Author: CryptoExplorer, Gate Research

What is AIGC?

AIGC (AI Generated Content) utilizes artificial intelligence to produce content tailored to your needs. The "GC" stands for generated content. Among related concepts, PGC (professionally generated content) and UGC (user-generated content) are more familiar. As its name suggests, AIGC employs AI to create content.

ChatGPT, currently in the spotlight, is a relatively successful product in the AIGC domain. Since its launch, it has taken the world by storm, surpassing 100 million monthly active users in just one month. These figures outperform popular platforms like TikTok and Facebook. The historical data is even more intriguing.

Beyond the question-answering field represented by ChatGPT, AIGC has also introduced numerous outstanding products in other areas. Among these, AI art generation is more mature. AI can create the desired image based on your instructions.

Currently, AIGC has become the hottest new trend, with major players outlining their strategies. If the Metaverse was labeled a "bubble" 21 years ago, the rise of AIGC will propel the Metaverse's development and aid its realization.

In the entire digital ecosystem, if the Metaverse becomes the representative of Web3.0, then virtual application scenarios are the Metaverse's most crucial output content. Celebrities, including Musk and Zuckerberg, have also participated, critiquing tech giants for creating new virtual applications.

Thus, when AIGC integrates with the Metaverse, it will inevitably become a vital part of content production output. Of course, AIGC has a wide range of functions, is diverse, and won't be limited to a specific industry. The first thing that comes to mind is that it will initially tackle various challenges.

AIGC Development History

Starting in 2014, the proposal of "Generative Adversarial Networks" (GAN) that year became a popular deep learning model among major producers. In retrospect, this can be considered the earliest practical foundation of AIGC.

GAN's core principle adopts the idea of competition between models. The generative model G continuously generates and outputs, which is input into the discriminative model D along with the training set for evaluation, and then optimizes learning.

The generative model G and discriminative model D compete with each other and learn together to achieve optimal results (the output of the discriminative model after being fed the output generated by the generative model and the training set is 0.5, meaning it's impossible to determine whether the input is real data).

The figure above illustrates the process of training the generative model with given input X from initially following a uniform distribution to conforming to a normal distribution.

In 2020, Art Blocks, a leader in generative art NFTs, was successfully launched. This marked AIGC's first step in the blockchain domain.

Art Blocks, a randomly generated art platform founded by Erick Snowfro, is a platform focused on programmable generative content. The generated content is immutable on the Ethereum blockchain.

Its random process is governed by numbers. These numbers are first stored in the NFT on the Ethereum network. This number string controls a series of attributes of the artwork you acquire and ultimately generates a unique NFT according to your ideas.

Creators need to pre-configure and deploy their own generated art scripts in Art Blocks, ensure their output and input are correct, and then store the scripts on the ETH network using tools.

For collectors, when they mint a certain series of works, they essentially obtain a random hash value, and then the script is executed to create an NFT corresponding to that hash value.

Shortly before publication, Gate announced on Twitter the official launch of its first AI product - Gicasso. Users can use artificial intelligence technology to create new NFTs based on their personal works after adding corresponding descriptions. This is also the first time an "image-to-image" application has been launched in the blockchain field.

Until 2021, AIGC mainly generated text (ghost articles), but the content format that the new generation model can handle includes text, sound, image, video, action, etc. It can fully unleash its technical advantages in terms of creativity, expression, iteration, communication, and personalization.

The development speed of AIGC in 2022 is astounding. At the beginning of the year, it was still in a raw technical stage, but within a few months, it reached a professional level, and the product results are sufficiently convincing.

Future Prospects of AIGC

It took ten years for AIGC to evolve from concept to product maturity.

The maturity of AIGC also makes the implementation of the Metaverse no longer just empty talk. It can not only truly help the future development of the Metaverse but also significantly save labor costs. With AI, it can break free from the shackles of the production process and have unlimited application possibilities and imagination, allowing the Metaverse to develop rapidly and produce high-quality content with high efficiency.

We should believe that, based on the current development situation, a virtual chip might be suddenly launched one day in the future, allowing users to infinitely explore the virtual world. At that time, we may be like today, with curiosity and new experiences, truly entering the Web3.0 era and opening a new era of the Metaverse.