NVIDIA Cosmos: The Makings of a World Foundation Model
World foundation models are neural networks that simulate real-world environments and predict accurate outcomes based on text, image, or video input.
Multimodal Makers | Mixpeek
Learn best practices, reference architectures and follow example tutorials to build multimodal AI applications
AI Video Tagging With Dynamic Taxonomies
AI video tagging used to mean manual review and basic object detection. With multimodal models and dynamic taxonomies, you can now automatically detect brand moments, inappropriate content, actions, moods and trending content at scale.
Building your own AI-Powered Media Asset Management System
This guide will walk developers through building a modern Media Asset Management (MAM) system with semantic search capabilities using Mixpeek's infrastructure.
Semantic Video Chunking: Scene Detection
Intelligent video chunking using scene detection and vector embeddings. This tutorial covers how to break down videos into semantic scenes, generate embeddings, and enable powerful semantic search capabilities.
Reverse Image Search with CLIP and MongoDB
AI-powered image discovery app using Mixpeek's multimodal SDK and MongoDB's $vectorSearch. Features deep learning, vector embeddings, and KNN search for advanced visual content management.
Advanced Video Understanding: Mixpeek Embed and Weaviate KNN for Multimodal AI
This article demonstrates how to build a reverse video search system using Mixpeek for video processing and embedding, and Weaviate as a vector database, enabling both video and text queries to find relevant video segments through semantic similarity.
Hybrid search on distributed signals for multimodal understanding
Our brains process multiple inputs simultaneously. Mixpeek brings this power to AI, enabling multimodal video understanding. Search across transcripts, visuals, and more for truly intelligent content analysis. #AI #VideoAnalytics
Transforming Multimodal Search with Mixpeek 0.9.0
At Mixpeek, we're on a mission to make multimodal search (images, videos, audio and text) accessible and powerful.
Semantic Video Search: Unlocking Visual Content
Find, analyze, and leverage visual information within your video library using advanced AI and natural language processing, revolutionizing how you interact with and extract value from your multimedia assets.
Mixpeek & FLUX for Multimodal RAG
Building a Comprehensive Image Indexing, Retrieval, and Generation Pipeline Using Mixpeek and Replicate's FLUX
Multimodal Classification: A Practical Tool for Organizing Your Diverse Content
Streamline your content management with Mixpeek’s Multimodal Classification. Automatically categorize videos, images, audio files, and text into predefined categories, making data retrieval faster and more efficient. Ideal for businesses handling diverse content types.
AI-Powered Video Captioning Models for Hybrid Video Retrieval
Automatic, AI-generated video captioning for video
Top 5 Most Impactful Computer Vision Papers of 2024
Here's a look at the top 5 most impactful papers, their significance, and their implications for the future.
Multimodal AI for Visual Property Analysis in Insurance
From pristine offices to high-risk buildings, see how smart visual analysis is saving insurers millions.
Scaling Video Processing with Celery and Render
Build a scalable, distributed video processing pipeline using celery and render with fastapi
How We Indexed the 1000 Top Movie Trailers for AI Apps
In the ever-evolving landscape of digital content, the ability to process vast amounts of unstructured data has become a game-changer.
Risk Assessment with Video Understanding
In today's data-driven world, insurance companies are constantly seeking innovative ways to assess risk accurately and efficiently. Mixpeek
Building a Multimodal Data Processing Pipeline with Kafka, Airflow, and SageMaker
Build a multimodal data processing pipeline using Apache Kafka, Apache Airflow, and Amazon SageMaker. This pipeline will handle various file types (image, video, audio, text, and documents) in parallel, process them through custom ML tasks, and store the results in a database.
Set Up and Run OpenAI's CLIP on SageMaker for Inference
How to deploy and run OpenAI's CLIP model on Amazon SageMaker for efficient real-time and offline inference.
Reverse Video Search
Reverse video search allows us to use a video clip as an input for a query against videos that have been indexed in a vector store.
Video Scene Detection Embedding Models
Using semantic video understanding models to intelligently locate key scenes across petabytes of videos.
Introducing VUSE: Video Understanding and Semantic Embedding
State-of-the art video understanding model that converts videos into embeddings.
Build an S3 RAG App with Langchain and MongoDB KNN
Unlock the power of your unstructured data with Mixpeek, automating ETL from S3 to MongoDB and enabling advanced question answering, content analysis, and semantic search capabilities through LangChain's cutting-edge AI models.
Unlock your S3 Bucket with Mixpeek and MongoDB KNN
The standard design pattern when you want to serve non JSON data to your client is to first store it