Bonseyes Glossary

A
I Marketplace
A digital marketplace where AI artefacts are traded and exchanged.
A
I Artefact
A product offered on the Bonseyes marketplace: data, annotations, or models.
A
I Task
A task specifies a detection, location, classification, or regression capability offered by a smart device. It enables the use of the Bonseyes framework.
A
nnotations
Human knowledge solidified in the form of labels. Examples of annotations are bounding boxes around features visible in image data and labels documenting the meaning of spoken text in voice data.
B
enchmark
The result of evaluating an AI artifact in a defined environment according to a defined process and with defined measurements. The purpose of a Benchmark is the comparison between alternative AI artefacts.
B
onseyes Components
The parts of the Bonseyes technological contributions and offering: the AI marketplace, the Deep Learning toolbox, and the CPS Developer Platforms
C
apability
A combination of AI artefacts that allow performing an AI task.
C
apacity
One or more servers offering storage, memory, and computational performance.
C
ontract Components
An agreement between a customer and a vendor. The agreement refers to a license, e.g. for the use or modification of AI artifacts, and terms and conditions, e.g. regarding the handling of personal data.
D
ata
Data used for deep learning, including video, image, audio, and text data. In deep learning, data is used as training data and test data.
F
eedback
Quantitative ratings and qualitative judgments that users of AI artifacts give about an AI artifact on the marketplace. Judgments may include uses of the AI artifact, problems in the AI artifact, or requests for enhancements of the AI artifact.
L
PDNN
Low Power Deep Neural Network: specificaly suited for (embedded) low power devices
M
odel
Artificial intelligence solidified in the form of a deep learning model. A deep learning model has an architecture of layers, nodes, and weights learned with the help of a sandbox consisting of data and annotations. A model may be compiled into code for integration in applications and execution on target platforms. A compiled model trades off quality requirements like inference accuracy, time performance, and resource utilisation.
P
roduct
An offering on a marketplace. The Bonseyes product offerings concern AI artifacts, capacity to store the artifacts and run model training.
R
esource
A cloud server, an edge device (such as a gateway), a device (such as a smart phone), or a sensor.
S
andbox
A combination of data and annotations used for training a model.
U
ser
A person registered in the AI marketplace for participating in the exchange of AI artifact and utilization of the toolbox and developer platforms.
V
ersion
An AI artefact may exist in different versions. Each modification of data, annotations, or model architecture and weights will lead to a version increment. Also, the code may be offered in multiple version.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 732204 (Bonseyes). This work is supported by the Swiss State Secretariat for Education‚ Research and Innovation (SERI) under contract number 16.0159. The opinions expressed and arguments employed herein do not necessarily reflect the official views of these funding bodies.
© 2017 Bonseyes Project – Created by SCIPROM