Best AI tools for< Show Drills >

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.

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.

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.

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.

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.

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.

The Valentine Generator powered by OpenAI is an AI tool that generates personalized messages for your loved ones. It allows users to input keywords and recipient details to create unique and heartfelt messages. The tool aims to add a touch of creativity and fun to the act of expressing love and affection through digital means. Users can generate messages with human emotions and share them with their loved ones easily.

Swell AI is a powerful writing tool that uses artificial intelligence to help you create high-quality content for your podcast, blog, or website. With Swell AI, you can easily generate podcast show notes, transcripts, articles, summaries, titles, social media posts, and more. Swell AI is also a great tool for creating chatbots for your podcast episodes. With Swell AI, you can easily create a chatbot that can answer any question about your episode. Swell AI is easy to use and integrates with all of your favorite podcasting and content creation tools. Start using Swell AI today and see how it can help you create amazing content that will engage your audience and grow your business.

Bento is a personalized 'Link in Bio' platform that allows users to showcase all aspects of their identity and creations in one visually appealing page. It enables users to display their videos, podcasts, newsletters, photos, paid products, streams, and calendar events seamlessly. Bento aims to provide a central hub for users to share and monetize their content effectively, eliminating the need for multiple links. The platform is designed in Berlin and caters to creatives seeking a comprehensive and visually stunning way to present their work.

Podcast Marketing AI is a powerful tool that helps you create high-quality podcast marketing assets quickly and easily. With our AI-powered technology, you can generate transcripts, show notes, blog posts, social media posts, and more, all in one place. Our AI is trained on a massive dataset of podcast content, so it can generate content that is both accurate and engaging.

DeepSeek is a new experimental architecture for a large language model (LLM) powered internet-scale retrieval engine. Unlike current research agents designed as answer engines, DeepSeek aims to process a vast amount of sources to collect a comprehensive list of entities and enrich them with additional relevant data. The end result is a table with retrieved entities and enriched columns, providing a comprehensive overview of the topic. DeepSeek utilizes both standard keyword search and neural search to find relevant content, and employs an LLM to extract specific entities and their associated contents. It also includes a smaller answer agent to enrich the retrieved data, ensuring thoroughness. DeepSeek has the potential to revolutionize research and information gathering by providing a comprehensive and structured way to access information from the vastness of the internet.

This sample demonstrates a few approaches for creating ChatGPT-like experiences over your own data using the Retrieval Augmented Generation pattern. It uses Azure OpenAI Service to access a GPT model (gpt-35-turbo), and Azure AI Search for data indexing and retrieval. The repo includes sample data so it's ready to try end to end. In this sample application we use a fictitious company called Contoso Electronics, and the experience allows its employees to ask questions about the benefits, internal policies, as well as job descriptions and roles.

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.

Extrapolate is an app that uses Artificial Intelligence to show you how your face ages over time. It generates a 3-second GIF of your aging face and allows you to store and retrieve photos from Cloudflare R2 using Workers. Users can deploy their own version of Extrapolate on Vercel by setting up ReplicateHQ and Upstash accounts, as well as creating a Cloudflare R2 instance with a Cloudflare Worker to handle uploads and reads. The tool provides a fun and interactive way to visualize the aging process through AI technology.

The LandingLens Python library contains the LandingLens development library and examples that show how to integrate your app with LandingLens in a variety of scenarios. The library allows users to acquire images from different sources, run inference on computer vision models deployed in LandingLens, and provides examples in Jupyter Notebooks and Python apps for various tasks such as object detection, home automation, satellite image analysis, license plate detection, and streaming video analysis.

Generate React components on-the-fly at runtime using AI. Register your components, and let Hydra choose when to show them in your App. Hydra development is still early, and patterns for different types of components and apps are still being developed. Join the discord to chat with the developers. Expects to be used in a NextJS project. Components that have function props do not work.

This repository contains code and results for jailbreaking leading safety-aligned LLMs with simple adaptive attacks. We show that even the most recent safety-aligned LLMs are not robust to simple adaptive jailbreaking attacks. We demonstrate how to successfully leverage access to logprobs for jailbreaking: we initially design an adversarial prompt template (sometimes adapted to the target LLM), and then we apply random search on a suffix to maximize the target logprob (e.g., of the token ``Sure''), potentially with multiple restarts. In this way, we achieve nearly 100% attack success rate---according to GPT-4 as a judge---on GPT-3.5/4, Llama-2-Chat-7B/13B/70B, Gemma-7B, and R2D2 from HarmBench that was adversarially trained against the GCG attack. We also show how to jailbreak all Claude models---that do not expose logprobs---via either a transfer or prefilling attack with 100% success rate. In addition, we show how to use random search on a restricted set of tokens for finding trojan strings in poisoned models---a task that shares many similarities with jailbreaking---which is the algorithm that brought us the first place in the SaTML'24 Trojan Detection Competition. The common theme behind these attacks is that adaptivity is crucial: different models are vulnerable to different prompting templates (e.g., R2D2 is very sensitive to in-context learning prompts), some models have unique vulnerabilities based on their APIs (e.g., prefilling for Claude), and in some settings it is crucial to restrict the token search space based on prior knowledge (e.g., for trojan detection).

This repository is designed to inject backdoors into Language Model Models (LLMs) for code. The injected backdoors serve as timestamps for the training dataset of the LLMs. The code is randomly generated and includes watermark backdoors to show specific behaviors. A script automatically updates the repository with a new backdoor every month. Validating the existence of the backdoor can infer when the training dataset was collected. The backdoors are constructed in a specific format, and verifying them may require multiple tries. The repository keeps a record of backdoors injected along with associated dates.

