Marcio Cunha

Technical Articles

Practical articles, in-depth tutorials, and architectural insights on software engineering, AI, and systems.

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IADevOps•4 min

GPU Resource Allocation Optimization in Large-Scale Language Model Inference Clusters

Explore practical strategies to manage graphics card usage in high-scale servers, balancing response speed and infrastructure costs for large language models.

IAEngenharia•5 min

Sparse Attention Mechanisms in Language Models: Runtime Cost Reduction

Learn how implementing sparse attention in language models drastically reduces computational cost and memory consumption at runtime, enabling efficient processing of long texts.

IABackend•6 min

Building Autonomous Agent Pipelines with Epistemic Memory and Real-Time Vector Retrieval

Learn how to architect autonomous AI systems by combining structured knowledge memory and real-time vector search for consistent decision-making.

IABackend•4 min

RAG Inference Systems: Hybrid Search and Large-Scale Re-rankers

Learn how to build efficient vector search architectures using hybrid retrieval and re-rankers to scale massive volumes of textual data.

IAHardware•4 min

Language Model Inference Optimization in Heterogeneous Hardware with Int4 Quantization and Memory Pager

Learn how to structure large language model inference by combining 4-bit weight quantization and paged memory management in heterogeneous hardware environments.

IAEngenharia•4 min

Implementing Recovery Mechanisms for Autonomous Agents Powered by Language Models

Learn how to build artificial intelligence autonomous agents capable of detecting failures, correcting paths, and recovering lost data in complex workflows.

IAEngenharia•4 min

State Recovery Implementation and Dynamic Hyperparameter Tuning in LLMs

Learn how to architect conversation state recovery and dynamic hyperparameter tuning in language models to ensure resilience and high performance in demanding production environments.

IAHardware•4 min

Efficient Local Inference with Model Quantization on Heterogeneous Hardware

Learn how to run large language models locally using weight quantization and distributed processing across CPU, GPU, and NPU.

IABackend•4 min

Mitigating Hallucinations in Language Models Through Knowledge Graph Static Verifications

Learn how to combine the flexibility of language models with the logical rigidity of knowledge graphs to eliminate false answers and ensure factual runtime consistency.

IADevOps•5 min

Embedding Monitoring in Language Models: Mitigating Concept Drift in Production

Learn how to detect and correct behavioral shifts in artificial intelligence models through continuous run-time analysis of vector representations.