The field of information theory and cryptography is witnessing significant developments, with a focus on improving the security and efficiency of various protocols and algorithms. Researchers are exploring new approaches to enhance the robustness of cryptographic systems, such as the use of dual moduli in RSA variants and the application of quantum random numbers to strengthen the ChaCha cipher. Additionally, there is a growing interest in the development of more efficient and effective methods for source coding, channel synthesis, and dataset distillation. Notably, innovative energy-based modeling frameworks and neural network architectures are being proposed to tackle complex problems in rate-distortion theory and probabilistic shaping. Some noteworthy papers in this area include the proposal of DM-RSA, a variant of the RSA cryptosystem that employs two distinct moduli to enhance security, and the development of a joint rate-utility optimization method for dataset distillation, which achieves significant compression ratios while preserving the utility of the original dataset.