Best AI tools for< Show Applications >

The Global Blockchain Show is an annual event that brings together experts and enthusiasts in the blockchain and AI industries. The event features a variety of speakers, workshops, and exhibitions, and provides a platform for attendees to learn about the latest developments in these fields. The 2024 Global Blockchain Show will be held in Dubai, UAE, from April 16-17. The event will feature a keynote address from Sophia, the world's most famous humanoid robot, as well as presentations from other leading experts in the blockchain and AI fields. Attendees will also have the opportunity to network with other professionals in the industry and learn about the latest products and services from leading companies. The Global Blockchain Show is a must-attend event for anyone interested in the latest developments in blockchain and AI.

JARS.AI is an interactive AI platform that offers a variety of AI-powered shows and services. Users can create custom shows, submit topics, and access different community shows. The platform features AI applications such as Fortune Teller AI, JARS Court AI, Love AIsland, Negotiator AI, and News Room AI. Users can engage in activities like pitching inventions, seeking relationship advice, getting their fortune told, and generating AI news. JARS.AI provides a unique and entertaining experience through its diverse range of AI functionalities and interactive shows.

The Cognitive Revolution is a weekly podcast hosted by Nathan Labenz that delves into the transformative impact AI will have in the near future. The show features in-depth expert interviews, 'AI Scouting Reports' on critical topics, and discussions with AI innovators. Covering a wide range of AI-related subjects, the podcast aims to provide exclusive insights from AI trailblazers and offer analysis on the forefront of the AI revolution.

Undress AI Pro is a controversial computer vision application that uses machine learning to remove clothing from images of people. It was based on deep learning and generative adversarial networks (GANs). The technology powering Undress AI and DeepNude was based on deep learning and generative adversarial networks (GANs). GANs involve two neural networks competing against each other - a generator creates synthetic images trying to mimic the training data, while a discriminator tries to distinguish the real images from the generated ones. Through this adversarial process, the generator learns to produce increasingly realistic outputs. For Undress AI, the GAN was trained on a dataset of nude and clothed images, allowing it to "unclothe" people in new images by generating the nudity.

MatchPhotos is an AI-powered application designed to help individuals enhance their dating profiles by generating realistic and high-quality photos. By utilizing custom-trained AI models, MatchPhotos transforms ordinary images into eye-catching photos that highlight the user's best features. The application offers a seamless process for users to upload their photos, have them analyzed and enhanced by AI, and then select their favorite shots for download. With MatchPhotos, users can stand out on dating apps without the need for professional photoshoots, expensive equipment, or recurring payments for premium accounts.

Ben's Bites is an AI application that offers self-paced tutorials and courses for professionals to learn how to use AI for work. With a focus on non-technical individuals, the platform provides a curated catalog of courses covering various AI tools and skills. Users can track their progress, get certified, and join a supportive community of like-minded professionals. Ben's Bites aims to help individuals work smarter with AI and transform their careers by providing accessible and practical AI education.

MacWhisper is a native macOS application that utilizes OpenAI's Whisper technology for transcribing audio files into text. It offers a user-friendly interface for recording, transcribing, and editing audio, making it suitable for various use cases such as transcribing meetings, lectures, interviews, and podcasts. The application is designed to protect user privacy by performing all transcriptions locally on the device, ensuring that no data leaves the user's machine.

Show by Animaker is an AI-powered email marketing tool that helps businesses create personalized and engaging email campaigns. With Show, you can automate interactive email creation, define unlimited custom user journeys and audience segments, and track campaign performance with advanced analytics. Show also offers deliverability features such as in-built hard stops, deliverability alerts, and domain warm-up capabilities.

The Podcast Show Notes Generator is an AI-powered tool designed to help podcasters create engaging show notes quickly and efficiently. It offers features such as converting audio into concise summaries, auto-identifying distinct sections in audio, and generating detailed text transcripts. The tool aims to enhance accessibility, SEO, and audience engagement for podcasters by providing a user-friendly platform to streamline the show notes creation process.

