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How AI Creativity Influences Human Art and Business

by Ana Lopez
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CEO at Refacea Ukrainian startup and AI product company of easy-to-use digital self-expression tools.

Until recently, we could hardly imagine that by entering an absurd text prompt, such as “Spiderman on the moon shaking hands with a surrealist Elon Musk”, we could almost immediately get realistic and highly detailed images of this scene created by AI. But this finally happened. And while I think the hype around generative AI is absolutely justified, new AI content generators are only surpassing previous competitors.

In less than a month after the launch of Stable Diffusion, DreamStudio exceeded one million users. By comparison, it took GPT-3 two years to reach its million users; Copilot skipped that about six monthsand DALL-E broke this mark in just 2.5 months.

The rapidly growing variety of AI tools for visual content generation marks a new paradigm for the industry’s development. Due to the explosive potential of generative AI, innovative companies need to keep the context of this technology clear. Answering essential questions about generative AI can help us better understand the place of artificial creativity in the creative industry and how it can be applied to other companies and their strategies.

The scope of generative AI

Machine learning tools for content creation have long been part of the tech inventory of cutting-edge companies, including top media automated journalism, trying to keep the pace of content production up. Early adopters include The Washington Post’s heliograf tool, businessroundups.org’ Bert or ReutersLynx Insights.

Recently introduced by the Google Research team, DreamBooth AI allows you to train Stable Diffusion AI with various objects. This algorithm can associate shapes and visual patterns with keywords and personalize the result. This means that in addition to the image itself, the tools can put you in a certain environment or generate a new one, stylize it and create a new work of art.

Created by a growing number of tech startups adopting the latest advances in generative AI, average social media platforms are also starting to fill their pages with highly detailed synthetic content, including 3D.

AI generators have become a meme-making tool in the multi-layered social media ecosystem. According to research by Know your meme, social media apps and messengers are increasingly sharing the same content in their feeds, and memes make up the vast majority. After a series of upgrades and a few viral tweets, the DALL-E Mini became a hype AI meme machine this summer surreal and absurd nine-part images with a text prompt.

In addition, generative AI helps create new visuals and designs based on existing software and programs for creators such as Adobe, Canva or Figma. This sparks a real innovation boom, from creating unlimited design templates to generating your own unique Dungeons and Dragons or Fortnite characters, and even filming a fantasy series from scratch in Unreal Engine.

Should we even consider generative AI as art?

Amid the rapid commoditization of generative AI, there is a growing debate over its rules and regulations, raising questions about creativity, monetization, ethics and more.

While art is classified as the product of imagination, skill, experience, and emotion, machine learning can make up for many of the components it lacks to reach the level of human art by processing and training large amounts of data.

adobe officially on the side of generative AI and Shutterstock has announced that it will sell AI-generated art. At the same time Getty Images has banned synthetic content because of the legal challenges it poses.

Artist Jason Allen won first prize at the Colorado State Fair using an image created by MidJourney generative AI. Louis Rosenberg, Ph.D. from California, suggested a humanitarian tax generated on AI artwork and trained on user data.

Both sides of this great debate – the proponents of democratizing generative AI and the opponents – have compelling arguments. However, in the postmodern era, where the boundaries of reality and its components are blurring like never before, only humans can determine whether machines can create lifelike and beautiful things.

Tips for implementing generative AI in your product

As you can see, there is a lot of potential in Generative AI and many opportunities to grow your business. We are already seeing this shift in film production, media, and even 3D editors. In addition to the obvious benefits, such as saving time and compute costs, implementing generative AI in your product can also improve other metrics if you take the following steps.

• Turn your customers into makers. By implementing generative AI in their products, companies can give users easy access to creative tools. User-generated content drives engagement, especially when people create something using AI, whether it’s a new avatar, a banner ad, or a complex visual piece of content created with your inventory of AI tools.

• Rule community rules. Businesses should establish clear community guidelines to monitor copyright and moderate community compliance. The field of regulating synthetic content is still evolving as ever-emerging AI developments push the tech industry to learn new angles on ethics, rights, and security issues. By organizing and democratizing this process, generative AI can bring more benefits to your business.

• Improve customer service. Automated solutions work even better when users provide meaningful feedback, encouraged by the product and support teams. Ask your users how your tools and products work and conduct in-depth interviews. Improving user acquisition services can make your product more relevant to user needs and more ergonomic in UX design.

AI-powered products can enhance human creativity and self-expression. But for generative AI to really disrupt the world of human art, these synthetic masterpieces need better integration. Many VCs in the market believe generative AI has the potential generating trillions of dollars of economic value. Evolving models of generative AI are forcing us to rethink maker economics and our relationship with art. By working with the artificial, I believe that human creativity can achieve an unprecedented symbiosis of technology and art.

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