The field of cryptographic security and data availability is witnessing significant advancements, with a focus on improving the scalability and accessibility of blockchain systems. Researchers are exploring new approaches to data availability sampling, such as modularizing the coding and commitment process, which enables light nodes to obtain stronger assurances of data availability. Additionally, there is a growing interest in using hardware-generated true random numbers to enhance the security of generative artificial intelligence models. Furthermore, the development of exact security bounds for linear extractors in True Random Number Generators is providing new insights into the trade-offs between compression efficiency and cryptographic security. Overall, these innovations are pushing the boundaries of what is possible in cryptographic security and data availability. Noteworthy papers include:

• One paper introduces a new paradigm for data availability sampling that enables light nodes to obtain up to multiple orders of magnitude stronger assurances of data availability.
• Another paper presents a concrete protocol that realizes this paradigm using random linear network coding.
• A paper on securing generative artificial intelligence with parallel magnetic tunnel junction true randomness demonstrates the potential of spintronic RNGs as practical security components for next-generation GAI systems.