Driving Deeptech Innovation with Vinnova

We are proud to announce that Vinnova and the program Advanced Digitalization has granted funding for the second phase of our Deeptech Acceleration project - Hektar AI. This support from Vinnova affirms their confidence in our vision to create groundbreaking solutions in generative design, artificial intelligence and urban development.‍

‍Our project builds on the successes of Phase 1 of acceleration of deeptech, where we launched our platform, Hektar. Now, we are taking the next step by focusing on the development of synthetic datasets, which will be integrated with AI technologies in phase 3.

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Development of Synthetic Datasets for AI Integration

‍The development of synthetic data sets for the AEC industry addresses the challenges of fragmented data, siloed expertise, and non-uniform building representations, which pose significant barriers to the industry's digital revolution. Despite these challenges, the potential for innovation is vast. To overcome these obstacles, we are focusing on generating synthetic datasets across various architectural scales to create a comprehensive dataset for training future AI models.

We will develop these crucial datasets, establish a feedback loop, and continuously refine our generation algorithms for urban planning and early stage property development. By doing so we will enhance our algorithms. The datasets are also essential for building and training future AI models capable of delivering high-precision suggestions to our end-users.

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Synthetic data outside AEC

Additionally, we recognize that outside the AEC industry, there is a general trend towards the adoption of synthetic datasets for AI training.Today’s AI is primarily based on real data, but as the AI boom continues, the demand for data grows. As both and Garter and NVIDIA also points out in this article (https://blogs.nvidia.com/blog/what-is-synthetic-data) this trend highlights the growing need for high-quality synthetic data across various sectors, further validating our approach to use data artificially generated by rules, statistical models and simulations.

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Collaboration with Engineering Firms and Analytics Experts‍

To ensure optimal performance of our datasets and AI models, we will collaborate with leading engineering firms and analytics experts. Together, we will analyze the performance of our datasets to meet the highest standards andprovide valuable insights and suggestions in real-time, even before generatingdesign options.

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Final Goal: A Revolutionary AI Platform for Urban Development

‍The ultimate goal of Phase 2 is to develop a revolutionary AI platform that transforms urban development. By combining advanced AI technologies with comprehensive data analysis, we aim to create tools that help cities become more efficient, sustainable, and adaptable to future challenges.

We are grateful for Vinnova's and Avanderad Digitaliserings support and look forward to continuing our journey towards pioneering AI solutions for urban development.

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For More Information, Please Contact:

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Sofia Malmsten
Co-founder & CEO
Parametric Solutions
sofia.malmsten@parametric.se

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