AI models capable of generating new content, text, code, and images.
Multimodal RAG lets you search an image database with text or images, then generate intelligent responses. It combines three technologies: embedding model, vector database, and multimodal LLM. How the Landscape Changed in 7 Years Around 2019, we built data processing systems RAG with numpy, scikit-learn, RabbitMQ, and PostgreSQL. Today, the ecosystem shifted completely – instead… more
The legal industry faces a digital transformation challenge. Generative AI models offer tremendous potential – from automating document analysis to supporting legal opinion preparation. However, standard solutions like ChatGPT or public models carry risks that law firms cannot afford. A proprietary LLM/RAG system is the answer to these challenges. Why It’s Worth Investing in Your… more
I built my first RAG in 2019. The task was to create a product that worked like this: send a photo of clothing, the application suggests 10 most similar products and links to various stores. I needed to gather a database of stores, their products, and photos, then transform those images into vectors and embed… more