US 12,265,765 B2
Method for training AI models to generate 3D CAD designs
Maor Farid, Rosh HaAyin (IL); and Mordechai Moravia, Rosh HaAyin (IL)
Assigned to SCINTIUM LTD, Ramat Gan (IL)
Filed by SCINTIUM LTD, Ramat Gan (IL)
Filed on Oct. 7, 2024, as Appl. No. 18/908,028.
Application 18/908,028 is a continuation of application No. 18/742,135, filed on Jun. 13, 2024, granted, now 12,164,847.
Application 18/742,135 is a continuation of application No. PCT/IL2024/050514, filed on May 23, 2024.
Claims priority of provisional application 63/468,716, filed on May 24, 2023.
Prior Publication US 2025/0036836 A1, Jan. 30, 2025
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 30/27 (2020.01); G06F 40/20 (2020.01)
CPC G06F 30/27 (2020.01) [G06F 40/20 (2020.01)] 11 Claims
OG exemplary drawing
 
1. A computerized method for training an artificial intelligence (AI) model to generate a 3D Computer-Aided Design (CAD), the method comprising:
obtaining input data comprising at least requirements for a new design; and
training the AI model to interpret the input data and generate a corresponding CAD design, wherein the CAD design is an assembly of at least two separate components,
wherein training the AI model further comprises training the AI model to generate a CAD design comprising at least one known component;
wherein training the AI model further comprises training the AI model to:
generate an embedding vector corresponding to an ideal component to be included in the CAD design;
access a vector database storing a plurality of vectors, wherein each vector represents a known component used in designs;
search the vector database to identify a matching vector to the embedding vector;
retrieve a known component corresponding to the matching vectors; and
generate the CAD design using the retrieved known component; and
wherein training the AI model further comprises training the AI model to identify and model engineering constraints between the different components by masking some of the components during training and teaching the AI model to predict an appropriate component to place in the masked position.