{"id":725,"date":"2023-06-28T14:49:15","date_gmt":"2023-06-28T12:49:15","guid":{"rendered":"https:\/\/talkingtochatbots.com\/?p=725"},"modified":"2024-03-11T01:11:22","modified_gmt":"2024-03-10T23:11:22","slug":"aiart","status":"publish","type":"post","link":"https:\/\/talkingtochatbots.com\/es\/aiart\/","title":{"rendered":"Charlas con chatbots: \u00bfa la IA le gusta el arte?"},"content":{"rendered":"\n

Original LinkedIn article<\/a>.<\/p>\n\n\n\n

Continuing a series of LinkedIn articles about my experience with generative AI. First in the series was Talking to chatbots: Play-to-Learn<\/a><\/strong>.<\/p>\n\n\n\n

What is art?<\/strong><\/h2>\n\n\n\n

That’s a daring way to start an article, right? I don’t know how to define art without investing a significant amount of time in it, getting help from academic writing, or from several articles that I may find online after doing some comprehensive research… or from an AI chatbot, the virtual friend that has the incredible potential to boost people’s productivity and creativity. So I just asked:<\/p>\n\n\n\n

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\ud83d\ude0e  What is art? Provide a few short definitions.<\/p>\n\n\n\n

\ud83e\udd16 Art is not easy to define, as different people may have different views and interpretations of what constitutes art. However, here are a few short definitions from various sources:<\/p>\n\n\n\n

\u2022 Art is the expression or application of human creative skill and imagination<\/strong>, typically in a visual form such as painting or sculpture, producing works to be appreciated primarily for their beauty or emotional power.<\/p>\n\n\n\n

\u2022 Art is a visual object or experience consciously created through an expression of skill or imagination.<\/p>\n\n\n\n

\u2022 Art is a diverse range of human activity, and resulting product, that involves creative or imaginative talent expressive of technical proficiency, beauty, emotional power, or conceptual ideas<\/strong>.<\/p>\nBing Chat<\/a><\/cite><\/blockquote>\n\n\n\n

This simple prompt and answer might not impress most people, but the AI chatbot has proven to have the skill that can help write valuable text quickly. Large Language Models<\/strong> (LLM\u2019s) are the key technology behind this. LLM\u2019s are neural networks with billions of parameters that are trained on huge amounts of text data. They can learn the complexity and patterns of language and generate text for various tasks, including one as difficult as defining art in words. <\/p>\n\n\n\n

LLMs are probably the most familiar generative AI algorithms because they have been around for a while and have been incorporated to some degree in popular virtual assistants (Siri, Alexa, Google Assistant\u2026), chatbots (ChatGPT, Bing Chat\u2026) and search engines (Google, Bing Search\u2026). But LLMs are not the only technology behind the huge hype and excitement about generative AI. They are actually just the tip of the iceberg<\/strong>. This chart from McKinsey & Company illustrates what kind of iceberg we are dealing with:<\/p>\n\n\n\n

\"Exploring<\/a>
Exploring opportunities in the generative AI value chain<\/figcaption><\/figure>\n\n\n\n

Link: McKinsey & Company: Exploring opportunities in the generative AI value chain<\/a><\/p>\n\n\n\n

This article in the Talking to Chatbots<\/a> series will examine how some of the GenAI models can enhance our productivity and creativity, particularly the ones that work with Images. Imaging models<\/strong>, along with LLMs (Text), are the ones that have the most widespread adoption nowadays among all the modalities defined in the above chart. They have also brought a new and controversial concept to media and the daily lives and jobs of many people: AI art<\/strong>.<\/p>\n\n\n\n

The focus of this series of articles is still in chatbots and LLM\u2019s, and I won\u2019t forget to talk about them and their relation to AI art. But, before going into details, I decided to get help from a text-to-image AI solution (my favourite, NightCafe Studio<\/a>) to get another perspective of what (visual) art might be. This time by transforming text into an image:<\/p>\n\n\n\n

\"\"<\/a>
Algorithm: Stable Diffusion 2.1
Text prompt 1: the purest expression of human creative skill and imagination
Text prompt 2 (this is one of the tool\u2019s presets): surrealism Salvador Dali matte background melting oil on canvas
Text prompt 3 (this is configured as a \u201cnegative prompt\u201d, very important in text-to-image): ugly, tiling, poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, blurry, bad anatomy, blurred, watermark, grainy, signature, cut off, draft<\/figcaption><\/figure>\n\n\n\n

See all the details by accessing the image<\/a> on NightCaf\u00e9 Studio. You can easily replicate my prompts or try your own. If you are new to AI imaging, the website\u2019s knowledge base<\/a> offers helpful learning content.<\/p>\n\n\n\n

I won\u2019t judge if the picture above is a piece of art or not. I won\u2019t judge if the text-to-image model output of one single image in this case helps in any way to explain what art might be. I\u2019m just sharing and encouraging everyone to play an learn with text-to-image, it\u2019s more than fun \ud83d\ude0e <\/p>\n\n\n\n

