AI tools for synthetic user research
Related Tools:
Synthetic Users
Synthetic Users is an AI-powered user research tool that allows users to conduct user and market research without the need for recruitment. It leverages advanced AI architecture to create human-like AI participants for interviews and surveys. The tool enables users to enrich their Synthetic Users with proprietary data, conduct in-depth interviews, and run quantitative research at scale. Synthetic Users offers a multi-agent architecture that simulates real human interactions, providing valuable insights for various applications.
Nuanced
Nuanced is an AI tool that detects AI-generated images to protect the integrity and authenticity of online services. It helps platforms combat fraud, deepfakes, and inauthentic content by distinguishing between genuine human-authored artifacts and AI-generated content. Nuanced's algorithms stay ahead of the accelerating changes in AI content generation, providing a privacy-first solution that is simple to adopt and integrate. With Nuanced, businesses can focus on their core operations while ensuring the authenticity of their content.
MOSTLY AI Platform
The website offers a Synthetic Data Generation platform with the highest accuracy for free. It provides detailed information on synthetic data, data anonymization, and features a Python Client for data generation. The platform ensures privacy and security, allowing users to create fully anonymous synthetic data from original data. It supports various AI/ML use cases, self-service analytics, testing & QA, and data sharing. The platform is designed for Enterprise organizations, offering scalability, privacy by design, and the world's most accurate synthetic data.
AI or Not
AI or Not is an AI-powered tool that helps businesses and individuals detect AI-generated images and audio. It uses advanced machine learning algorithms to analyze content and determine the likelihood of AI manipulation. With AI or Not, users can protect themselves from fraud, misinformation, and other malicious activities involving AI-generated content.
Arro
Arro is an AI-powered research assistant that helps product teams collect customer insights at scale. It uses automated conversations to conduct user interviews with thousands of customers simultaneously, generating product opportunities that can be directly integrated into the product roadmap. Arro's innovative AI-led methodology combines the depth of user interviews with the speed and scale of surveys, enabling product teams to gain a comprehensive understanding of their customers' needs and preferences.
Notably
Notably is a research synthesis platform that uses AI to help researchers analyze and interpret data faster. It offers a variety of features, including a research repository, AI research, digital sticky notes, video transcription, and cluster analysis. Notably is used by companies and organizations of all sizes to conduct product research, market research, academic research, and more.
Umbrellabird
Umbrellabird is an AI-powered tool that automates the analysis and synthesis of user interview recordings. It helps product teams transform user interviews into actionable insights for faster decision-making. With features like automated document generation, intelligent key insights extraction, custom document generation, and enhanced workflow experience, Umbrellabird streamlines the process of generating valuable insights from user interviews. It ensures security and privacy of user data through encryption and offers best-in-class transcription services. Users can collaborate with their team members, share insights, and export documents easily. Umbrellabird is designed for product managers at software companies or UX researchers involved in summarizing user/customer interviews.
ChatTTS
ChatTTS is a text-to-speech tool optimized for natural, conversational scenarios. It supports both Chinese and English languages, trained on approximately 100,000 hours of data. With features like multi-language support, large data training, dialog task compatibility, open-source plans, control, security, and ease of use, ChatTTS provides high-quality and natural-sounding voice synthesis. It is designed for conversational tasks, dialogue speech generation, video introductions, educational content synthesis, and more. Users can integrate ChatTTS into their applications using provided API and SDKs for a seamless text-to-speech experience.
SDXL Turbo
SDXL Turbo is a cutting-edge text-to-image generation model that leverages Adversarial Diffusion Distillation (ADD) technology for high-quality, real-time image synthesis. Developed by Stability AI, SDXL Turbo is a distilled version of the SDXL 1.0 model, specifically trained for real-time synthesis. It excels in generating photorealistic images from text prompts in a single network evaluation, making it ideal for applications demanding speed and efficiency, such as video games, virtual reality, and instant content creation. SDXL Turbo is accessible to both professionals and hobbyists alike, with simple setup requirements and an intuitive interface. It presents unparalleled opportunities for research and development in advanced AI and image synthesis.
QuData
QuData is an AI and ML solutions provider that helps businesses enhance their value through AI/ML implementation, product design, QA, and consultancy services. They offer a range of services including ChatGPT integration, speech synthesis, speech recognition, image analysis, text analysis, predictive analytics, big data analysis, innovative research, and DevOps solutions. QuData has extensive experience in machine learning and artificial intelligence, enabling them to create high-quality solutions for specific industries, helping customers save development costs and achieve their business goals.
System Pro
System Pro is a cutting-edge platform that revolutionizes the way users search, synthesize, and contextualize scientific research, with a primary focus on health and life sciences. It offers a fast and reliable solution for accessing valuable information in the field of research. Users can create a free account to explore the platform's features and capabilities.
