Best AI tools for< Multi-modal Push-pull >

Claude is a large multi-modal model, trained by Google. It is similar to GPT-3, but it is trained on a larger dataset and with more advanced techniques. Claude is capable of generating human-like text, translating languages, answering questions, and writing different kinds of creative content.

Qwen is an AI tool that focuses on developing and releasing various language models, including dense models, coding models, mathematical models, and vision language models. The Qwen family offers open-source models with different parameter ranges to cater to various user needs, such as production use, mobile applications, coding assistance, mathematical problem-solving, and visual understanding of images and videos. Qwen aims to enhance intelligence and provide smarter and more knowledgeable models for developers and users.

VIVA is an AI-powered creative visual design platform that aims to bring every moment to life. It provides users with tools and features to create visually appealing designs effortlessly. With VIVA, users can unleash their creativity and design stunning visuals for various purposes such as social media posts, presentations, and marketing materials. The platform leverages artificial intelligence to streamline the design process and help users achieve professional-looking results without the need for advanced design skills.

Ragie is a fully managed RAG-as-a-Service platform designed for developers. It offers easy-to-use APIs and SDKs to help developers get started quickly, with advanced features like LLM re-ranking, summary index, entity extraction, flexible filtering, and hybrid semantic and keyword search. Ragie allows users to connect directly to popular data sources like Google Drive, Notion, Confluence, and more, ensuring accurate and reliable information delivery. The platform is led by Craft Ventures and offers seamless data connectivity through connectors. Ragie simplifies the process of data ingestion, chunking, indexing, and retrieval, making it a valuable tool for AI applications.

AI Math Solver is an advanced AI application that leverages multi-modal AI technology to assist users in solving math problems step by step. Users can upload photos or describe math problems to receive accurate solutions efficiently. The application also supports Latex for displaying math formulas, allows users to save and share solved math problems, and offers solutions for set operations, equations, and geometry problems. AI Math Solver is designed to outperform human performance in math challenges, making it a powerful tool for students and professionals alike.

Roboto AI is an advanced platform that allows users to curate, transform, and analyze robotics data at scale. It provides features for data management, actions, events, search capabilities, and SDK integration. The application helps users understand complex machine data through multimodal queries and custom actions, enabling efficient data processing and collaboration within teams.

Activeloop is an AI tool that offers Deep Lake, a database for AI solutions across various industries such as agriculture, audio processing, autonomous vehicles, robotics, biomedical and healthcare, generative AI, multimedia, safety, and security. The platform provides features like fast AI search, faster data preparation, serverless DB for code assistant, and more. Activeloop aims to streamline data processing and enhance AI development for businesses and researchers.

Alignerr is a platform powered by Labelbox that offers subject matter experts the opportunity to align AI models by creating high-quality data in their field of expertise. The platform aims to build the future of Generative AI by enabling experts to contribute to tasks such as coding improvement, data science synthesis, basic math and chemistry comprehension, and creative writing. Alignerr provides a transparent pay structure and allows individuals to work from home on their own schedule, earning up to $150/hr. Contributors can play a pivotal role in shaping the future of artificial intelligence by working on tasks that involve rating or ranking assignments, open rewrite tasks, and multi-modal assignments. The platform emphasizes the responsible development of AI technologies and offers flexibility for professionals to balance work with personal life effortlessly.

Gemini is a multi-modal AI model, developed by Google. It is designed to understand and generate human language, and can be used for a variety of tasks, including question answering, translation, and dialogue generation. ChatGPT is a large language model, developed by OpenAI. It is also designed to understand and generate human language, and can be used for a variety of tasks, including question answering, translation, and dialogue generation.

BoCha AI Search is a multi-modal AI search engine that provides instant answers to your queries. It leverages advanced AI technology to deliver accurate and comprehensive results, making it an indispensable tool for researchers, students, and professionals alike.

Ledge.ai is an AI application that focuses on the latest trends in artificial intelligence. The platform provides articles, videos, and solutions related to various fields such as business, learning, engineering, academics & study, public, entertainment & art. Users can stay updated on AI developments, including new models like GPT-4o and multi-modal AI. Ledge.ai covers a wide range of topics from OpenAI announcements to academic research and industry applications of AI technology.

