Retrieval Augmented Generation Chatbot uses a knowledge base to answer questions about information the model has no clue about. The knowledge base usually is an organization's internal documentation. The model has never seen the documentation during the training process. The documentation is given to the model as a context inside the prompt, and therefore, the model is able to answer questions correctly.
Apple has introduced Embedding Atlas, a new open-source tool for visualizing and exploring large-scale embeddings interactively. Designed for researchers, data scientists, and developers, the platform provides a fast and intuitive way to analyze complex, high-dimensional data-from text embeddings to multimodal representations-without requiring any backend infrastructure or external data upload. The system runs entirely in the browser, meaning all computations, including embedding generation and projection, happen locally.
You have 10,000 images. Maybe 100,000. How do you know what's really in your dataset? Which samples are redundant? Which are rare and valuable? Are there hidden patterns or quality issues lurking in your training data? Staring at individual images won't scale. Aggregate metrics hide the details. But neural network embeddings give you X-ray vision into your visual data. They enable you see structure, search semantically, and systematically clean your dataset.
The late English writer Douglas Adams is best known as the author of the 1979 book The Hitchhiker's Guide to the Galaxy. But there is much more to Adams than what is written in his Wikipedia entry. Whether or not you need to know that his birth sign is Pisces or that libraries worldwide store his books under the same string of numbers - 13230702 - you can if you head to an overlooked corner of the Wikimedia Foundation called Wikidata.
