--- title: Best Multimodal posts of 2025 | daily.dev description: The most upvoted Multimodal posts of 2025, curated by the daily.dev community. canonical: https://daily.dev/tags/multimodal/best-of/2025 twitter:card: summary_large_image twitter:site: @dailydotdev og:url: https://daily.dev/tags/multimodal/best-of/2025 og:type: website og:site_name: daily.dev og:title: Best Multimodal posts of 2025 | daily.dev og:description: The most upvoted Multimodal posts of 2025, curated by the daily.dev community. og:image: https://media.daily.dev/image/upload/s--VAY5ToZt--/f_auto/v1724209435/public/daily.dev%20-%20open%20graph --- # Best of Multimodal — 2025 1. 1 [](/posts/how-llms-see-images-audio-and-more-tsvkahega "How LLMs See Images, Audio, and More") Article ByteByteGo · 1y How LLMs See Images, Audio, and More Modern AI systems process images, audio, and video by converting them into discrete tokens, similar to text processing. Images use patch embeddings (dividing into grid squares), vector quantization (learning visual codebooks), or contrastive embeddings. Audio employs neural codecs for quality preservation, ASR transcription for semantic content, or hierarchical approaches for multi-scale representation. Each tokenization method involves trade-offs between computational efficiency, information preservation, and semantic understanding, with the optimal choice depending on specific use cases and requirements. 138 2. 2 [](/posts/building-real-time-multimodal-ai-pipelines-xqsbruifc "Building Real-Time Multimodal AI Pipelines") Article Salesforce Engineering · 1y Building Real-Time Multimodal AI Pipelines Salesforce engineering team built real-time multimodal AI capabilities for Prompt Builder that process PDFs, images, and documents without pre-indexing. The system handles 50 million daily file uploads through a unified architecture serving both Data Cloud and non-Data Cloud customers. Key innovations include a real-time file processing pipeline with base64 conversion, a compatibility abstraction layer for multiple LLM providers (OpenAI, Gemini, Anthropic), and partial grounding validation that processes files independently rather than failing entire workflows. The solution unlocks file-based business data for AI agents, enabling use cases like automated document field extraction, insurance claim assessments, and case attachment summarization. 37 3. 3 [](/posts/build-a-multimodal-agentic-rag-p38xdqqwt "Build a Multimodal Agentic RAG") Article Daily Dose of Data Science | Avi Chawla | Substack · 1y Build a Multimodal Agentic RAG A comprehensive guide to building a multimodal agentic RAG system that processes both documents and audio files using speech input. The tutorial covers the complete workflow from data ingestion and audio transcription with AssemblyAI, to embedding storage in Milvus vector database, and orchestration with CrewAI Flows. The system allows users to query information using voice commands, with agents retrieving relevant context and generating cited responses. The implementation includes deployment using Beam for serverless containers and a Streamlit interface for user interaction. 16 4. 4 [](/posts/build-the-ultimate-mcp-server-for-multimodal-ai-mkwehvna6 "Build the Ultimate MCP Server for Multimodal AI") Article Daily Dose of Data Science | Avi Chawla | Substack · 1y Build the Ultimate MCP Server for Multimodal AI A comprehensive guide to building an MCP (Model Context Protocol) server that enables multimodal AI capabilities across text, images, audio, and video. The tutorial demonstrates using Pixeltable as the multimodal AI infrastructure and CrewAI for orchestrating agent workflows. The system includes specialized agents for different modalities, a router agent for query classification, and a synthesis agent for response generation. The implementation supports RAG (Retrieval-Augmented Generation) operations across all media types through Docker-deployed MCP servers. 14 1 5. 5 [](/posts/vision-language-models-better-faster-stronger--nwsn5gyhe "Vision Language Models (Better, Faster, Stronger)") Article Hugging Face · 1y Vision Language Models (Better, Faster, Stronger) This post reviews the developments in vision language models over the past year, highlighting new model architectures, specialized capabilities, and emerging paradigms. It covers trends such as any-to-any models, reasoning models, smaller yet capable models, and multimodal safety models, offering insights into how these innovations are shaping the future of AI. 12 [See all Multimodal archives](/tags/multimodal/best-of) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@graph":[{"@type":"CollectionPage","@id":"https://daily.dev/tags/multimodal/best-of/2025#page","url":"https://daily.dev/tags/multimodal/best-of/2025","name":"Best Multimodal Posts of 2025","description":"The most upvoted Multimodal posts of 2025, curated by the daily.dev community.","isPartOf":{"@type":"WebSite","url":"https://daily.dev"}},{"@type":"ItemList","@id":"https://daily.dev/tags/multimodal/best-of/2025#items","numberOfItems":5,"itemListElement":[{"@type":"ListItem","position":1,"url":"https://daily.dev/posts/how-llms-see-images-audio-and-more-tsvkahega","name":"How LLMs See Images, Audio, and More"},{"@type":"ListItem","position":2,"url":"https://daily.dev/posts/building-real-time-multimodal-ai-pipelines-xqsbruifc","name":"Building Real-Time Multimodal AI Pipelines"},{"@type":"ListItem","position":3,"url":"https://daily.dev/posts/build-a-multimodal-agentic-rag-p38xdqqwt","name":"Build a Multimodal Agentic RAG"},{"@type":"ListItem","position":4,"url":"https://daily.dev/posts/build-the-ultimate-mcp-server-for-multimodal-ai-mkwehvna6","name":"Build the Ultimate MCP Server for Multimodal AI"},{"@type":"ListItem","position":5,"url":"https://daily.dev/posts/vision-language-models-better-faster-stronger--nwsn5gyhe","name":"Vision Language Models (Better, Faster, Stronger)"}]},{"@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Tags","item":"https://daily.dev/tags"},{"@type":"ListItem","position":3,"name":"Multimodal","item":"https://daily.dev/tags/multimodal"},{"@type":"ListItem","position":4,"name":"Best of","item":"https://daily.dev/tags/multimodal/best-of"},{"@type":"ListItem","position":5,"name":"2025"}]}]} ```