At Rambus, we create cutting-edge semiconductor and IP products, providing industry-leading chips and silicon IP to make data faster and safer.
As artificial intelligence workloads evolve from model training to real-time inference and autonomous agentic workflows, the demands placed on system memory continue to rise rapidly.
The transition to post-quantum cryptography (PQC) has moved from research planning to operational execution. Federal policy, emerging procurement requirements, and evolving security standards are accelerating
As the automotive industry transitions to software-defined vehicles (SDVs), security architectures must evolve from discrete features into integrated, platform-level capabilities. The next generation of automotive
Read this blog to learn what PCI Express is, how PCIe 7.0 improves bandwidth and efficiency, and how features like PAM4, FEC, FLIT mode and AXI support next-generation AI, cloud, HPC and edge systems.
AI PCs running agentic workloads are expected to plan, execute, and adapt workflows in real time. These workloads depend on persistent context, concurrent processing, and
As AI workloads continue to diversify, the systems that support them are evolving just as quickly. AI is no longer confined to the hyperscale data center. It is moving to the factory floor, into vehicles, and increasingly to the edge, where power, cost, and form factor constraints can matter just as much as raw performance.