Stablematic
Stablematic is a web-based platform that allows users to run Stable Diffusion and other machine learning models without the need for local setup or hardware limitations. It provides a user-friendly interface, pre-installed plugins, and dedicated GPU resources for a seamless and efficient workflow. Users can generate images and videos from text prompts, merge multiple models, train custom models, and access a range of pre-trained models, including Dreambooth and CivitAi models. Stablematic also offers API access for developers and dedicated support for users to explore and utilize the capabilities of Stable Diffusion and other machine learning models.
Azoo
Azoo is an AI-powered platform that offers a wide range of services in various categories such as logistics, animal, consumer commerce, real estate, law, and finance. It provides tools for data analysis, event management, and guides for users. The platform is designed to streamline processes, enhance decision-making, and improve efficiency in different industries. Azoo is developed by Cubig Corp., a company based in Seoul, South Korea, and aims to revolutionize the way businesses operate through innovative AI solutions.
Wig Store Directory
The Wig Store Directory is an AI-powered platform that helps users discover the best wig shops of 2024. It offers a comprehensive list of wig stores, including a variety of wig types such as lace front wigs, human hair wigs, synthetic wigs, and more. Users can search for specific wig styles and submit their own wig store to enhance SEO and sales. The platform is updated daily by GPT-4o, providing users with the latest information on wig stores. Additionally, the directory features a startup list for wig store developers and offers free submissions to the directory.
Speech Studio
Speech Studio is a cloud-based speech-to-text and text-to-speech platform that enables developers to add speech capabilities to their applications. With Speech Studio, developers can easily transcribe audio and video files, generate synthetic speech, and build custom speech models. Speech Studio is a powerful tool that can be used to improve the accessibility, efficiency, and user experience of any application.
RAVATAR
RAVATAR is a comprehensive platform that seamlessly integrates various AI services, including AI Voice, AI Avatars, Conversational AI, and more. By leveraging cutting-edge artificial intelligence and no-code/low-code technologies, RAVATAR focuses on creating holistic, customized solutions designed to enhance online presence, boost user engagement, optimize operational efficiency, and significantly improve customer experience for its clients.
Synthetic Work (Re)Search Assistant
Search data on the impact of AI on jobs, productivity and operations published by Synthetic Work (https://synthetic.work)
Synthetic Biologist
A customized ChatGPT designed to excel in the field of synthetic biology, as a scientist, an engineer, and a business man
Synthetic Detectives, a text adventure game
AI powered sleuths solve crimes with synthetic precision. Let me entertain you with this interactive true crime mystery game, lovingly illustrated in the style of synthetic, AI-powered humanoid robots.
Synthetic Heists, a text adventure game
AI-powered heists: Where cunning meets calculation. Let me entertain you with this interactive heist game, lovingly illustrated in the style of synthetic, AI-powered humanoid robots.
NeuroAI Expert
Expert in synthetic neurobiology, brain organoids, and AI applications in neuroscience. Powered by Breebs (www.breebs.com)
Advanced Motor Oils & Lubricants Guru
Premier expert guide on motor oils, lubricants, developed on OpenAI.
awesome-generative-ai
A curated list of Generative AI projects, tools, artworks, and models
Recommendation-Systems-without-Explicit-ID-Features-A-Literature-Review
This repository is a collection of papers and resources related to recommendation systems, focusing on foundation models, transferable recommender systems, large language models, and multimodal recommender systems. It explores questions such as the necessity of ID embeddings, the shift from matching to generating paradigms, and the future of multimodal recommender systems. The papers cover various aspects of recommendation systems, including pretraining, user representation, dataset benchmarks, and evaluation methods. The repository aims to provide insights and advancements in the field of recommendation systems through literature reviews, surveys, and empirical studies.
LLM-for-misinformation-research
LLM-for-misinformation-research is a curated paper list of misinformation research using large language models (LLMs). The repository covers methods for detection and verification, tools for fact-checking complex claims, decision-making and explanation, claim matching, post-hoc explanation generation, and other tasks related to combating misinformation. It includes papers on fake news detection, rumor detection, fact verification, and more, showcasing the application of LLMs in various aspects of misinformation research.
