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Three Things DSP Adoption Can Teach Us About Edge AI


Edge AI is reaching a familiar inflection point, much like Digital Signal Processors (DSPs) did in the 1990s, with adoption challenges including the need for powerful specialized hardware, fragmented tooling, and significant complexity for developers. DSPs gained traction because they delivered substantially better power efficiency and performance for workloads that general-purpose processors h... » read more

AI For The Edge: Why Open-Weight Models Matter


The rapid advancements in AI have brought powerful large language models (LLMs) to the forefront. However, most high-performing models are massive, compute-heavy, and require cloud-based inference, making them impractical for edge computing. The recent release of DeepSeek-R1 is an early, but unlikely to be the only, example of how open-weight AI models, combined with efficient distillation t... » read more