Deadline: Year of 2023
Dart Container aims to leverage emerging generative AI technologies by utilizing software platforms able to optimize existing products or create new container designs. The identified platforms will enhance the capabilities of Dart Container’s internal design team.
background:
Modern software engineers have designed platforms that utilize natural language prompts to create life-like text, using millions of documents as guides for both content and style. Similar advances in AI generated images and video create increasingly lifelike scenes. Dart Container aims to utilize the advancements in generative artificial intelligence for refining and developing designs for use in the food and beverage container industry.
Through this Sprint, Dart seeks to identify software companies with AI platforms capable of producing 3D CAD files that can be used as a blueprint for physical prototypes. CAD files may be in any applicable format, however commonly used formats such as SolidWorks, Catia, Fusion 360 and NX are strongly preferred. The proposed platform should accommodate diverse container types, sizes, and materials, ensuring flexibility in meeting Dart’s packaging needs.
Dart intends to begin direct engagement in Q1 2024 with an eye towards the generation of the first models by EOY 2024. Platforms with longer development timelines are still of interest.
In-scope generative AI platforms of all technical maturities, including those from academic sources, are welcome. Solutions which already possess a broad design database from which to generate new models are preferred however Dart is open to exploring early-stage platforms which still need to identify such source materials.
The goal of this sprint is to facilitate contact and interactions between the Sprint sponsor and commercial entities (including Start-ups), technology developers or research organization/university in this space.
requirements:
Solvers submitting an Entry are encouraged to highlight capabilities in their Submission that meet criteria including:
- Technology overview
- Output format
- Previous usage, if any
- Current size of available design database
- Development and implementation plan
- Scalability
- Customization options
- Desired engagement with Dart Container
- Commercialization timeline
- Technical maturity