Coupled with our vector correction and resolution adjustment AI technologies, this allows to create AI paintings with an oil-painting effect. For some of our paintings it is hard to even tell whether the painting is a canvas print or an oil painting when looking from a distance - all because of the ultra high resolution (1000 dpi) and 3D brush stroke effects that are the product of AI imagination.
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