Featured image of post Development Guide for Small AI Models (TinyLLaMA, etc.) Using C++

Development Guide for Small AI Models (TinyLLaMA, etc.) Using C++

A detailed development guide and internal architecture explanation for running inference on small AI models like TinyLLaMA in a local environment using C++ and ggml. Covers memory mapping, tensor operations, and SIMD optimization.

Featured image of post Quantum Annealing vs Gate Model Explained Clearly

Quantum Annealing vs Gate Model Explained Clearly

A thorough comparison and explanation of the two quantum computing architectures, Quantum Annealing and the Gate Model, from mathematical models and physical backgrounds such as the Ising model, QUBO formulation, unitary transformation, and error correction, to specific use cases.

Featured image of post [Illustrated PQC] Comparison of Major Post-Quantum Cryptography Algorithms

[Illustrated PQC] Comparison of Major Post-Quantum Cryptography Algorithms

A comprehensive guide on the threat of cryptography compromise due to the rise of quantum computers and the NIST standard Post-Quantum Cryptography (PQC) algorithms such as Kyber, Dilithium, FALCON, and SPHINCS+ that counter it, from the mathematical foundation of lattice-based cryptography (LWE problem) to detailed mechanisms and performance comparisons.

Featured image of post How to Integrate Speech Recognition AI (Whisper) into a C++ Project

How to Integrate Speech Recognition AI (Whisper) into a C++ Project

A complete guide to integrating high-accuracy speech recognition AI into edge devices and native applications using C++ and whisper.cpp. Covers everything from the basics of audio signal processing to optimizing real-time inference.

Featured image of post Techniques for Resolving GPU Memory Shortages in AI Development (CPU Offloading, etc.)

Techniques for Resolving GPU Memory Shortages in AI Development (CPU Offloading, etc.)

VRAM (GPU memory) shortage is the biggest barrier in LLM training and inference. This article thoroughly explains resolution techniques such as CPU offloading, KV cache quantization, and gradient checkpointing, using mathematical formulas and architecture diagrams.