AI art: just a trend or here to stay?<\/strong><\/h2>\n\n\n\n

People are talking a lot about AI<\/strong> and Generative AI<\/strong>. You\u2019ve probably seen those hashtags a couple of times or three when browsing your social networks today \ud83d\ude09. More specifically, people are talking about AI Art\u2026<\/strong> But, unlike most other trending topics on LinkedIn and in business, people are not only talking a lot about it, but using it and producing content with it very fast, at a speed that probably has not been seen before in other routine hype cycles\u2026 Remember NFT art?<\/p>\n\n\n\n

\"Google<\/a>
Google Trends chart. AI art, NFT Art. January 2021 to present.<\/figcaption><\/figure>\n\n\n\n

Note: posting this chart does not intend in any way to express an opinion on NFT or text-to-image technologies. I actually believe NFTs have some interesting use cases that can precisely complement well with the emergence of generative AI imaging, but there was an undeniable level of craze and mania surrounding NFTs a couple of years ago, as the Google Trends chart illustrates. Additionally, the chart helps infer that what is known as \u201cAI art\u201d is not a temporary craze and will quickly go beyond the current niche scenarios.<\/p>\n\n\n\n

Text-to-image generation is clearly not the most popular type of generative AI on LinkedIn or other professional networks, compared to chatbots, automation, data analytics, or other direct applications of LLMs. But if we look at the rest of the Internet, AI imaging (whether it is called \u201cart\u201d or something else) could well be the not-so-obvious big new thing<\/strong> within the bigger picture \u201cnext big thing\u201d many people see in generative AI.\u00a0<\/p>\n\n\n\n

This is a well-known pattern<\/strong>. Technology revolutions are sometimes hidden from the general public, developing at universities and Big Tech company labs and papers for years, absent from mass media and casual conversations\u2026 until one day a very specific, perhaps unexpected, application of the technology crosses the bridge from the corporate and academic world to reach consumers. This is what innovation economists, such as Austrian Joseph Schumpeter, called innovation diffusion<\/strong>. Diffusion, in innovation economics theory terms, is the process of how, why, and at what rate new ideas, practices, or products spread through a population or social system. I did not come up with this definition, I asked a chatbot again.<\/p>\n\n\n\n

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\ud83d\ude0e What is innovation diffusion?<\/p>\n\n\n\n

\ud83e\udd16 According to some sources [Wikipedia<\/a>] [Corporate Finance Institute<\/a>], innovation diffusion is the process of how, why, and at what rate new ideas, practices, or products spread through a population or social system. The theory of innovation diffusion explains the pattern and speed of adoption of innovations by different groups of people, such as innovators, early adopters, early majority, late majority, and laggards [cleverism.com<\/a>] [Investopedia<\/a>].<\/p>\n\n\n\n

\ud83d\ude0e Which economic theory<\/strong> describes the dynamics of innovation diffusion? Who are some economists or authors<\/strong> who have developed the concept?<\/p>\n\n\n\n

\ud83e\udd16 One economic theory that describes the dynamics of innovation diffusion is the diffusion of innovations theory, popularized by Everett Rogers <\/strong>in 1962 [Investopedia<\/a>] [Corporate Finance Institute<\/a>]. This theory explains how, why, and at what rate new ideas, practices, or products spread through a population or social system. The theory identifies five categories of adopters: innovators, early adopters, early majority, late majority, and laggards. The theory also considers various factors that influence the adoption process, such as the characteristics of the innovation, the communication channels, the social system, and the time.<\/p>\n\n\n\n

Some other economists or authors who have developed the concept of innovation diffusion are Joseph Schumpeter<\/strong>, who introduced the notion of creative destruction<\/strong> and the role of entrepreneurs in innovation; Frank Bass<\/strong>, who proposed a mathematical model of diffusion based on the interactions between adopters and potential adopters; and Geoffrey Moore<\/strong>, who popularized the concept of the chasm between early adopters and early majority in his book Crossing the Chasm  .<\/p>\nBing Chat<\/cite><\/blockquote>\n\n\n\n

It\u2019s a curious coincidence that the word diffusion was used by economists more than 60 years ago and one of the major forces driving the widespread adoption of generative AI today is called Stable Diffusion<\/strong> (see McKinsey\u2019s chart).  <\/p>\n\n\n\n

Typically, the particular application triggering the diffusion of an invention or technological advance is not the gadget that appeared in a recent science fiction novel or futuristic movie (it\u2019s 2023\u2026 where is my floating hoverboard and my flying car?), but something that most of us could not even imagine before. If you are reading this, I guess you have probably seen this Bill Gates interview from 1995<\/strong>, which has been referenced many times when talking about any type of innovation that happened over the past 30 years. \u201cWhat about this Internet thing?\u201d\u00a0<\/p>\n\n\n\n

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