OpenAdapt
OpenAdapt is an open-source software adapter between Large Multimodal Models (LMMs) and traditional desktop and web Graphical User Interfaces (GUIs). It aims to automate repetitive GUI workflows by leveraging the power of LMMs. OpenAdapt records user input and screenshots, converts them into tokenized format, and generates synthetic input via transformer model completions. It also analyzes recordings to generate task trees and replay synthetic input to complete tasks. OpenAdapt is model agnostic and generates prompts automatically by learning from human demonstration, ensuring that agents are grounded in existing processes and mitigating hallucinations. It works with all types of desktop GUIs, including virtualized and web, and is open source under the MIT license.
llms-interview-questions
This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.
slideflow
Slideflow is a deep learning library for digital pathology, offering a user-friendly interface for model development. It is designed for medical researchers and AI enthusiasts, providing an accessible platform for developing state-of-the-art pathology models. Slideflow offers customizable training pipelines, robust slide processing and stain normalization toolkit, support for weakly-supervised or strongly-supervised labels, built-in foundation models, multiple-instance learning, self-supervised learning, generative adversarial networks, explainability tools, layer activation analysis tools, uncertainty quantification, interactive user interface for model deployment, and more. It supports both PyTorch and Tensorflow, with optional support for Libvips for slide reading. Slideflow can be installed via pip, Docker container, or from source, and includes non-commercial add-ons for additional tools and pretrained models. It allows users to create projects, extract tiles from slides, train models, and provides evaluation tools like heatmaps and mosaic maps.
llm-swarm
llm-swarm is a tool designed to manage scalable open LLM inference endpoints in Slurm clusters. It allows users to generate synthetic datasets for pretraining or fine-tuning using local LLMs or Inference Endpoints on the Hugging Face Hub. The tool integrates with huggingface/text-generation-inference and vLLM to generate text at scale. It manages inference endpoint lifetime by automatically spinning up instances via `sbatch`, checking if they are created or connected, performing the generation job, and auto-terminating the inference endpoints to prevent idling. Additionally, it provides load balancing between multiple endpoints using a simple nginx docker for scalability. Users can create slurm files based on default configurations and inspect logs for further analysis. For users without a Slurm cluster, hosted inference endpoints are available for testing with usage limits based on registration status.
ichigo
Ichigo is a local real-time voice AI tool that uses an early fusion technique to extend a text-based LLM to have native 'listening' ability. It is an open research experiment with improved multiturn capabilities and the ability to refuse processing inaudible queries. The tool is designed for open data, open weight, on-device Siri-like functionality, inspired by Meta's Chameleon paper. Ichigo offers a web UI demo and Gradio web UI for users to interact with the tool. It has achieved enhanced MMLU scores, stronger context handling, advanced noise management, and improved multi-turn capabilities for a robust user experience.
bonito
Bonito is an open-source model for conditional task generation, converting unannotated text into task-specific training datasets for instruction tuning. It is a lightweight library built on top of Hugging Face `transformers` and `vllm` libraries. The tool supports various task types such as question answering, paraphrase generation, sentiment analysis, summarization, and more. Users can easily generate synthetic instruction tuning datasets using Bonito for zero-shot task adaptation.
Dataset
DL3DV-10K is a large-scale dataset of real-world scene-level videos with annotations, covering diverse scenes with different levels of reflection, transparency, and lighting. It includes 10,510 multi-view scenes with 51.2 million frames at 4k resolution, and offers benchmark videos for novel view synthesis (NVS) methods. The dataset is designed to facilitate research in deep learning-based 3D vision and provides valuable insights for future research in NVS and 3D representation learning.
NeMo
NeMo Framework is a generative AI framework built for researchers and pytorch developers working on large language models (LLMs), multimodal models (MM), automatic speech recognition (ASR), and text-to-speech synthesis (TTS). The primary objective of NeMo is to provide a scalable framework for researchers and developers from industry and academia to more easily implement and design new generative AI models by being able to leverage existing code and pretrained models.
AiTreasureBox
AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.
awesome-generative-ai-guide
This repository serves as a comprehensive hub for updates on generative AI research, interview materials, notebooks, and more. It includes monthly best GenAI papers list, interview resources, free courses, and code repositories/notebooks for developing generative AI applications. The repository is regularly updated with the latest additions to keep users informed and engaged in the field of generative AI.
Awesome-Segment-Anything
Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.
AITreasureBox
AITreasureBox is a comprehensive collection of AI tools and resources designed to simplify and accelerate the development of AI projects. It provides a wide range of pre-trained models, datasets, and utilities that can be easily integrated into various AI applications. With AITreasureBox, developers can quickly prototype, test, and deploy AI solutions without having to build everything from scratch. Whether you are working on computer vision, natural language processing, or reinforcement learning projects, AITreasureBox has something to offer for everyone. The repository is regularly updated with new tools and resources to keep up with the latest advancements in the field of artificial intelligence.
llms-tools
The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.
baal
Baal is an active learning library that supports both industrial applications and research use cases. It provides a framework for Bayesian active learning methods such as Monte-Carlo Dropout, MCDropConnect, Deep ensembles, and Semi-supervised learning. Baal helps in labeling the most uncertain items in the dataset pool to improve model performance and reduce annotation effort. The library is actively maintained by a dedicated team and has been used in various research papers for production and experimentation.