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A practical guide to the main C++ libraries for neural-network inference and deployment. It shows where ONNX Runtime, LibTorch, OpenVINO, TensorFlow Lite, and llama.cpp fit in production systems.
A technical comparison of where C++ and Rust fit in decentralized exchange stacks. It maps smart-contract work, simulators, routing, and low-latency off-chain infrastructure.
A practical look at why C++ still matters in high-frequency trading. It connects market data, order books, replay, profiling, and deterministic latency engineering.
A practical guide to profiling C++ applications without guessing. It covers workloads, tools, flame graphs, memory behavior, and how to turn measurements into dependable performance wins.
A practical guide to stopping sensitive data from leaking through AI systems. It covers prompts, RAG, memory, tool permissions, and runtime controls that keep boundaries clear.
A practical owner-level note on GPUThor, shared GPU tenancy, hardware isolation, monitoring, AI infrastructure, and customer proof.
