Author: Calder Rivenhall
Model Parallelism and Pipeline Parallelism in Large Generative AI Training
Model and pipeline parallelism enable training of massive generative AI models by splitting them across multiple GPUs. Learn how these techniques overcome GPU memory limits and power models like GPT-3 and Claude 2.
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Few-Shot vs Fine-Tuned Generative AI: How Product Teams Should Decide
Learn how product teams should choose between few-shot learning and fine-tuning for generative AI. Real cost, performance, and time comparisons for practical decision-making.
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Governance Policies for LLM Use: Data, Safety, and Compliance in 2025
In 2025, U.S. governance policies for LLMs demand strict controls on data, safety, and compliance. Federal rules push innovation, but states like California enforce stricter safeguards. Know your obligations before you deploy.
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Multi-Head Attention in Large Language Models: How Parallel Perspectives Power Modern AI
Multi-head attention lets large language models understand language from multiple angles at once, enabling breakthroughs in context, grammar, and meaning. Learn how it works, why it dominates AI, and what's next.
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Contact Best PHP AI Scripts for questions, feedback, or collaboration. Reach Calder Rivenhall directly about PHP AI scripts, tutorials, and integration help.
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Confidential Computing for LLM Inference: How TEEs and Encryption-in-Use Protect AI Models and Data
Confidential computing uses hardware-based Trusted Execution Environments to protect LLM models and user data during inference. Learn how encryption-in-use with TEEs from NVIDIA, Azure, and Red Hat solves the AI privacy paradox for enterprises.
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Export Controls and AI Models: How Global Teams Stay Compliant in 2025
In 2025, exporting AI models is tightly regulated. Global teams must understand thresholds, deemed exports, and compliance tools to avoid fines and keep operations running smoothly.
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Error Analysis for Prompts in Generative AI: Diagnosing Failures and Fixes
Error analysis for prompts in generative AI helps diagnose why AI models give wrong answers-and how to fix them. Learn the five-step process, key metrics, and tools that cut hallucinations by up to 60%.
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