Tag: Production ML
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Test-Time Augmentation in Production: 3x Slower, 1.2% Better
TTA promises better accuracy but costs 5x GPU budget. Real benchmarks from defect detection, medical imaging, and ImageNet show when it's worth it.
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LLM Memory Calculator: Online Estimators Miss 40% Usage
Calculate LLM memory needs accurately. Why online tools fail at KV cache estimation and how to fix it with real GPU profiling methods.
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RAG vs Fine-Tuning vs Hybrid: Cost-Performance for 3 Use Cases
Compare RAG vs Fine-Tuning vs Hybrid approaches for Q&A, summarization, and code generation. See which method wins on cost and performance.
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RAG vs Fine-Tuning: When Each Wins in Production LLMs
Compare RAG vs Fine-Tuning for production LLMs. Learn when retrieval beats training, cost-performance tradeoffs, and real-world deployment patterns.
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BERT Fine-tuning Fails in Production: 5 Hidden Pitfalls
BERT fine-tuning fails? Discover 5 critical production pitfalls causing silent degradation, from tokenizer mismatches to catastrophic forgetting.
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SimCLR vs CLIP: Why Contrastive Learning Failed in Prod
SimCLR hit 89% accuracy but burned $50K in GPU costs. CLIP served 2000 QPS at 45ms. Real latency benchmarks and the trade-offs papers don't mention.
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Speculative Decoding: Why 2x Faster Inference Fails
Speculative decoding promises 2x faster LLM inference, but real-world gains often disappoint. Debug the hidden bottlenecks killing your speedup.