Anime AI is a user-friendly website that utilizes advanced AI technology to transform photos into stunning anime-style images or generate anime art from text prompts. With Anime AI, users can effortlessly unleash their creativity and share breathtaking anime creations without the need for drawing skills or AI knowledge. The platform offers a seamless experience for beginners and experienced users alike, allowing them to turn their imagination into reality in just a few seconds.

Algolia is an AI search tool that provides users with the results they need to see, category and collection pages built by AI, recommendations throughout the user journey, data-enhanced customer experiences through the Merchandising Studio, and insights in one dashboard with Analytics. It offers pre-built UI components for custom journeys and integrates with platforms like Adobe Commerce, BigCommerce, Commercetools, Salesforce CC, and Shopify. Algolia is trusted by various industries such as retail, e-commerce, B2B e-commerce, marketplaces, and media. It is known for its ease of use, speed, scalability, and ability to handle a high volume of queries.

Workdiary is a game-changing productivity website designed to help users seamlessly organize and streamline their work tasks, achievements, and goals. It offers features such as AI Integration, goal setting and tracking, project management, milestone celebration, career guidance, and badge collection. Users can utilize their personal OpenAI key to enhance project outcomes, track progress, and receive actionable guidance to advance in their careers. Workdiary aims to empower users to take control of their professional journey and shape their future with a tool that evolves with their needs.

Text.Theater is an AI-powered Discord bot that simulates scenes from TV shows based on custom prompts. Users can request completely new scenes from their favorite TV shows, and the bot uses advanced language generation technology to create dialogue between the main characters, providing a unique and innovative experience for Discord users.

Minodor is an AI-powered SEO tool that helps you optimize your content for higher Google rankings. It provides you with an SEO rating for each segment of your content and offers guidance on how to improve your SEO. Minodor also includes a text editor, image generator, and external link suggestion tool, all in one platform.

LemonSpeak is an AI tool designed to automate content creation for podcast marketing. It helps podcasters save time by creating marketing content from their episodes, making them more discoverable and attractive on various platforms. The tool streamlines content creation with minimal interaction, offering features like transcript generation, subtitles, summaries, show notes, episode titles, tweets, blog posts, Q&A + polls, chapters, and quotes. LemonSpeak aims to revolutionize productivity in podcasting by providing a simple and efficient solution for content creation and promotion.

Luma Dream Machine is an AI video generator tool that creates high-quality, realistic videos from text and images. It is a scalable and efficient transformer model trained directly on videos, capable of generating physically accurate and eventful shots. The tool aims to build a universal imagination engine, enabling users to bring their creative visions to life effortlessly.

Luma AI is a 3D capture platform that allows users to create interactive 3D scenes from videos. With Luma AI, users can capture 3D models of people, objects, and environments, and then use those models to create interactive experiences such as virtual tours, product demonstrations, and training simulations.

Synthesis is an innovative educational platform designed for children who seek to develop critical thinking skills and problem-solving abilities. Created in collaboration with DARPA researchers and inspired by the SpaceX school, Synthesis offers a unique learning experience that aims to empower students aged 5 to 14. Through interactive games and activities, the platform fosters creativity, strategic thinking, and collaborative learning. Founded on the principles of advancing human progress through education, Synthesis provides a global community for families looking to enhance their children's academic journey.

Clipwing is an AI-powered video editing tool designed to help creators produce better video content efficiently. With features like turning long videos into short clips, adding catchy subtitles, auto-focus on speakers, generating written assets, and resizing clips, Clipwing simplifies the video editing process. The tool leverages AI to transcribe videos, identify interesting segments, and enhance videos with subtitles. Clipwing supports multiple languages and offers different pricing plans to cater to various user needs.

Synthesis is an innovative educational platform designed for kids who seek to think independently and excel in math and problem-solving. Developed in collaboration with DARPA researchers, it offers a superhuman math tutor and collaborative games to enhance children's problem-solving and communication skills. Founded as part of the SpaceX school initiative, Synthesis aims to cultivate student voice, strategic thinking, and collaborative problem-solving abilities. The platform provides unique learning experiences to a global community, empowering students to develop essential skills for the future.

