+++ SORDI (Synthetic Object Recognition Dataset for Industries)
accelerates artificial intelligence in production +++ AI dataset
contains more than 800,000 photorealistic images in 80 categories of
production resource +++ Synthesising training data takes the
efficiency of AI in production to a new level +++ Further
strengthening of no-code AI: Superfast generation of robust AI models. +++
Munich. The BMW Group is publishing the world’s
largest data set to streamline and significantly accelerate the
training of artificial intelligence in production. The synthesised AI dataset – known as SORDI
(Synthetic Object Recognition Dataset for Industries) – consists of
more than 800,000 photorealistic images. These are divided into 80
categories of production resources, from pallets and pallet cages to
forklifts, and include objects of particular relevance to the core
technologies of automotive engineering and logistics.
By publishing SORDI, the BMW Group together with its partners
Microsoft, NVIDIA and idealworks is making available the world’s
largest reference dataset for artificial intelligence in the field of
manufacturing. The visual data is of particularly high quality, and
the integrated digital labels enable basic image processing tasks to
be carried out, such as classification, object detection or
segmentation for relevant areas of production in general.
“The BMW Group has been using artificial intelligence since 2019. AI
has already been utilised in various quality assurance applications in
production at the plants. SORDI, the new, synthetic dataset makes AI
models much faster to train and AI considerably more cost-efficient in
production,” says Michele Melchiorre, Senior Vice President of BMW
Group Production System, Planning, Tool and Plant Engineering.
To create the synthesised AI training data non-manually, the
simulated environment for robotics, the digital twin of the production
system and the AI training environment were all fused within the
NVIDIA Omniverse. The rendering pipeline from the BMW Tech Office in
Munich allows any number of photos, including labels, to be
synthesised in sufficient photorealistic HD quality for them to be
used in the creation of highly robust AI models. SORDI can be utilised
by IT professionals to develop and tailor AI solutions for
manufacturing, and by production employees to maintain mature AI
systems for validation purposes ready for the start of production.
Freely available to software developers, the publication of the
innovative dataset represents the next targeted step in the BMW
Group’s systematic expansion of activities to democratise artificial
intelligence (https://github.com/bmw-innovationlab). The publications
of no-code AI and SORDI complement each other: on the one hand, the
BMW Labelling Tool Lite and published AI training tools explicitly
allow users to use AI intuitively, even if they lack sound IT
expertise. On the other, SORDI’s synthesis significantly accelerates
and simplifies the training of AI models for production applications.