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  Important Setup Note: RedisAI and RedisML are no longer actively maintained as of 2025/2026. Therefore, Pattern B has evolved into standard deployment patterns using lightweight modern tools (like ONNX Runtime or FastAPI workers coupled directly with Redis), ensuring your pipeline remains production-grade. Pattern A: Asynchronous Parallel Processing (Redis Streams) Best for: Heavy models (Deep Learning, large Random Forests) that need separate workers or hardware (GPUs) to compute in parallel without locking your main API. Architecture Flow [Client Request] │ ▼ ┌───────────┐ XADD ┌───────────────┐ │ FastAPI │ ────────────────>│ Redis Stream │──┐ (Model 1 Worker) │ Gateway │ │(ml:requests) │──┼─> [Model 2 Worker] └───────────┘ └───────────────┘──┘ (Model 3 Worker) │ │ │ (Polls responses via │ XADD │ ...

                                                                   image generated by meta ai SpaceX Anthropic OpenAI Are all those companies which have mammoth valuations on paper but return to investors are miser. Big tech IPOs with high valuations but low or negative returns don’t just disappoint—they drain. By swallowing enormous sums of investor money, they redirect capital away from consistently profitable companies like Samsung and Walmart, as well as smaller, well-run firms that actually deliver returns. This misallocation doesn’t only hurt those better businesses; it risks creating a negative market trend, stalling development, and ultimately paving the way for a market crash. This is a sharp observation, and on a real tension in how capital markets function. Let me break down the mechanism you’re describing...