Tri-City AI Links

Debugging Prompts: Systematic Methods to Improve LLM Outputs

Debugging Prompts: Systematic Methods to Improve LLM Outputs

Learn systematic methods to debug and improve LLM outputs, from task decomposition and RAG to advanced mathematical steering and prompt chaining.

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Differential Privacy in LLM Training: Balancing Data Protection and Model Performance

Differential Privacy in LLM Training: Balancing Data Protection and Model Performance

Explore how Differential Privacy protects sensitive data in LLM training. Learn about DP-SGD, the epsilon-delta tradeoff, and how to balance privacy with model accuracy.

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COPPA and Generative AI: Navigating Children's Data Privacy Rules

COPPA and Generative AI: Navigating Children's Data Privacy Rules

Learn how the 2025-2026 COPPA updates change data collection for Generative AI. Discover new rules on parental consent, biometrics, and data retention to avoid FTC penalties.

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MoE Architectures: Balancing Cost and Quality in Large Language Models

MoE Architectures: Balancing Cost and Quality in Large Language Models

Explore the trade-offs of Mixture-of-Experts (MoE) in LLMs. Learn how sparse activation reduces compute costs while increasing memory demands for better AI scale.

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Building PII Detection and Redaction Pipelines for LLMs

Building PII Detection and Redaction Pipelines for LLMs

Learn how to build PII detection and redaction pipelines for LLMs using hybrid Regex/NER methods and tools like Microsoft Presidio to ensure data privacy.

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Multimodal Evolution in Generative AI: 3D, Haptics, and Sensor Fusion

Multimodal Evolution in Generative AI: 3D, Haptics, and Sensor Fusion

Discover how AI is evolving from late fusion to unified architectures. We explore the rise of 3D, haptics, and sensor fusion in 2026.

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Bias in Generative AI: How Training Data, Selection, and Algorithmic Design Shape Outcomes

Bias in Generative AI: How Training Data, Selection, and Algorithmic Design Shape Outcomes

Explore how training data selection and algorithm design drive bias in generative AI. Learn about real-world impacts, mitigation techniques like the MIT method, and practical steps to reduce discrimination.

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Red Teaming Prompts for Generative AI: Finding Safety and Security Gaps

Red Teaming Prompts for Generative AI: Finding Safety and Security Gaps

Learn how to identify and fix safety gaps in generative AI using red teaming strategies. Covers prompt injection, automation tools, and regulatory compliance.

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Risk and Controls for Generative AI: Policies, Approvals, and Monitoring Strategy

Risk and Controls for Generative AI: Policies, Approvals, and Monitoring Strategy

A comprehensive guide to managing risk and controls for generative AI in 2026. Covers NIST frameworks, ISO certifications, policy enforcement, and continuous monitoring strategies.

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Beyond CRUD: Vibe Coding Complex Distributed Systems

Beyond CRUD: Vibe Coding Complex Distributed Systems

Explore how vibe coding transforms distributed systems development in 2026. Learn about AI tools, governance strategies, and real-world risks beyond simple CRUD apps.

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Mastering Dependency Management in Vibe-Coded Apps: Upgrade Safely

Mastering Dependency Management in Vibe-Coded Apps: Upgrade Safely

Learn how to manage software dependencies in AI-generated apps safely. Avoid breakage during upgrades with practical workflows, version pinning strategies, and audit techniques.

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Supervised Fine-Tuning for Large Language Models: A Practitioner’s Playbook

Supervised Fine-Tuning for Large Language Models: A Practitioner’s Playbook

A practical guide to Supervised Fine-Tuning for LLMs. Learn data prep, tools like Hugging Face TRL, and avoid common pitfalls like catastrophic forgetting.

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