The CERN teams from ATLAS, CMS, EP, TH and IT develop cutting-edge AI and physics simulation algorithms and common applications across multiple experiments. Development of neural network optimization techniques will enable deployment of hardware-optimal algorithms on real-time systems. Novel approaches based on classical and quantum-inspired algorithms for Lattice-quantum-field theory (LQFT) simulations of increasing complexity are also being investigated. A local dedicated cluster of interconnected GPUs of the latest generation and access to commercial cloud platforms and resources are provided to support the research activities. The associated increase in heterogeneous low-latency/high-bandwidth parallel computing resources will also require matching software and algorithm development, and an increase in the network interconnect throughput. The improvements to the computational infrastructure, and resulting gains in algorithm performance, are intended to improve the robustness of the experimental data collection, the scope of physics simulations, and reconstruction, leading to increased experimental efficiency and predictivity of theory simulations. WP1 is composed of a range of specific interdisciplinary tasks connecting IT, theory and experiments.