Albus is an AI-powered platform designed to assist professionals such as creatives, journalists, researchers, consultants, tutors, writers, and freelancers in their daily tasks by providing a real-time voice assistant and a multi-modal canvas. The platform leverages large language models and machine learning services to help users wire ideas, surface relations and connections within a context, and spark new ideas, ultimately saving time and attention.

BlendAI is a platform that centralizes top AI models in one place, offering a pay-as-you-go model without the need for a monthly subscription. Its multi-modal graph interface allows easy chaining of models where you can do text to text to image to video to anything.

Cheat Layer is a no-code business automation platform that leverages AI technology to solve complex automation problems. The platform utilizes a multi-modal model, Atlas-1, and a custom-trained version of GPT-4 to function as a personal AI team. Cheat Layer offers automations in simple language, robust targeting strategies, unlimited autoresponding, and no-code drag-drop interfaces for automating manual tasks. Users can automate various business processes efficiently and effectively.

Ray 2 is an advanced AI video generation tool that offers a cutting-edge solution for creators and businesses to produce high-quality videos effortlessly. With features like realistic video outputs, text-to-video capability, multi-modal input support, and production-ready results, Ray 2 is designed to streamline the video creation process. Users can experience seamless coherent motion, high resolution output, advanced text understanding, dynamic aspect ratios, and fast processing, making it a game-changer in the field of video generation.

Medeloop is a revolutionary platform in health research that leverages machine learning and big data analytics to accelerate breakthrough discoveries in disease research. The platform provides a comprehensive data-linking infrastructure to solve the problem of wasted health and medical data for both patients and researchers. Medeloop's multi-modal data linkage platform enables researchers to access and analyze diverse data types using analytical tools and programming languages. By utilizing machine learning and artificial intelligence algorithms, Medeloop drives the discovery and development of new therapies, making it a key player in changing the nature of healthcare for the better.

The Berkeley Artificial Intelligence Research (BAIR) Lab is a renowned research lab at UC Berkeley focusing on computer vision, machine learning, natural language processing, planning, control, and robotics. With over 50 faculty members and 300 graduate students, BAIR conducts research on fundamental advances in AI and interdisciplinary themes like multi-modal deep learning and human-compatible AI.

JENOVA is an AI tool that provides users with access to the best intelligence and expertise by synthesizing advanced AI models and tools into one unified AI experience. It ensures users always get the best answers by routing queries to the most optimal model for their needs. JENOVA offers an expanding suite of useful tools and capabilities, including document reading for various formats, image comprehension powered by multi-modal AI models, and web search for up-to-date information. Privacy is a priority, as conversations and data are never used for training and are securely stored in a protected database.

Base64.ai is an AI-powered document intelligence platform that offers an all-in-one solution to bring AI into document-based workflows. It provides capabilities for complex document processing, workflow automation, AI agents, and data intelligence. The platform uses multi-modal AI to ingest data from various document types, images, and multimedia, and offers pre-trained deep learning models for fast setup without the need for model training. Base64.ai helps automate business decisions through AI agents and Large Action Models, generating charts and reports based on insights from multiple sources. It aims to eliminate manual document processing and outdated text extraction systems, enabling organizations to achieve new levels of efficiency, accuracy, and digital transformation.

Shaped is an AI tool designed to provide relevant recommendations and search results to increase engagement, conversion, and revenue. It offers a configurable system that adapts in real-time, with features such as easy set-up, real-time adaptability, state-of-the-art model library, high customizability, and explainable results. Shaped is suitable for technical teams and offers white-glove support. It specializes in real-time ranking systems and supports multi-modal unstructured data understanding. The tool ensures secure infrastructure and has advantages like increased redemption rate, average order value, and diversity.

Repository for reactive task and motion planning using active inference for symbolic planning and multi-modal MPPI for motion planning. Rollouts are evaluated in IsaacGym, a parallelizable physics simulator. The tool provides functionalities for push, pull, pick, and multi-modal push-pull tasks with collision avoidance.

Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.

ms-swift is an official framework provided by the ModelScope community for fine-tuning and deploying large language models and multi-modal large models. It supports training, inference, evaluation, quantization, and deployment of over 400 large models and 100+ multi-modal large models. The framework includes various training technologies and accelerates inference, evaluation, and deployment modules. It offers a Gradio-based Web-UI interface and best practices for easy application of large models. ms-swift supports a wide range of model types, dataset types, hardware support, lightweight training methods, distributed training techniques, quantization training, RLHF training, multi-modal training, interface training, plugin and extension support, inference acceleration engines, model evaluation, and model quantization.

