Archive: 2025/12

Model Compression Economics: How Quantization and Distillation Cut LLM Costs by 90%

Learn how quantization and knowledge distillation slash LLM inference costs by up to 95%, making powerful AI affordable for small teams and edge devices. Real-world results, tools, and best practices.

Energy Efficiency in Generative AI Training: Sparsity, Pruning, and Low-Rank Methods

Sparsity, pruning, and low-rank methods slash generative AI training energy by 40-80% without sacrificing accuracy. Learn how these techniques work, their real-world results, and why they're becoming mandatory for sustainable AI.

Evaluation Protocols for Compressed Large Language Models: What Works, What Doesn’t, and How to Get It Right

Compressed LLMs can look perfect on perplexity scores but fail in real use. Learn the three evaluation pillars-size, speed, substance-and the benchmarks (LLM-KICK, EleutherAI) that actually catch silent failures before deployment.

Archive: 2025/12

Model Compression Economics: How Quantization and Distillation Cut LLM Costs by 90%

Energy Efficiency in Generative AI Training: Sparsity, Pruning, and Low-Rank Methods

Evaluation Protocols for Compressed Large Language Models: What Works, What Doesn’t, and How to Get It Right

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