ChatGPT Images 2.0 Shift From Monolithic Compute To Collaborative Systems For decades, compute scaling followed a predictable path: pack more transistors onto a single die, increase frequency, and extract higher performance from a centralized processor. That model is now structurally breaking down. The limiting factor is no longer just transistor density, but the inefficiency of mapping increasingly diverse workloads onto a uniform compute architecture. Artificial intelligence, large-scale data processing, and real-time systems clearly expose this mismatch. Matrix-heavy operations, sparse data movement, control logic, and memory access patterns all stress different parts of a system in fundamentally different ways. Forcing these onto a single processor type leads to underutilization, power inefficiency, and memory bottlenecks. As a result, performance scaling is constrained not only by compute capability but also […]