C4: Container, Code, Cloud & Context
Designing intelligent systems, one layer at a time. ~ Nithin Mohan T K
Throughout my two decades in machine learning and AI systems, few developments have captured my imagination quite like the convergence of meta-learning with generative models. The ability to teach machines not just to learn, but to learn how to learn efficiently from minimal examples, represents a fundamental shift in how we approach AI system design. […]
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The moment I first deployed a production generative AI application on AWS, I realized we had crossed a threshold that would fundamentally change how enterprises build intelligent systems. After spending two decades architecting solutions across every major cloud platform, I can say with confidence that AWS has assembled the most comprehensive generative AI ecosystem available […]
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The moment I truly understood tokenization was not when I read about it in a textbook, but when I watched a production NLP pipeline fail catastrophically because of an edge case the tokenizer could not handle. After two decades of building enterprise systems, I have learned that tokenization—the seemingly simple act of breaking text into […]
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The first time I watched a generative model produce coherent text from a simple prompt, I knew we had crossed a threshold that would reshape how we build software. After two decades of working with various AI and ML systems, from rule-based expert systems to deep learning pipelines, I can say with confidence that generative […]
Read more →A comprehensive guide to OpenAI’s GPT model family. Understand the differences between GPT-3.5, GPT-4, and GPT-4 Turbo, including pricing, features, context windows, and practical implementation advice for developers.
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