Thanks for the interest! I'd be happy to. At its core, Lumineuroptic™ is a new computing architecture designed to solve the fundamental bottlenecks that limit current AI hardware like GPUs. Instead of improving the old system, I went back to first principles. The core innovation is a "Neuro-Optical Sandwich" (NOS), a 1 cm² module that does three things fundamentally differently: It computes with light, not just electrons. We use a dense array of 10 million micro-LEDs for massively parallel processing at 1.5 GHz. It eliminates the memory wall. It features an in-memory computing layer (the Lumionic Memory Array or LMA) where memory access and computation are a single, ultra-fast operation (~0.69 ns). This avoids the ~10 ns latency penalty of accessing external HBM memory. It scales with massive bandwidth. Modules are stacked in 3D and communicate via optical TSVs at >15 Tbps, creating a dense compute fabric. The result, based on theoretical analysis, is a module that is ~21x faster (in terms of effective PFLOPS) and ~260x more energy-efficient than a state-of-the-art H100 GPU. The full paper is on Zenodo, but I've created a more visual one-page summary on the project website: [Enlace a tu micrositio lumineuroptic.com] Happy to answer any more specific questions!