The realization of an interoperable and scalable virtual platform, currently known as the “metaverse,” is inevitable, but many technological challenges need to be overcome first. With the metaverse still in a nascen...The realization of an interoperable and scalable virtual platform, currently known as the “metaverse,” is inevitable, but many technological challenges need to be overcome first. With the metaverse still in a nascent phase, research currently indicates that building a new 3D social environment capable of interoperable avatars and digital transactions will represent most of the initial investment in time and capital. The return on investment, however, is worth the financial risk for firms like Meta, Google, and Apple. While the current virtual space of the metaverse is worth $6.30 billion, that is expected to grow to $84.09 billion by the end of 2028. But the creation of an entire alternate virtual universe of 3D avatars, objects, and otherworldly cityscapes calls for a new development pipeline and workflow. Existing 3D modeling and digital twin processes, already well-established in industry and gaming, will be ported to support the need to architect and furnish this new digital world. The current development pipeline, however, is cumbersome, expensive and limited in output capacity. This paper proposes a new and innovative immersive development pipeline leveraging the recent advances in artificial intelligence (AI) for 3D model creation and optimization. The previous reliance on 3D modeling software to create assets and then import into a game engine can be replaced with nearly instantaneous content creation with AI. While AI art generators like DALL-E 2 and DeepAI have been used for 2D asset creation, when combined with game engine technology, such as Unreal Engine 5 and virtualized geometry systems like Nanite, a new process for creating nearly unlimited content for immersive reality is possible. New processes and workflows, such as those proposed here, will revolutionize content creation and pave the way for Web 3.0, the metaverse and a truly 3D social environment.展开更多
以智能化科研(AI for Science)为核心的第五科研范式已经在多个自然科学和高技术领域得到了广泛应用。与人工智能(AI)在自然科学领域的应用强调发现新原理、新机理和新规律不同,高技术领域更强调用AI技术来发明创造新方案、新工具和新产...以智能化科研(AI for Science)为核心的第五科研范式已经在多个自然科学和高技术领域得到了广泛应用。与人工智能(AI)在自然科学领域的应用强调发现新原理、新机理和新规律不同,高技术领域更强调用AI技术来发明创造新方案、新工具和新产品,以解决特定的领域问题。文章总结了AI在高技术领域的应用——“技术智能”(AI for Technology)的典型特征和科学问题,并以CPU芯片全自动设计为例介绍过往的成功案例。最后,文章指出技术智能的目标不仅是加速创新流程并减少人工投入,同时也希望其具备更强的创造能力,最终超过人类的水平。展开更多
文摘The realization of an interoperable and scalable virtual platform, currently known as the “metaverse,” is inevitable, but many technological challenges need to be overcome first. With the metaverse still in a nascent phase, research currently indicates that building a new 3D social environment capable of interoperable avatars and digital transactions will represent most of the initial investment in time and capital. The return on investment, however, is worth the financial risk for firms like Meta, Google, and Apple. While the current virtual space of the metaverse is worth $6.30 billion, that is expected to grow to $84.09 billion by the end of 2028. But the creation of an entire alternate virtual universe of 3D avatars, objects, and otherworldly cityscapes calls for a new development pipeline and workflow. Existing 3D modeling and digital twin processes, already well-established in industry and gaming, will be ported to support the need to architect and furnish this new digital world. The current development pipeline, however, is cumbersome, expensive and limited in output capacity. This paper proposes a new and innovative immersive development pipeline leveraging the recent advances in artificial intelligence (AI) for 3D model creation and optimization. The previous reliance on 3D modeling software to create assets and then import into a game engine can be replaced with nearly instantaneous content creation with AI. While AI art generators like DALL-E 2 and DeepAI have been used for 2D asset creation, when combined with game engine technology, such as Unreal Engine 5 and virtualized geometry systems like Nanite, a new process for creating nearly unlimited content for immersive reality is possible. New processes and workflows, such as those proposed here, will revolutionize content creation and pave the way for Web 3.0, the metaverse and a truly 3D social environment.
文摘以智能化科研(AI for Science)为核心的第五科研范式已经在多个自然科学和高技术领域得到了广泛应用。与人工智能(AI)在自然科学领域的应用强调发现新原理、新机理和新规律不同,高技术领域更强调用AI技术来发明创造新方案、新工具和新产品,以解决特定的领域问题。文章总结了AI在高技术领域的应用——“技术智能”(AI for Technology)的典型特征和科学问题,并以CPU芯片全自动设计为例介绍过往的成功案例。最后,文章指出技术智能的目标不仅是加速创新流程并减少人工投入,同时也希望其具备更强的创造能力,最终超过人类的水平。
