NJWC White Paper


2022 is the year of AIGC (artificial intelligence production content) explosion. From AI painting to dialogue robots close to human level, artificial intelligence is accelerating the realization of the transition from perception and understanding of the world to generation and creation of the world. The publicity of AIGC content generation methods Chain innovation will become a new productivity tool in the Web3 era.
AIGC (AI-Generated Content) represents the beginning of a new round of paradigm shift. Recently, many first-line VCs in Silicon Valley have begun to set their sights on AI start-up public chain teams, especially in the field of generative AI art. This year, two unicorns, Stability and Jasper, have both received more than US$100 million in financing, with valuations exceeding US$1 billion. The popularity of the AIGC track is not only due to technological advancement, extensive commercial applications, and growing demand, but also due to the fact that the track is still in its early stages. While large tech companies capture a lot of value, startups still have a chance to break through.
AIGC will be a productivity tool in the Web3 era. As we enter the era of Web 3.0, artificial intelligence, linked data, and semantic network construction form a new link between people and the Internet, and the demand for content consumption grows rapidly. Content generation methods such as UGC\PGC will be difficult to meet the needs of expansion. AIGC will be the new metaverse content generation solution. The generation of AIGC uses artificial intelligence to learn knowledge graphs, automatically generate them, and provide assistance to humans in the creation of content or generate content entirely by AI. It can not only help improve the efficiency of content generation, but also improve the diversity of content. With the development of NLP (Natural Language Processing, Natural Language Processing) technology and diffusion model (Diffusion Model), AI is no longer just an auxiliary tool for content creation, and it is possible to create and generate content. As a result, in the future, text generation, picture drawing, video editing, and game content generation can all be replaced by AI.
From Stable Diffusion to ChatGPT, the AIGC model has become the focus of the Silicon Valley spotlight. When the winter of Web3 and the cryptocurrency industry comes, venture capital capital rushes into the Web3 AI public chain track. Generative AI applications are driven by breakthroughs in public chain technology for large-scale pre-training models (also known as "foundation models", large models). These models differ from previous-generation AI models in that they have larger parameter sizes, perform better on a wide range of tasks such as text and image generation, and possess new capabilities such as video generation.
Last modified 2mo ago