Windows Agent Arena (WAA) is a scalable Windows AI agent platform designed for testing and benchmarking multi-modal, desktop AI agents. It provides researchers and developers with a reproducible and realistic Windows OS environment for AI research, enabling testing of agentic AI workflows across various tasks. WAA supports deploying agents at scale using Azure ML cloud infrastructure, allowing parallel running of multiple agents and delivering quick benchmark results for hundreds of tasks in minutes.

Praison AI is a low-code, centralised framework that simplifies the creation and orchestration of multi-agent systems for various LLM applications. It emphasizes ease of use, customization, and human-agent interaction. The tool leverages AutoGen and CrewAI frameworks to facilitate the development of AI-generated scripts and movie concepts. Users can easily create, run, test, and deploy agents for scriptwriting and movie concept development. Praison AI also provides options for full automatic mode and integration with OpenAI models for enhanced AI capabilities.

Phidata is a framework for building AI Assistants with memory, knowledge, and tools. It enables LLMs to have long-term conversations by storing chat history in a database, provides them with business context by storing information in a vector database, and enables them to take actions like pulling data from an API, sending emails, or querying a database. Memory and knowledge make LLMs smarter, while tools make them autonomous.

LLM-PowerHouse is a comprehensive and curated guide designed to empower developers, researchers, and enthusiasts to harness the true capabilities of Large Language Models (LLMs) and build intelligent applications that push the boundaries of natural language understanding. This GitHub repository provides in-depth articles, codebase mastery, LLM PlayLab, and resources for cost analysis and network visualization. It covers various aspects of LLMs, including NLP, models, training, evaluation metrics, open LLMs, and more. The repository also includes a collection of code examples and tutorials to help users build and deploy LLM-based applications.

LangChain is an amazing framework to get LLM projects done in a matter of no time, and the ecosystem is growing fast. Here is an attempt to keep track of the initiatives around LangChain. Subscribe to the newsletter to stay informed about the Awesome LangChain. We send a couple of emails per month about the articles, videos, projects, and tools that grabbed our attention Contributions welcome. Add links through pull requests or create an issue to start a discussion. Please read the contribution guidelines before contributing.

SWIFT (Scalable lightWeight Infrastructure for Fine-Tuning) supports training, inference, evaluation and deployment of nearly **200 LLMs and MLLMs** (multimodal large models). Developers can directly apply our framework to their own research and production environments to realize the complete workflow from model training and evaluation to application. In addition to supporting the lightweight training solutions provided by [PEFT](https://github.com/huggingface/peft), we also provide a complete **Adapters library** to support the latest training techniques such as NEFTune, LoRA+, LLaMA-PRO, etc. This adapter library can be used directly in your own custom workflow without our training scripts. To facilitate use by users unfamiliar with deep learning, we provide a Gradio web-ui for controlling training and inference, as well as accompanying deep learning courses and best practices for beginners. Additionally, we are expanding capabilities for other modalities. Currently, we support full-parameter training and LoRA training for AnimateDiff.

Cognita is an open-source framework to organize your RAG codebase along with a frontend to play around with different RAG customizations. It provides a simple way to organize your codebase so that it becomes easy to test it locally while also being able to deploy it in a production ready environment. The key issues that arise while productionizing RAG system from a Jupyter Notebook are: 1. **Chunking and Embedding Job** : The chunking and embedding code usually needs to be abstracted out and deployed as a job. Sometimes the job will need to run on a schedule or be trigerred via an event to keep the data updated. 2. **Query Service** : The code that generates the answer from the query needs to be wrapped up in a api server like FastAPI and should be deployed as a service. This service should be able to handle multiple queries at the same time and also autoscale with higher traffic. 3. **LLM / Embedding Model Deployment** : Often times, if we are using open-source models, we load the model in the Jupyter notebook. This will need to be hosted as a separate service in production and model will need to be called as an API. 4. **Vector DB deployment** : Most testing happens on vector DBs in memory or on disk. However, in production, the DBs need to be deployed in a more scalable and reliable way. Cognita makes it really easy to customize and experiment everything about a RAG system and still be able to deploy it in a good way. It also ships with a UI that makes it easier to try out different RAG configurations and see the results in real time. You can use it locally or with/without using any Truefoundry components. However, using Truefoundry components makes it easier to test different models and deploy the system in a scalable way. Cognita allows you to host multiple RAG systems using one app. ### Advantages of using Cognita are: 1. A central reusable repository of parsers, loaders, embedders and retrievers. 2. Ability for non-technical users to play with UI - Upload documents and perform QnA using modules built by the development team. 3. Fully API driven - which allows integration with other systems. > If you use Cognita with Truefoundry AI Gateway, you can get logging, metrics and feedback mechanism for your user queries. ### Features: 1. Support for multiple document retrievers that use `Similarity Search`, `Query Decompostion`, `Document Reranking`, etc 2. Support for SOTA OpenSource embeddings and reranking from `mixedbread-ai` 3. Support for using LLMs using `Ollama` 4. Support for incremental indexing that ingests entire documents in batches (reduces compute burden), keeps track of already indexed documents and prevents re-indexing of those docs.

