Practical articles, in-depth tutorials, and architectural insights on software engineering, AI, and systems.
Explore how to run AI models combining text, vision, and audio directly on resource-constrained local hardware using dedicated NPU accelerators and computational efficiency techniques.
Learn how to adapt large language models directly on limited hardware using quantization-aware training, dramatically reducing memory consumption without sacrificing accuracy.
Learn how to build efficient local pipelines for image generation using diffusion models on dedicated hardware, balancing speed and energy consumption in edge servers.
Learn how to design artificial intelligence systems with multiple cooperative agents, managing shared context, dynamic routing, and tool execution.
Explore how sparse attention optimizes memory and processing in large language models, enabling efficient handling of long contexts.
Learn how combining structured prompt engineering and context caching accelerates AI code generation while significantly cutting operational costs.
Learn how to run artificial intelligence models combining vision and text locally on low-power devices using dedicated hardware accelerators.
Learn how to efficiently adapt large language models specialized in source code using LoRA adapters and QLoRA quantization to optimize GPU memory and costs.
Learn how to combine artificial intelligence with local logical chains to prevent fabrications and guarantee structured, reliable answers in critical environments.
Learn how to design embedded Artificial Intelligence systems capable of listening to machinery operation and identifying mechanical failures before they occur, using energy-efficient microcontrollers.
Page 35 of 62 • 614 articles