Andy Alder 和 Arjun Mather 是斯坦福大学的室友，两人均主修计算机科学，随后在 Palantir 工作了十年。Alder 领导一个 800 人团队的产品设计，为美国国防和情报机构构建软件；Mather 则担任公司商业业务的高级副总裁。早前去年，这对好友决定共同创业，毫无悬念地选择了携手合作。
Andy Alder and Arjun Mather were Stanford roommates who both studied computer science before spending a decade at Palantir. Alder led product design for a team of 800 people building software for U.S. defense and intelligence agencies, while Mather served as a senior vice president in the company’s commercial practice. When the friends decided to build a startup early last year, there was no question they would do it together.
尽管二人并无建筑行业的直接从业背景，但他们对一个日益严重的问题深感忧虑：与几十年前相比，美国如今建造的建筑更少了，因为开发成本飙升。
Despite having no direct background in architecture, Alder and Mather were troubled by a growing problem: fewer buildings are constructed in the U.S. today than a few decades ago, as development costs have surged.
“我们已经从拨号上网进化到了超级智能 AI，但我们构建周围物理世界的能力实际上却在下降，”Mather 对 TechCrunch 表示。
“We’ve gone from dial-up internet to super intelligent AI, but our ability to build the physical world around us has actually decreased,” Mather told TechCrunch.
两人坚信 AI 能够提升建筑、工程和施工（AEC）行业的生产力，于是着手创建 Dream，这是一家开发世界模型以实现建筑设计和工程自动化的初创公司。Dream 正式退出隐身模式，获得 1700 万美元种子轮融资，由 Andreessen Horowitz 领投，SV Angel、XYZ 和 Zigg Capital 等跟投。该公司旨在取代笨重、过时的 AEC 工具，如 Autodesk 的 AutoCAD 和 Revit。
Believing AI can boost productivity across the architecture, engineering, and construction (AEC) industry, they set out to build Dream, a startup developing world models that automate building design and engineering. Dream has emerged from stealth with $17 million in seed funding led by Andreessen Horowitz, alongside other backers including SV Angel, XYZ, and Zigg Capital. The startup aims to replace cumbersome, outdated AEC tools like Autodesk’s AutoCAD and Revit.
Mather 说，如果你坐在建筑师或结构工程师身边，会发现他们仍在传统软件上“绘制”设计的每一个部件，“AI 在这一过程中实际上完全不起作用。”虽然像 ChatGPT 这样的标准大语言模型能生成建筑图像，但结果不会具备结构合理性。相比之下，Dream 基于真实的物理学和施工标准。正如大语言模型从文本中学习一样，Dream 的世界模型基于从美国各地许可档案收集的超过 1 亿平方英尺建筑数据进行训练。
If you sit next to an architect or a structural engineer, you’ll notice that they are still “drawing” every piece of their designs part-by-part on legacy software, Mather said. “AI really plays no role in that equation.”While a standard LLM like ChatGPT can generate an image of a building, the result won’t be structurally sound. Dream, by contrast, is grounded in real physics and construction standards. Just as LLMs learn from text, Dream’s world model is trained on more than 100 million square feet of building data gathered from permit archives across the United States.
“我们的模型实际上理解墙体内部的结构。使用了什么材料，梁是由什么制成的，以及它们能承受多少重量，”Alder 说。
“Our model actually understands what’s within those walls. What materials are used, what the beams are made of, and how much weight they can support,” Alder said.
这家初创公司称其方法为“结构认知”，因为其模型能生成结构精确的设计，并考虑管道和暖通空调等内部建筑要素。
The startup calls its approach “structural cognition” because its model generates structurally precise designs that account for internal building elements like plumbing and HVAC.
据创始人介绍，Dream 已开始向 AEC（建筑、工程和施工）专业人士和开发商销售其产品，他们利用该模型构思建筑设计并估算总体成本。该平台已部署在得克萨斯州和加利福尼亚州的 10 个活跃项目中。
Dream has already begun selling its product to AEC professionals and developers, who use the model to conceptualize building designs and estimate overall costs, according to the founders. The platform is already deployed across 10 active projects in Texas and California.
虽然 Dream 并非唯一试图用 AI 更新 AEC 软件的公司——从事此项工作的其他初创公司还包括 Motif、Snaptrude 和 Arcol——但 Alder 和 Mather 声称，他们是唯一开发出能即时设计整栋建筑的世界模型的公司。
While Dream isn’t the only company attempting to update AEC software with AI – other startups working on this include Motif, Snaptrude and Arcol—Alder and Mather claim that they are the only ones that developed a world model that instantly designs whole buildings.
Andreessen Horowitz 合伙人 Kimberly Tan 表示，虽然该公司在一年多前就投资了 Dream，当时该初创公司的模型还只是一个想法，但她对他们的进展印象极深。“我没见过任何人采取这种技术路线，”她说。“他们一切都基于自己的模型。”
Kimberly Tan, a partner at Andreessen Horowitz, said that while the firm first invested in Dream over a year ago, when the startup model was just an idea, she has been extremely impressed with their progress. “I have not seen anybody take the technical approach,” she said. “They’re doing everything based on their own models.”