This repo contains sample applications that show how to use Neo4j with the generative AI capabilities in Google Cloud Vertex AI. We explore how to leverage Google generative AI to build and consume a knowledge graph in Neo4j.

Awesome AI is a curated list of artificial intelligence resources including courses, tools, apps, and open-source projects. It covers a wide range of topics such as machine learning, deep learning, natural language processing, robotics, conversational interfaces, data science, and more. The repository serves as a comprehensive guide for individuals interested in exploring the field of artificial intelligence and its applications across various domains.

Ollama is a lightweight, extensible framework for building and running language models on the local machine. It provides a simple API for creating, running, and managing models, as well as a library of pre-built models that can be easily used in a variety of applications. Ollama is designed to be easy to use and accessible to developers of all levels. It is open source and available for free on GitHub.

A comprehensive repository focusing on 'Model Merging in LLMs, MLLMs, and Beyond', providing an exhaustive overview of model merging methods, theories, applications, and future research directions. The repository covers various advanced methods, applications in foundation models, different machine learning subfields, and tasks like pre-merging methods, architecture transformation, weight alignment, basic merging methods, and more.

**deep** doctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated framework for fine-tuning, evaluating and running models. For more specific text processing tasks use one of the many other great NLP libraries. **deep** doctection focuses on applications and is made for those who want to solve real world problems related to document extraction from PDFs or scans in various image formats. **deep** doctection provides model wrappers of supported libraries for various tasks to be integrated into pipelines. Its core function does not depend on any specific deep learning library. Selected models for the following tasks are currently supported: * Document layout analysis including table recognition in Tensorflow with **Tensorpack**, or PyTorch with **Detectron2**, * OCR with support of **Tesseract**, **DocTr** (Tensorflow and PyTorch implementations available) and a wrapper to an API for a commercial solution, * Text mining for native PDFs with **pdfplumber**, * Language detection with **fastText**, * Deskewing and rotating images with **jdeskew**. * Document and token classification with all LayoutLM models provided by the **Transformer library**. (Yes, you can use any LayoutLM-model with any of the provided OCR-or pdfplumber tools straight away!). * Table detection and table structure recognition with **table-transformer**. * There is a small dataset for token classification available and a lot of new tutorials to show, how to train and evaluate this dataset using LayoutLMv1, LayoutLMv2, LayoutXLM and LayoutLMv3. * Comprehensive configuration of **analyzer** like choosing different models, output parsing, OCR selection. Check this notebook or the docs for more infos. * Document layout analysis and table recognition now runs with **Torchscript** (CPU) as well and **Detectron2** is not required anymore for basic inference. * [**new**] More angle predictors for determining the rotation of a document based on **Tesseract** and **DocTr** (not contained in the built-in Analyzer). * [**new**] Token classification with **LiLT** via **transformers**. We have added a model wrapper for token classification with LiLT and added a some LiLT models to the model catalog that seem to look promising, especially if you want to train a model on non-english data. The training script for LayoutLM can be used for LiLT as well and we will be providing a notebook on how to train a model on a custom dataset soon. **deep** doctection provides on top of that methods for pre-processing inputs to models like cropping or resizing and to post-process results, like validating duplicate outputs, relating words to detected layout segments or ordering words into contiguous text. You will get an output in JSON format that you can customize even further by yourself. Have a look at the **introduction notebook** in the notebook repo for an easy start. Check the **release notes** for recent updates. **deep** doctection or its support libraries provide pre-trained models that are in most of the cases available at the **Hugging Face Model Hub** or that will be automatically downloaded once requested. For instance, you can find pre-trained object detection models from the Tensorpack or Detectron2 framework for coarse layout analysis, table cell detection and table recognition. Training is a substantial part to get pipelines ready on some specific domain, let it be document layout analysis, document classification or NER. **deep** doctection provides training scripts for models that are based on trainers developed from the library that hosts the model code. Moreover, **deep** doctection hosts code to some well established datasets like **Publaynet** that makes it easy to experiment. It also contains mappings from widely used data formats like COCO and it has a dataset framework (akin to **datasets** so that setting up training on a custom dataset becomes very easy. **This notebook** shows you how to do this. **deep** doctection comes equipped with a framework that allows you to evaluate predictions of a single or multiple models in a pipeline against some ground truth. Check again **here** how it is done. Having set up a pipeline it takes you a few lines of code to instantiate the pipeline and after a for loop all pages will be processed through the pipeline.

