Objectives
To improve the explainability and traceability of DL components
To provide clear safety patterns for the incremental adoption of DL software in Critical Autonomous AI-based Systems (CAIS)
To integrate the SAFEXPLAIN libraries with an industrial system-testing toolset
To create architectures of DL components with quantifiable and controllable confidence, and that have the ability to identify when predictions should not be released based on applicability’s scope or security concerns
To design, implement, or update selected representative DL software libraries according to safety patterns and safety lifecycle considerations, meeting specific performance requirements on relevant platforms
Deep Learning (DL) techniques are key for most future advanced
software functions in Critical Autonomous AI-based Systems (CAIS) in
cars, trains and satellites. Hence, those CAIS industries depend on their
ability to design, implement, qualify, and certify DL-based software
products under bounded effort/cost
Case studies
Railway: Based on Automatic Train Operation (ATO), this case study seeks to check the viability of a safety architectural pattern composed of: DL artificial vision software elements that serve as “sensors” to provide information to safety-related software elements
Space: This case study envisions the use of state-of-the-art mission autonomy and artificial intelligence technologies to enable fully autonomous operations during space missions
Automotive: This case study will consider Apollo deployed on a variety of prototype vehicles. It supports state-of the-art hardware such as latest LIDARs and cameras as well as GPU acceleration
Safexplain starts its activities
The first face-to-face meeting of the project takes place on 26-27 October 2022 at the Barcelona Supercomputing Center (BSC) in order to discuss the first research project activities and next steps. The meeting is hosted by BSC at its premises.
Paving the way towards the next generation of R&I excellence in AI, Data and Robotics
Safexplain coordinator, Jaume Abella from BSC, participated at the "Paving the way towards the next generation of R&I excellence in AI, Data and Robotics" event that took place online on the 17th October online. Artificial intelligence, data and robotics are at...
Tweets
We're Basqu-ing in her success (sorry...!) Go @IruneAgirre! https://twitter.com/SafexplainAI/status/1623993559077486593
#Womeninscience inspire the next generation of scientists!
Meet @IruneAgirre . She's helping to ensure critical autonomous #ai -based systems are safe. Read about her work
🔗http://ow.ly/iNIy50MP37p
#11F @IKERLANofficial