AI & Models16 min
July 28, 2026RAG vs Fine-Tuning: What Teams Are Choosing in 2025? Data from Practice
New benchmarks show: hybrid approach (RAG + fine-tuning) delivers 86% accuracy vs 75% for base GPT-4. How to choose in practice?
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AI & Models
RAG, fine-tuning, embeddings, AI costs, and language model architecture.
AI & Models17 min
July 14, 2026AI Costs in Production: How to Optimize OpenAI and Gemini Spending
The cost difference between closed and open-source models reaches 62x. Learn routing, caching, and compression strategies that will reduce bills by 85%.
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AI & Models17 min
July 9, 2026World Models vs LLM: Revolution in AI Based on the Physics of Reality
Major AI labs are transitioning from language models to World Models. Analysis of NVIDIA's Cosmos architecture and the future of physical AI.
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AI & Models11 min
July 7, 2026Embeddings in E-commerce: Better Search Without Large Models
Embedding technology is revolutionizing product search and recommendations without the need for massive AI models. See how this method works.
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AI & Models6 min
June 21, 2026SFT in Practice: How Fine-Tuning a Small Language Model Can Beat GPT-5 at Invoice Processing
Running frontier LLMs in production is expensive and slow. Learn how LoRA fine-tuning of a 2B Vision Language Model on an NVIDIA L4 GPU achieves parity with GPT-5 at a fraction of the cost.
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AI & Models2 min
April 11, 2026Small Language Models – Benefits and Pitfalls
In the world of machine learning systems, a thoughtful shift is taking place. Instead of betting on gigantic, difficult-to-scale models, we increasingly opt for "agile" ones. Small Language Models (**SLMs**) promise lower costs and faster adaptation to project specifics. Sounds good, but concrete challenges stand behind success.
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