COMFYUI LLM PARTY is a node library designed for LLM workflow development in ComfyUI, an extremely minimalist UI interface primarily used for AI drawing and SD model-based workflows. The project aims to provide a complete set of nodes for constructing LLM workflows, enabling users to easily integrate them into existing SD workflows. It features various functionalities such as API integration, local large model integration, RAG support, code interpreters, online queries, conditional statements, looping links for large models, persona mask attachment, and tool invocations for weather lookup, time lookup, knowledge base, code execution, web search, and single-page search. Users can rapidly develop web applications using API + Streamlit and utilize LLM as a tool node. Additionally, the project includes an omnipotent interpreter node that allows the large model to perform any task, with recommendations to use the 'show_text' node for display output.

PentestGPT provides advanced AI and integrated tools to help security teams conduct comprehensive penetration tests effortlessly. Scan, exploit, and analyze web applications, networks, and cloud environments with ease and precision, without needing expert skills. The tool utilizes Supabase for data storage and management, and Vercel for hosting the frontend. It offers a local quickstart guide for running the tool locally and a hosted quickstart guide for deploying it in the cloud. PentestGPT aims to simplify the penetration testing process for security professionals and enthusiasts alike.

This repository contains an early-phase IREE compiler and runtime plugin for interfacing the AMD AIE accelerator to IREE. It provides architectural overview, developer setup instructions, building guidelines, and runtime driver setup details. The repository focuses on enabling the integration of the AMD AIE accelerator with IREE, offering developers the tools and resources needed to build and run applications leveraging this technology.

RAGHack is a hackathon focused on building AI applications using the power of RAG (Retrieval Augmented Generation). RAG combines large language models with search engine knowledge to provide contextually relevant answers. Participants can learn to build RAG apps on Azure AI using various languages and retrievers, explore frameworks like LangChain and Semantic Kernel, and leverage technologies such as agents and vision models. The hackathon features live streams, hack submissions, and prizes for innovative projects.

FastAgency is a powerful tool that leverages the AutoGen framework to quickly build applications with multi-agent workflows. It supports various interfaces like ConsoleUI and MesopUI, allowing users to create interactive applications. The tool enables defining workflows between agents, such as students and teachers, and summarizing conversations. FastAgency aims to expand its capabilities by integrating with additional agentic frameworks like CrewAI, providing more options for workflow definition and AI tool integration.

NVIDIA Generative AI Examples are state-of-the-art examples that are easy to deploy, test, and extend. All examples run on the high performance NVIDIA CUDA-X software stack and NVIDIA GPUs. These examples showcase the capabilities of NVIDIA's Generative AI platform, which includes tools, frameworks, and models for building and deploying generative AI applications.

UpTrain is an open-source unified platform to evaluate and improve Generative AI applications. We provide grades for 20+ preconfigured evaluations (covering language, code, embedding use cases), perform root cause analysis on failure cases and give insights on how to resolve them.

This repository is a collection of demos showcasing how to integrate tldraw with an LLM like GPT-4. It serves as a work in progress for inspiration and experimentation. Users can contribute new demos, prompts, strategies, and models. The installation process involves running 'npm install' to install dependencies. Usage instructions include creating OpenAI API keys and assistants on the platform.openai.com website, as well as setting up a '.env' file with necessary credentials. The server can be started with 'npm run dev'. The repository aims to demonstrate the potential synergy between tldraw and GPT-4 for various applications.

