Production

yourself how real machine learning products actually run in major tech corporations or departments? If yes, this text is for you 🙂 Before discussing scalability, please don’t hesitate to read my first article on...

Do you see yourself as a full-stack developer? How does your experience across the entire stack (from frontend to database) change the way you view the information scientist role? I do, but not within the...

, whether you’re a manager, an information scientist, an engineer, or a product owner, you’ve almost definitely been in no less than one meeting where the discussion revolved around “putting a model in production.” But...

, I worked on real-time fraud detection systems and suggestion models for product corporations that looked excellent during development. Offline metrics were strong. AUC curves were stable across validation windows. Feature importance plots told...

first stable v1.0 release in late October 2025. After spending the past two months working with their latest APIs, I genuinely feel that is essentially the most coherent and thoughtfully designed version of...

couple of years, RAG has became a type of credibility signal within the AI field. If an organization desires to look serious to investors, clients, and even its own leadership, it’s now expected...

Reaching the subsequent stage requires a three-part approach: establishing trust as an operating principle, ensuring data-centric execution, and cultivating IT leadership able to scaling AI successfully. Trust as a prerequisite for scalable,...

are large-scale AI models trained on an unlimited and diverse range of information, comparable to audio, text, images, or a mix of them. For this reason versatility, foundation models are revolutionizing Natural Language...