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Blog · Page 52
A brand is no longer what you say; it's what people find online.
AGI (artificial general intelligence) is a hypothetical system that learns and adapts across a wide range of tasks at human level. Definitions, limits of today's models, and what it means for business.
What is JWT, how does it work, and when should you use it? A plain guide to the structure, session cookie comparison, OAuth link, security mistakes, and a practical checklist.
What is the Turing test, how is it set up, and what does it measure? A balanced guide to the imitation game, the Chinese Room, CAPTCHA, and chatbot transparency for businesses.
AI scaling laws describe why model performance improves in a predictable way as size, data, and compute grow. Learn how they work, what limits them, and what they mean for business.
An AI jailbreak is a user's attempt to push a model outside its safety rules. We explain how it differs from prompt injection, the business risks and the defense layers.
A foundation model is a large AI model pre-trained on broad data and adapted to many tasks. Learn how it differs from an LLM, what risks it carries, and how to choose one.
A GAN trains two neural networks against each other so one learns to create realistic data. See how it works, why training is hard, and how it compares to diffusion models and VAEs.
What is microservices architecture, how does it differ from a monolith and a modular monolith, and when is it too early? Benefits, costs, migration strategy and a decision checklist.
Model collapse is the loss of diversity when AI models train generation after generation on AI-made data. We explain the mechanism, the link to synthetic data, and ways to prevent it in plain language.
Chunking splits long documents into meaningful pieces an AI system can search. We explain strategies, the chunk size trade-off, metadata, table and PDF problems, and a checklist.
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