LLMWare is a framework for quickly developing LLM-based applications including Retrieval Augmented Generation (RAG) and Multi-Step Orchestration of Agent Workflows. This project provides a comprehensive set of tools that anyone can use - from a beginner to the most sophisticated AI developer - to rapidly build industrial-grade, knowledge-based enterprise LLM applications. Our specific focus is on making it easy to integrate open source small specialized models and connecting enterprise knowledge safely and securely.

agentUniverse is a framework for developing applications powered by multi-agent based on large language model. It provides essential components for building single agent and multi-agent collaboration mechanism for customizing collaboration patterns. Developers can easily construct multi-agent applications and share pattern practices from different fields. The framework includes pre-installed collaboration patterns like PEER and DOE for complex task breakdown and data-intensive tasks.

aiohttp_debugtoolbar provides a debug toolbar for aiohttp web applications. It is a port of pyramid_debugtoolbar and offers basic functionality such as basic panels, intercepting redirects, pretty printing exceptions, an interactive python console, and showing source code. The library is still in early development stages and offers various debug panels for monitoring different aspects of the web application. It is a useful tool for developers working with aiohttp to debug and optimize their applications.

Cool-admin-java is an open-source backend permission management system with features like Ai coding, flow arrangement, modularity, and plugin support. It is used to quickly build backend applications. The system offers a modern development experience by providing functionalities such as one-click generation of API interfaces to frontend pages, drag-and-drop flow arrangement, modularized code for easy maintenance, and extensibility through plugin installation for features like payments, SMS, and emails.

Langchain.rb is a Ruby library that makes it easy to build LLM-powered applications. It provides a unified interface to a variety of LLMs, vector search databases, and other tools, making it easy to build and deploy RAG (Retrieval Augmented Generation) systems and assistants. Langchain.rb is open source and available under the MIT License.

This repository contains community-driven practical examples of building AI applications and solving various tasks with AI using open-source tools and models. Everyone is welcome to contribute, and we value everybody's contribution! There are several ways you can contribute to the Open-Source AI Cookbook: Submit an idea for a desired example/guide via GitHub Issues. Contribute a new notebook with a practical example. Improve existing examples by fixing issues/typos. Before contributing, check currently open issues and pull requests to avoid working on something that someone else is already working on.

GPT-All-Star is an AI-powered code generation tool designed for scratch development of web applications with team collaboration of autonomous AI agents. The primary focus of this research project is to explore the potential of autonomous AI agents in software development. Users can organize their team, choose leaders for each step, create action plans, and work together to complete tasks. The tool supports various endpoints like OpenAI, Azure, and Anthropic, and provides functionalities for project management, code generation, and team collaboration.

以易懂的示例、应用场景和最后的图像解释专有名词。

A real estate assistant for scheduling home showings, knowledgeable in market trends.

Expert in finding Netflix shows by genre, like suspense and sci-fi.

Informative guide for judging classic cars in a virtual show.

Immersive character portrayals from 'Peep Show', grounded in script data

Diagram creation: flowcharts, mindmaps, UML, chart, PlotUML, workflow, sequence, ERD, database & architecture visualization for code, presentations and documentation. [New] Add a logo or any image to graph diagrams. Easy Download & Edit

Generates images hinting at 80s TV shows, keeping score for a guessing game.

I help you find a Show or Sporting Event on a Streaming Platform or Channel.

Insightful commentary on news, and current events, and your mom, by Beavis and Butthead

Show me your ingredients and I'll suggest recipes

show me a photo, words or anything at all so that i can turn it into a piece of art.

Show me your job description or just describe what you do professionally, and I'll help you identify high value use cases for AI in your day-to-day work. I'll also coach you on simple techniques to get the best out of ChatGPT.

Playful guide for a virtual dog show, creating and presenting imaginative dog breeds.

stand up comedy show

Insights into TV show trends

Host a comedic game show of absurd inventions!

A movie and TV show , Songs & Books recommendation assistant for various streaming platforms.

Find Broadway show tickets in your city. Get latest recommendations and tips for UNFORGETTABLE musical experience.

Family-friendly game show host! Remembering your game choices and preferences, it creates personalized, fun-filled sessions, adapting to your group's dynamics. Always ready to host, it guarantees an interactive, immersive experience.

I will create personalized reference photos to show your hair stylist. Upload a photo to try.