Author: Emily Fies

Jun, 30 2026

Federated Learning for Generative AI: How Privacy-Preserving Collaboration Works in 2026

Emily Fies

Explore how federated learning enables privacy-preserving collaboration for generative AI. Learn about homomorphic encryption, differential privacy, and real-world applications in 2026.

Jun, 29 2026

Evaluation Protocols for Fine-Tuned LLMs: What to Measure in 2026

Emily Fies

Learn how to properly evaluate fine-tuned LLMs in 2026. Move beyond perplexity and ROUGE to master LLM-as-a-Judge, safety metrics, and real-world validation protocols.

Jun, 28 2026

What Makes a Language Model 'Large': Beyond Parameter Counts and Into Capabilities

Emily Fies

Explore what truly makes a language model 'large' in 2026. From emergent capabilities to Virtual Logical Depth, discover why parameter counts no longer define AI performance.

Jun, 27 2026

HR Knowledgebots: How LLMs and RAG Automate Policy Q&A

Emily Fies

Discover how HR Knowledgebots use LLMs and RAG to automate policy Q&A. Learn about implementation, security, accuracy, and ROI in this comprehensive guide.

Jun, 26 2026

Vibe Coding Productivity: Why 74% of Developers Report Gains (And the Hidden Costs)

Emily Fies

Explore the truth behind vibe coding productivity claims. While 74% of developers report gains, data reveals a sharp divide between senior and junior outcomes, highlighting the critical role of context engineering and the risks of technical debt.

Jun, 25 2026

Retrieval Augmentation on Open-Source LLMs: Tooling and Best Practices

Emily Fies

A practical guide to implementing Retrieval-Augmented Generation (RAG) with open-source LLMs. Covers core architecture, essential tools like LangChain and vLLM, vector databases, and best practices for reducing hallucinations.

Jun, 24 2026

How Large Language Models Learn Meaning and Grammar via Self-Supervision

Emily Fies

Discover how Large Language Models master language rules through self-supervised learning and attention mechanisms. We explain the role of queries, keys, values, and positional encoding in capturing syntax and semantics.

Jun, 23 2026

Multi-Model Prompting: When to Switch Between Claude, GPT-4, and Gemini

Emily Fies

Learn how to strategically switch between Claude, GPT-4, and Gemini for optimal results. Discover which AI model excels at coding, long documents, and speed to save costs and boost performance.

Jun, 22 2026

Hybrid Recurrent-Transformer Models: Do They Actually Help LLMs?

Emily Fies

Explore how hybrid recurrent-transformer models combine Mamba and attention to solve LLM scaling issues. Learn about sequential vs. parallel designs, real-world examples like Hunyuan-TurboS, and performance trade-offs.

Jun, 21 2026

How Usage Patterns Affect Large Language Model Billing in Production

Emily Fies

Explore how volatile AI usage patterns disrupt traditional SaaS billing. Learn about token metrics, hybrid pricing models, and real-time metering strategies to control LLM costs in production.

Jun, 20 2026

Latency vs Throughput in LLM Deployments: A Practical Guide for Production

Emily Fies

Master the latency vs throughput tradeoff in LLM deployments. Learn how batching, vLLM, and GPU selection impact performance and costs in production environments.

Jun, 19 2026

Preventing Catastrophic Forgetting During LLM Fine-Tuning: Techniques That Work

Emily Fies

Learn why LoRA fails to stop catastrophic forgetting and discover proven 2025-2026 techniques like FIP, EWC, and distillation to preserve LLM knowledge during fine-tuning.

Author: Emily Fies

Federated Learning for Generative AI: How Privacy-Preserving Collaboration Works in 2026

Evaluation Protocols for Fine-Tuned LLMs: What to Measure in 2026

What Makes a Language Model 'Large': Beyond Parameter Counts and Into Capabilities

HR Knowledgebots: How LLMs and RAG Automate Policy Q&A

Vibe Coding Productivity: Why 74% of Developers Report Gains (And the Hidden Costs)

Retrieval Augmentation on Open-Source LLMs: Tooling and Best Practices

How Large Language Models Learn Meaning and Grammar via Self-Supervision

Multi-Model Prompting: When to Switch Between Claude, GPT-4, and Gemini

Hybrid Recurrent-Transformer Models: Do They Actually Help LLMs?

How Usage Patterns Affect Large Language Model Billing in Production

Latency vs Throughput in LLM Deployments: A Practical Guide for Production

Preventing Catastrophic Forgetting During LLM Fine-Tuning: Techniques That Work

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Latest Courses

Chain-of-Verification (CoVe): How to Reduce LLM Hallucinations

Federated Learning for Generative AI: How Privacy-Preserving Collaboration Works in 2026

Latency vs Throughput in LLM Deployments: A Practical Guide for Production

Audio Generation in Generative AI: Speech, Music, and Sound Effects Explained

How Layer Dropping and Early Exit Speed Up LLM Inference

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