|
|
|
Safety_Critical_Machine_Learning |
|
|
The BIBLIC™ program began in 2026 with
the goal of promoting widespread, local AI capable of learning from contextual
data. More generally, the BIBLIC™ program promotes all
"intelligent" technologies or automation systems that do not
involve cloud connectivity. The initiative's goal is to raise
public awareness of the fact that AI connected to the cloud is currently
collecting and linking all of their data to profile them for commercial
purposes, but that this data could be used for other purposes tomorrow. We would also like to raise awareness
among those working in the sector to ensure that more and more companies try
to develop AI solutions that do not require connection to "Big
Brother" and that, possibly, are also able to learn contextual data on
site. We also want to encourage young people
and researchers to study and improve machine learning technologies that
enable an approach to AI that promotes citizens' freedom and not their
control by technocratic oligarchies. We are defining more detailed
technical specifications that could lead to certification and we are
involving certification bodies interested in operating in this direction with
a voluntary certification. |
|
|
BIgBrotherLess Intelligent Computing™ This symbol refers to any type of
personal, office or industrial device that demonstrates an intelligent
operational capability that is clearly superior to simple automation. This intelligent operational
capability must be achieved through internal processes of any kind, whether
on hardware or software, through connectionist models or generic
soft-computing systems that do not require cloud services and computing
power. More strictly, these devices must not have the ability to connect to
the cloud for any secondary purpose. |
|
|
BIgBrotherLess Intelligent
Computing with Adaptive Learning™ This symbol refers
to any type of personal, office or industrial device that demonstrates an
intelligent operational capability that is clearly superior to simple
automation. This intelligent
operational capability must be achieved through internal processes of any
kind, whether on hardware or software, through connectionist models or
generic soft-computing systems that do not require cloud services and
computing power. Furthermore, these
devices must demonstrate autonomous and adaptive learning capabilities
achieved through software algorithms or specialized hardware. More strictly,
these devices must not have the ability to connect to the cloud for any
secondary purpose. |
|
If you represent a
certification body interested in undertaking a voluntary certification process
for AI on the edge, please contact us. We are evaluating the possibility of
collaborating with several certification bodies. |
|
|
|
|
General Synaptics Aerospace_and_Defence_Machine_Learning_Company VAT NUMBER:_IT02670700992 REA NUMBER: GE-503104 Email:_luca.marchese@synaptics.org |
|
|
|
Copyright© 2026 General Synaptics |