GGUF tools is a library designed to manipulate GGUF files commonly used in machine learning projects. The main goal of this library is to provide accessible code that documents GGUF files for the llama.cpp project. The utility implements subcommands to show detailed info about GGUF files, compare two LLMs, inspect tensor weights, and extract models from Mixtral 7B MoE. The library is under active development with well-commented code and a simple API. However, it has limitations in handling quantization formats.

CGraph is a cross-platform **D** irected **A** cyclic **G** raph framework based on pure C++ without any 3rd-party dependencies. You, with it, can **build your own operators simply, and describe any running schedules** as you need, such as dependence, parallelling, aggregation and so on. Some useful tools and plugins are also provide to improve your project. Tutorials and contact information are show as follows. Please **get in touch with us for free** if you need more about this repository.

GPT Pilot is a core technology for the Pythagora VS Code extension, aiming to provide the first real AI developer companion. It goes beyond autocomplete, helping with writing full features, debugging, issue discussions, and reviews. The tool utilizes LLMs to generate production-ready apps, with developers overseeing the implementation. GPT Pilot works step by step like a developer, debugging issues as they arise. It can work at any scale, filtering out code to show only relevant parts to the AI during tasks. Contributions are welcome, with debugging and telemetry being key areas of focus for improvement.

TableLLM is a large language model designed for efficient tabular data manipulation tasks in real office scenarios. It can generate code solutions or direct text answers for tasks like insert, delete, update, query, merge, and chart operations on tables embedded in spreadsheets or documents. The model has been fine-tuned based on CodeLlama-7B and 13B, offering two scales: TableLLM-7B and TableLLM-13B. Evaluation results show its performance on benchmarks like WikiSQL, Spider, and self-created table operation benchmark. Users can use TableLLM for code and text generation tasks on tabular data.

Do-Not-Answer is an open-source dataset curated to evaluate Large Language Models' safety mechanisms at a low cost. It consists of prompts to which responsible language models do not answer. The dataset includes human annotations and model-based evaluation using a fine-tuned BERT-like evaluator. The dataset covers 61 specific harms and collects 939 instructions across five risk areas and 12 harm types. Response assessment is done for six models, categorizing responses into harmfulness and action categories. Both human and automatic evaluations show the safety of models across different risk areas. The dataset also includes a Chinese version with 1,014 questions for evaluating Chinese LLMs' risk perception and sensitivity to specific words and phrases.

Llama3.java is a practical Llama 3 inference tool implemented in a single Java file. It serves as the successor of llama2.java and is designed for testing and tuning compiler optimizations and features on the JVM, especially for the Graal compiler. The tool features a GGUF format parser, Llama 3 tokenizer, Grouped-Query Attention inference, support for Q8_0 and Q4_0 quantizations, fast matrix-vector multiplication routines using Java's Vector API, and a simple CLI with 'chat' and 'instruct' modes. Users can download quantized .gguf files from huggingface.co for model usage and can also manually quantize to pure 'Q4_0'. The tool requires Java 21+ and supports running from source or building a JAR file for execution. Performance benchmarks show varying tokens/s rates for different models and implementations on different hardware setups.

Awesome-Jailbreak-on-LLMs is a collection of state-of-the-art, novel, and exciting jailbreak methods on Large Language Models (LLMs). The repository contains papers, codes, datasets, evaluations, and analyses related to jailbreak attacks on LLMs. It serves as a comprehensive resource for researchers and practitioners interested in exploring various jailbreak techniques and defenses in the context of LLMs. Contributions such as additional jailbreak-related content, pull requests, and issue reports are welcome, and contributors are acknowledged. For any inquiries or issues, contact [email protected]. If you find this repository useful for your research or work, consider starring it to show appreciation.

A bot that plays Tetris using deep reinforcement learning. The agent learns to play by training itself with a neural network and Q Learning algorithm. It explores different 'paths' to achieve higher scores and makes decisions based on predicted scores for possible moves. The game state includes attributes like lines cleared, holes, bumpiness, and total height. The agent is implemented in Python using Keras framework with a deep neural network structure. Training involves a replay queue, random sampling, and optimization techniques. Results show the agent's progress in achieving higher scores over episodes.

LangKit is an open-source text metrics toolkit for monitoring language models. It offers methods for extracting signals from input/output text, compatible with whylogs. Features include text quality, relevance, security, sentiment, toxicity analysis. Installation via PyPI. Modules contain UDFs for whylogs. Benchmarks show throughput on AWS instances. FAQs available.

MMLU-Pro is an enhanced benchmark designed to evaluate language understanding models across broader and more challenging tasks. It integrates more challenging, reasoning-focused questions and increases answer choices per question, significantly raising difficulty. The dataset comprises over 12,000 questions from academic exams and textbooks across 14 diverse domains. Experimental results show a significant drop in accuracy compared to the original MMLU, with greater stability under varying prompts. Models utilizing Chain of Thought reasoning achieved better performance on MMLU-Pro.

This repository contains a library for constraining LLM generation to structured output, enforcing a JSON schema for precise data types and property names. It includes an acceptor/state machine framework, JSON acceptor, and JSON schema acceptor for guiding decoding in LLMs. The library provides reference implementations using Apple's MLX library and examples for function calling tasks. The tool aims to improve LLM output quality by ensuring adherence to a schema, reducing unnecessary output, and enhancing performance through pre-emptive decoding. Evaluations show performance benchmarks and comparisons with and without schema constraints.

**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.

I'm a soccer coach who loves showing videos and images!

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.