Using AI multimodal models for your applications (Part 3)

The article considers the use of two powerful multimodal models AI - Reka and Gemini 1.5 Pro. These models allow you to develop systems that process text, image or video and audio without the need for additional models to convert text into language or recognize language. 🚀

The structure of multimodal models uses common spaces of representation, attention mechanisms and interaction on different modalities. 💡

Reka offers three basic models: Reka Core, Reka Flash and Reka Edge. They are designed to perform various tasks, including the generation of text from video and images, translation of language and answering complex questions from long multimodal documents. 🧠

GEMINI 1.5 PRO has been developed by Google DeepMind and allows you to perform complex tasks effectively thanks to the new Mixture-Off-Experts (MOE) system. ⚡

• 📌 Multi -modal models process different types of input data - text, images, audio - in a common space.
• 📌 Attention mechanisms help models focus on the most important parts of each input.
• 📌 In many models, the input data of the same modality can control the generation or interpretation of other modality.
• 📌 Models are usually pre -learned on large data sets of different types and then specified for specific tasks.