Scaling AI workloads across multiple GPUs often hits a brick wall due to distributed training data transfer bottlenecks. Learn how to use NVIDIA Nsight, PowerSGD gradient compression, and PyTorch DDP optimizations to eliminate idle GPU time and maximize training throughput on both PCIe and NVLink hardware topologies.
Building a Neural Machine Translation system for low-resource languages like Dongxiang requires more than just raw data. Senior developer Ahmad Wael explains how to fine-tune Meta’s NLLB-200 model, handle language ID registration, and optimize training using the Adafactor optimizer for memory-efficient performance on a single GPU setup.
WordPress 7.0 is approaching, and the AI team is racing to meet the February 19 Beta 1 deadline. This week’s update covers the 0.2.0 release of AI Experiments, the progress of the Abilities API for core post management, and the release of the PHP AI Client v0.4.0. Learn what’s landing in core.
WordPress AI Client development is hitting its stride as contributors prepare for WordPress 7.0. The latest updates reveal a shift toward the Model Context Protocol (MCP), the removal of problematic streaming support for better hosting compatibility, and a new ‘kill switch’ filter for developers. Learn why these pragmatic architectural choices matter for your production sites.
WordPress AI Experiments 0.2.0 is here, and it’s a major step forward for the Abilities system. Senior dev Ahmad Wael breaks down the new AI-powered excerpt generation, the Abilities Explorer for debugging, and how to register custom AI actions using the matured framework. Stop chasing hype and start building structured AI features.
Standard machine learning is great at finding patterns, but it often fails when you need to make actual business decisions. In this post, I break down why Causal ML is the necessary refactor for any data-driven system, covering Potential Outcomes, DAGs, and de-biasing techniques to help you stop confusing correlation with causation.
Understanding Cursor Codebase Indexing is the key to mastering AI-assisted development. Learn how the RAG pipeline uses AST parsing, Merkle trees for efficient syncing, and vector databases like Turbopuffer to give coding agents deep codebase context while maintaining privacy through client-side path obfuscation. Skip the ‘magic’ and learn the real architecture.
Stop over-engineering your AI projects. For most internal tools and MVPs, a dedicated RAG Vector Database like Pinecone is overkill. Learn how to build production-ready retrieval systems using only NumPy and SciKit-Learn for millisecond search speeds without the extra cost or complexity of specialized databases.
WP-Bench is the first official AI benchmark for WordPress development. It moves beyond general coding tasks to measure how LLMs handle WordPress-specific APIs, security, and coding standards. Using a real WordPress runtime as a grader, WP-Bench provides a transparent, execution-based evaluation of model performance. Learn how to run and contribute to it.
Breaking into a Data Science Career in 2026 requires more than just knowing Python. Senior developer Ahmad Wael critiques the common “scattergun” application strategy, highlighting why fundamental math, resume optimization with metrics, and leveraging referrals are the only ways to bypass the 400+ rejection cycle that frustrates most new applicants in today’s market.