When you want to integrate generative AI into a product, three options come up often: RAG, fine-tuning, and SLMs (Small Language Models). In practice, these are three different levers: one brings the right context into the prompt, another shapes the model’s behavior, and the third changes the economics and deployment. Understanding the 3 approaches RAG […]
Two big families dominate the conversation around “AI that understands the world”: So, “which one is best?” doesn’t have a single answer. Definition: what do we call a World Model? A world model learns a latent representation of an environment and a transition function: if I’m in state X and I take action A, what […]
A useful “ops” agent isn’t a chatbot that just “answers.” It’s a system that executes actions cleanly: creating and updating tickets, notifying Slack, keeping a Notion page up to date, opening or commenting on a GitLab issue/MR, and, most importantly, keeping everything consistent. The real challenge isn’t AI. It’s orchestration, reliability, and managing side effects. […]
Over the past few years, we’ve hit a real turning point: an image or a video is no longer proof. Between generative AI and deepfakes, “seeing” isn’t enough anymore. Fake content is getting more realistic, detection tools are improving more slowly, and platforms like Instagram or TikTok still aren’t ready to display clear, user-friendly proof […]
For years, “doing AI” basically meant “sending data to a server” (Microsoft, Google, OpenAI, and others). It made sense: models were huge, GPUs were expensive, and latency was acceptable. But that’s changing. Hardware has caught up with software, and not only through GPUs. NPUs (Neural Processing Units) are becoming common in PCs and smartphones, designed […]