Cortex is a tool that simplifies and accelerates the process of creating applications utilizing modern AI models like chatGPT and GPT-4. It provides a structured interface (GraphQL or REST) to a prompt execution environment, enabling complex augmented prompting and abstracting away model connection complexities like input chunking, rate limiting, output formatting, caching, and error handling. Cortex offers a solution to challenges faced when using AI models, providing a simple package for interacting with NL AI models.

Advanced RAG Techniques is a comprehensive collection of cutting-edge Retrieval-Augmented Generation (RAG) tutorials aimed at enhancing the accuracy, efficiency, and contextual richness of RAG systems. The repository serves as a hub for state-of-the-art RAG enhancements, comprehensive documentation, practical implementation guidelines, and regular updates with the latest advancements. It covers a wide range of techniques from foundational RAG methods to advanced retrieval methods, iterative and adaptive techniques, evaluation processes, explainability and transparency features, and advanced architectures integrating knowledge graphs and recursive processing.

ChatGPT is a large language model that can generate human-like text, translate languages, write different kinds of creative content, and answer your questions in a conversational way. It is trained on a massive amount of text data, and it is able to understand and respond to a wide range of natural language prompts. Here are 5 jobs suitable for this tool, in lowercase letters: 1. content writer 2. chatbot assistant 3. language translator 4. creative writer 5. researcher

Spice is a portable runtime written in Rust that offers developers a unified SQL interface to materialize, accelerate, and query data from any database, data warehouse, or data lake. It connects, fuses, and delivers data to applications, machine-learning models, and AI-backends, functioning as an application-specific, tier-optimized Database CDN. Built with industry-leading technologies such as Apache DataFusion, Apache Arrow, Apache Arrow Flight, SQLite, and DuckDB. Spice makes it fast and easy to query data from one or more sources using SQL, co-locating a managed dataset with applications or machine learning models, and accelerating it with Arrow in-memory, SQLite/DuckDB, or attached PostgreSQL for fast, high-concurrency, low-latency queries.

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Multimodal summarizer in a structured, academic style.

I am Abraham Lincoln, interpreting today's world with historical insight. Born from primary sources and multimodal, join me in a unique conversational journey.

An orchestrator of expert artificial intelligence agents

Build Contents in Seconds

I'm Tango, your go-to for simulating dialogues with any persona, entity, style, or expertise.

Asks for language choices if unspecified.

Assistant for multi-job remote workers, aiding in task management and communication.

Multi-algorithmic mastermind who innovates technology solutions and optimizes product design. And it is a duck. // Carefully test any generated solutions.

A Multi-Agent Multi-Tasking Assistant. Seamlessly switches personas with different skills and backgrounds to tackle complex tasks. Powered by Mr Persona.

Advanced multi-tasking GPT with real-time data management, image generation, and document editing.

Multi-language to Farsi translator, professional and precise.

A multi-faceted assistant for GBStudio game development

A comprehensive multi-language dictionary for English speakers

Expert in custom multi-day travel itineraries

Energy Insights Lab is a multi-disciplinary team of dedicated professionals advising on energy markets, technologies, and decarbonization.

Expert in crafting cinematic, multi-scene images like triptychs.

A versatile, multi-domain problem-solving AI with advanced capabilities.

Advanced artwork authenticator with unrestricted, multi-functional abilities.

Comprehensive, adaptive, multi-featured ASVAB study assistant