一键生成的游戏世界AI破冰Web3游戏叙事“寒冰期”

币界网Published on 2024-07-31Last updated on 2024-07-31

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作者:DeMan

在Web3游戏的世界里,我们见证了一个颇具挑战的时代。从2018年至2023年,共有2817款Web3游戏问世,但可悲的是,其中2127款(占比75.5%)未能成功,这一数据凸显了行业的艰难。

虽然自2018年以来,Web3游戏始终未能真正掀起狂潮,但每当加密货币翻涌新篇章,Web3游戏常被寄予厚望,再结合当前市场的牛市预期,我们很可能会看到许多游戏达到疯狂的估值。

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仅看2024、2025两年,随着DALL-E、Stable Diffusion、Midjourney、ChatGPT 等众多 AI 模型的集中式爆发,我们认为“AI向Web3渗透”将成为其关键驱动力,基于AI 技术突破,7月,DeGame官方正式宣布上线“AI生成游戏”功能,希望通过一系列具有互操作性、可组合性、可编程性和工具,以及模块化的游戏/视频/语音生成模型,为Web3游戏产业强势复苏带来全新的尝试。

全球近30亿的Web2游戏玩家和近6亿的Web3用户,都让Web3游戏拥有具有强大的叙事基础。但目前,资金和项目更多聚集在基建层面,在大规模用户采用和转化叙事方面缺乏新的增长点。

推动游戏行业发展重点实际在于技术变革,AI技术在游戏开发中的应用正日益成熟,借助AI生成模型去解决Web3游戏面临的典型问题,从而在短期内实现破圈与增长,或许是最佳方案。

01 破冰叙事“寒冰期”

可玩性是此前限制Web3游戏难以获取大规模玩家的主要弊病。单调的玩法和粗糙的画面,经常让玩家在参与Web3游戏时闪回十几年前。但对普通玩家来说,评价一款游戏优劣的硬标准从来只有一个,就是好不好玩;过度注重“Fi”的Web3游戏只能吸引打金人群,却无法完成Web2用户的大规模转化。

但从现实层面看,作为一个极度烧钱和耗时的行业,游戏板块爆发需要资本、时间和技术等多重因素的共同推动。而当时间行进到2024年,AI似乎可以将这些要素聚集。模块化的AI生成工具的完善让Web3游戏朝3A级制作及高质量方向改进有了更强支撑。

在传统游戏中,NPC(非玩家角色)拥有非常有限的人工智能,往往只能在固定的情况下进行操作。而借助于AI技术,NPC可以更加逼真地模拟人类的行为,拥有更加智能化的操作方式。如《救救我!劳动法保护神》中的AI NPC实时对话解密,增加了游戏的互动性和沉浸感。

另外,AI还可以用于生成环境、角色形象和数值平衡等,进一步丰富游戏的多样性和可玩性,使游戏中的交互更加便捷和自然。传统的游戏交互方式往往基于键盘和鼠标,难以满足玩家的需求。而借助于AI技术,可以实现更加直观和生动的交互方式,例如语音、手势、表情等等。

总体来看,AI对于游戏领域,目前被成功实践最大的方向无疑是增强游戏体验、个性化游戏内容,AI生成模型能够在短周期内,优化游戏开发过程,以较低开发成本融合传统Web2游戏的多重亮点,以提升增量用户参与Web3游戏的丝滑度,而这则是Web2用户向Web3游戏大规模迁徙的重要一环。

02 释放无限创造力

去中心化的区块链是平衡AI(和机器学习)的重要力量,一是可以结合其他技术,比如ZK,优化机器学习的信任框架,二是可以有效地利用长尾资源,降低使用AI的成本和门槛,而另一方面,因为许多 Web3 应用为了安全性和去中心化而牺牲了用户体验,而 AI 则能够帮助优化和提升用户体验,这是AI可以赋能Web3的部分。

具体到落地的应用场景,虽然AI+DeFi,AI+DID/社交均有用例,但生成式AI天然适用在文字类、沙盒类、养成类、开放世界、UGC等Web2用户熟悉的玩法上,通过AI改写游戏逻辑,让游戏充满更多不确定性和随机性,都会使Web3游戏与AI碰撞出不一样的火花。

例如,Web3游戏的一个重要创新是它需要用户和平台一起参与创作过程,而不是规划好的有限游戏,在游戏当中,会有一个Lore的概念,在传统游戏当中,这是被游戏设计者规划好的,是完全可预测的,而通过 AI模型,可以将各种输入汇集在一起,并生成不可预测的输出,这样的游戏就拥有了无限可能性。

想象一下,在未来的某一天,我们能够通过 AR/VR 设备访问神奇的虚拟世界,我们可以通过 prompts 提示词瞬间创建出我们脑海中想象或者无法想象的 2D 以及 3D 物品,就像念了一句神奇的咒语,然后便真正拥有了它们(数据托管在公链上),我们还可以和虚拟世界智能的 AI NPC 交互,并影响整个游戏世界的故事发展,而这一切都将由完全透明的开源基础设施提供支持。

在这种愿景下,AI 驱动Web3游戏领域,将释放无限的创造力。

03 飞速演进和不断融合

实际上,AI开发游戏历史的雏形也许可以追溯到更早。

AI在游戏开发中的应用可以追溯到「星际争霸」和「暗黑破坏神」等经典游戏。在当时,开发人员需要用AI系统来制作交互式的虚拟世界和角色。而这些系统已成为此类互动平台开发的标准配置。

早期和游戏开发AI相关的研究强调控制非玩家的角色(NPC),而随着自然语言处理(NLP)技术的发展,出现了一些利用深度学习技术生成关卡的开创性工作。

其中代表作是MarioGPT,它通过微调的GPT-2模型成功生成了「超级马里奥兄弟」中的部分关卡。

随着模型的快速迭代,AI的能力越来越强悍。对于Web3游戏领域的从业者来说,如何用AI更好地打造优质游戏,如何将AI生成模型运用到研发流程当中,是抢占增量用户的核心。

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我们希望看到涌现的、程序生成的世界,每个世界都有自己丰富的历史、居民和谜团。将有互动小说,故事通过玩家的选择不断发展,并通过生成的图像、视频和音频来讲述,让Web3游戏拥有更多可能性。

写在最后

如果一个Web3游戏领域从业者想要完成游戏作品,必须至少涵盖互动性、可玩性,以及具有游戏情节内核的内容,考虑游戏中人物之间的剧情联系,同时还要为玩家精心设计游戏关卡和目标。借助前沿的AI生成模型,可以将创意和想象力转化为复杂的游戏机制和故事情节,设计出拥有生动的个性特征的AI NPC带领玩家的行动,触发影响游戏故事的走向,并且提高游戏的开发和运营效率,降低游戏的开发和运营成本,从而产生新的利润增长点。

AI技术在游戏的开发和运营过程中有众多方向的应用,包括游戏情节策划、地图生成、关卡设置、任务生成、对话生成、故事叙述、模型生成,以及游戏内的成长系统和经济系统等规则的生成。

现在只是刚刚开始,我们相信在AI和Web3游戏领域的探索将打开一扇通往新游戏世界的大门。随着技术的进步和应用的深入,玩家可以期待遇到更多独特的游戏体验,这些体验将超越传统游戏的边界,带来更加沉浸式和互动性的游戏世界。对于热爱游戏和技术创新的玩家来说,这是一个激动人心的时代。

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