I will explain the outline of Astraea-Software activities.
What are the current AI problems and why do we need 3D AI? This is an overview of how to utilize 3D AI.
Why do you need 3D AI?
We will compare the current AI issues, text-based, 2D data AI and 3D data AI, and explain why 3D AI is necessary.
At the sites of many industries such as the manufacturing industry and the construction industry, operations using 3D data are the mainstream. Computer-aided technology related to design and manufacturing called CAD, CAM, and CAE is also based on 3D shapes such as 3D CAD.
When introducing AI to these support, it is indispensable for AI to recognize the three-dimensional shape.
Comparison of 3D AI with text-based AI
Take, for example, database search, which is one of the main functions of AI.
1With text-based AI, it is necessary to search for similar shapes by handing out textual information such as part numbers. However, it is necessary for a person to prepare the text information of the clue in advance assuming the search content, which requires careful preparation and enormous effort. Also, the maintenance requires a lot of effort.
If AI can recognize the 3D shape, it can search the database for a shape similar to the search target. Therefore, all you need to do in advance is to prepare only 3D shape data such as CAD.
Comparison of 2D AI and 3D AI
Attempts have been made to make AI recognize 3D shapes for some time, but since there is no technology to recognize 3D shapes as they are, we take snapshots from about 20 different viewpoints for 3D shapes and take them. Alternative measures have been taken, such as having the 2D AI recognize the 3D shape from the 2D image group.
This is a technology that is an extension of 2D image recognition, and when the 3D shape becomes complicated, there are cases where the hole shape becomes a shadow and is not displayed on the screen, making it difficult to maintain recognition accuracy. was.
With the 3D AI technology that we have been researching and developing, the shape can be recognized directly from the nodes (vertices, coordinate positions) and elements (node connection information) that make up the 3D shape. Therefore, the shape of the hole etc. is not hidden, the dimensions can be grasped from the coordinate position, and it can be used for classification and matching of 3D shapes. Also, since it has coordinate positions, it is possible to generate new 3D shapes.
Furthermore, the 3D shape captured by the 3D scanner can be recognized as it is, and it can be classified and matched, and can be used in various scenes of the design process.
Fusion of AI / CAE / cloud
Our activity goal is to integrate CAE, AI, and cloud technologies and to infiltrate technologies from large companies to SMEs.
We will permeate the advanced technology cultivated in large companies into every corner of the industrial structure and strongly support the entire Japanese manufacturing industry.
We will create new added value by integrating 3D AI technology with CAE technology, which has already been used for decades at manufacturing design sites.
Furthermore, we provide a system with excellent operability, efficiency, and cost while reducing the burden on users with cloud technology.
Two technical advisors strongly support research on cutting-edge AI development.
For the features of our main technology, 3D AI, please refer to the features of 3D AI models.