-
Assurance and verification offerings for AI are fragmented and target specific areas of AI lifecycle (e.g. model assurance or prompt injections) without offering a unified view of the security
-
Assurance and verification offerings for AI are fragmented and target specific areas of AI lifecycle (e.g. model assurance or prompt injections) without offering a unified view of the security
-
data management. Design and analysis of hardware and software. Coding, debugging, and troubleshooting. Testing, validation and verification. Carry out risk assessment, and ensure compliance with work
-
. Literature review of technologies and commercial market scanning. Modelling, simulation and data management. Design and analysis of hardware and software. Coding, debugging, and troubleshooting. Testing
-
. Literature review of technologies and commercial market scanning. Modelling, simulation and data management. Design and analysis of hardware and software. Coding, debugging, and troubleshooting. Testing
-
. Literature review of technologies and commercial market scanning. Modelling, simulation and data management. Design and analysis of hardware and software. Coding, debugging, and troubleshooting. Testing
-
the areas including: emerging hardware architectures (weak memory, RDMA, persistent memory, CXL); formal modelling, verification and/or logic; interactive and automated tools, such as theorem provers and
-
. Literature review of technologies and commercial market scanning. Modelling, simulation and data management. Design and analysis of hardware and software. Coding, debugging, and troubleshooting. Testing
-
. Literature review of technologies and commercial market scanning. Modelling, simulation and data management. Design and analysis of hardware and software. Coding, debugging, and troubleshooting. Testing