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前Palantir公司的高管们利用来自a16z的1700万美元资金,推出了Dream项目,旨在构建用于人工智能领域的世界模型。

原文标题 · Ex-Palantir execs launch Dream with $17M from a16z to build AI world models for construction

“Dream”模型基于真实的物理原理和建筑标准进行构建。就像大型语言模型通过文本数据进行学习一样,“Dream”的世界模型也是基于来自美国各地建筑档案中的1亿多平方英尺的建筑数据进行训练的。

来源:TechCrunch AI · techcrunch.com

正文为英文,可一键机器翻译(仅首次需要等待)

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Ex-Palantir execs launch Dream with $17M from a16z to build AI world models for construction

Andy Elder and Arjun Mathur were Stanford roommates who both studied computer science before spending a decade at Palantir. Elder led product design for a team of 800 people building software for U.S. defense and intelligence agencies, while Mathur 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.

Despite having no direct background in architecture, Elder and Mathur 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.

“We’ve gone from dial-up internet to superintelligent AI, but our ability to build the physical world around us has actually decreased,” Mathur told TechCrunch.

Believing AI can boost productivity across the architecture, engineering, and construction (AEC) industry, they set out to build Dream , a startup developing built 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 The startup aims to replace cumbersome, outdated AEC tools like Autodesk’s AutoCAD and Revit.

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, Mathur 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.

“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,” Elder said.

The startup calls its approach “structural cognition” because its model generates structurally precise designs that account for internal building elements like plumbing and HVAC.

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.

While Dream isn’t the only company attempting to update AEC software with AI — other startups working on this include Motif , Snaptrude , and Arcol — Elder and Mathur claim that they are the only ones that developed a world model that instantly designs whole buildings.

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.”

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Marina Temkin is a venture capital and startups reporter at TechCrunch. Prior to joining TechCrunch, she wrote about VC for PitchBook and Venture Capital Journal. Earlier in her career, Marina was a financial analyst and earned a CFA charterholder designation.

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