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Tag: multimodal

  • Building a Multimodal RAG That Responds with Text, Images, and Tables from Sources

    Building a Multimodal RAG That Responds with Text, Images, and Tables from Sources Why do few chatbots return figures from source documents in their responses? The post Building a Multimodal RAG That Responds with Text, Images, and Tables from Sources appeared first on Towards Data Science. Partha Sarkar Go to original source

  • Multimodal Bandits: Regret Lower Bounds and Optimal Algorithms

    Multimodal Bandits: Regret Lower Bounds and Optimal Algorithms arXiv:2510.25811v1 Announce Type: new Abstract: We consider a stochastic multi-armed bandit problem with i.i.d. rewards where the expected reward function is multimodal with at most m modes. We propose the first known computationally tractable algorithm for computing the solution to the Graves-Lai optimization problem, which in turn…

  • Unlocking Multimodal Video Transcription with Gemini

    Unlocking Multimodal Video Transcription with Gemini Explore how to transcribe videos with speaker identification in a single prompt The post Unlocking Multimodal Video Transcription with Gemini appeared first on Towards Data Science. Laurent Picard Go to original source

  • Four AI Minds in Concert: A Deep Dive into Multimodal AI Fusion

    Four AI Minds in Concert: A Deep Dive into Multimodal AI Fusion Introduction: From System Architecture to Algorithmic Execution In my previous article, I explored the architectural foundations of the VisionScout multimodal AI system, tracing its evolution from a simple object detection model into a modular framework. There, I highlighted how careful layering, module boundaries,…

  • LLaVA on a Budget: Multimodal AI with Limited Resources

    LLaVA on a Budget: Multimodal AI with Limited Resources Let’s get started with multimodality The post LLaVA on a Budget: Multimodal AI with Limited Resources appeared first on Towards Data Science. Marcello Politi Go to original source

  • Multimodal Search Engine Agents Powered by BLIP-2 and Gemini

    Multimodal Search Engine Agents Powered by BLIP-2 and Gemini This post was co-authored with Rafael Guedes. Introduction Traditional models can only process a single type of data, such as text, images, or tabular data. Multimodality is a trending concept in the AI research community, referring to a model’s ability to learn from multiple types of…

  • Generative Distribution Prediction: A Unified Approach to Multimodal Learning

    Generative Distribution Prediction: A Unified Approach to Multimodal Learning arXiv:2502.07090v1 Announce Type: new Abstract: Accurate prediction with multimodal data-encompassing tabular, textual, and visual inputs or outputs-is fundamental to advancing analytics in diverse application domains. Traditional approaches often struggle to integrate heterogeneous data types while maintaining high predictive accuracy. We introduce Generative Distribution Prediction (GDP), a…

  • Multimodal RAG: Process Any File Type with AI

    Multimodal RAG: Process Any File Type with AI A beginner-friendly guide with example (Python) code This is the third article in a larger series on multimodal AI. In the previous posts, we discussed multimodal LLMs and embedding models, respectively. In this article, we will combine these ideas to enable the development of multimodal RAG systems. I’ll…