Best AI tools for< Research Pan >

PandaRocket is an AI-powered suite designed to support various eCommerce business models. It offers a range of tools for product research, content creation, and store management. With features like market analysis, customer segmentation, and predictive intelligence, PandaRocket helps users make data-driven decisions to optimize their online stores and maximize profits.

Poll the People is an AI-powered consumer research platform that offers 10X more effective surveys powered by ChatGPT. With a human panel of 500,000+ participants, the platform provides insights on brand testing, concept testing, logo testing, content testing, and more. By leveraging AI technology, users can make data-driven decisions, achieve faster insights, and access deep consumer understanding for better decision-making. The platform automates survey analysis, saving time and resources, and offers unbiased and accurate market insights. Poll the People is trusted by top brands worldwide for its efficiency and reliability in consumer research.

Marvin is an AI research software that serves as the perfect AI research assistant for qualitative research. It automates tedious parts of qualitative research, allowing users to analyze hours of research in minutes. Marvin helps in centralizing, searching, and sharing user research data, making it easily accessible for the whole team. With AI-powered enhancements, Marvin assists in consolidating user insights, finding patterns, and backing decisions with evidence. The tool streamlines the research journey by managing user interview panels, recruiting participants effectively, and providing features like automatic transcripts, video clips, and privacy filters for compliance. Marvin offers different pricing plans suitable for small teams, startups, companies with multiple teams, and large organizations.

Transkrip.com is an AI-powered transcription application that converts audio and video files into text with high accuracy. It is the top transcription application for Bahasa Indonesia, trusted by over 200,000 users. The platform offers fast and affordable transcription services, making it easy for professionals and students to transcribe audio and video recordings. With a focus on accuracy and speed, Transkrip.com supports large file sizes and long durations, providing users with reliable transcriptions in multiple languages. The application is loved by many loyal users for its convenience and effectiveness in transcribing various types of content.

ClearSeas.AI is an AI-powered market research visualization dashboard that leverages advanced AI technologies to interpret complex datasets, delivering intuitive and visually compelling insights. The platform offers services such as expert survey design, efficient survey deployment, B2B panel access, and full-service project management. ClearSeas.AI prioritizes data security by employing stringent protocols, advanced encryption technologies, and document protection measures. The platform does not use customer data for AI training, ensuring data privacy and confidentiality. ClearSeas.AI aims to illuminate insights with the power of AI, empowering users to stay ahead of market trends and make informed strategic decisions.

MachineCon 2024 is an exclusive gathering of analytics and artificial intelligence leaders, organized by AIM Research. The conference focuses on exploring cutting-edge AI technologies and innovative analytics solutions that are shaping the future of various industries. It provides a platform for top analytics leaders to learn, network, and do business, emphasizing the transformative potential of data and AI in driving competitive advantage and business transformation.

Probz is an AI-powered end-to-end Insights Platform that helps brands gather detailed insights on their ideas through Quant, Qual, and Video Research. With a panel of over 10 million users worldwide, Probz enables brands to supercharge their decision-making process, understand customer behavior, collect feedback for product development, optimize marketing strategies, explore new initiatives, and obtain feedback on technology preferences and designs. The platform offers AI-generated hypotheses, customizable surveys, and real-user tests to enhance sales, customer satisfaction, and brand loyalty.

Google Research is a leading research organization focusing on advancing science and artificial intelligence. They conduct research in various domains such as AI/ML foundations, responsible human-centric technology, science & societal impact, computing paradigms, and algorithms & optimization. Google Research aims to create an environment for diverse research across different time scales and levels of risk, driving advancements in computer science through fundamental and applied research. They publish hundreds of research papers annually, collaborate with the academic community, and work on projects that impact technology used by billions of people worldwide.

Google Research is a team of scientists and engineers working on a wide range of topics in computer science, including artificial intelligence, machine learning, and quantum computing. Our mission is to advance the state of the art in these fields and to develop new technologies that can benefit society. We publish hundreds of research papers each year and collaborate with researchers from around the world. Our work has led to the development of many new products and services, including Google Search, Google Translate, and Google Maps.

The Google Research Blog is a platform for researchers at Google to share their latest work in artificial intelligence, machine learning, and other related fields. The blog covers a wide range of topics, from theoretical research to practical applications. The goal of the blog is to provide a forum for researchers to share their ideas and findings, and to foster collaboration between researchers at Google and around the world.

The Research Center Trustworthy Data Science and Security is a hub for interdisciplinary research focusing on building trust in artificial intelligence, machine learning, and cyber security. The center aims to develop trustworthy intelligent systems through research in trustworthy data analytics, explainable machine learning, and privacy-aware algorithms. By addressing the intersection of technological progress and social acceptance, the center seeks to enable private citizens to understand and trust technology in safety-critical applications.

Research Studio is a next-level UX research tool that helps you streamline your user research with AI-enhanced analysis. Whether you're a freelance UX designer, user researcher, or agency, Research Studio can help you get the insights you need to make better decisions about your products and services.

HelpMoji Research is an AI-powered product research assistant that helps users conduct internet research without being tracked by digital advertising giants. It allows users to search for product specifications, compare products, and focus on research without being influenced by targeted ads. The tool works on all devices and browsers, providing a seamless research experience.

RapidAI Research Institute is an academic institution under the RapidAI open-source organization, a non-enterprise academic institution. It serves as a platform for academic research and collaboration, providing opportunities for aspiring researchers to publish papers and engage in scholarly activities. The institute offers mentorship programs and benefits for members, including access to resources such as internet connectivity, GPU configurations, and storage space. The management team consists of esteemed professionals in the field, ensuring a conducive environment for academic growth and development.

MIRI (Machine Intelligence Research Institute) is a non-profit research organization dedicated to ensuring that artificial intelligence has a positive impact on humanity. MIRI conducts foundational mathematical research on topics such as decision theory, game theory, and reinforcement learning, with the goal of developing new insights into how to build safe and beneficial AI systems.

Branded Research, acquired by Dynata, provides access to AI-verified audience insights. It offers a range of research methods, including surveys, webcam studies, and emotional AI. With its advanced algorithms and extensive profiling, Branded helps businesses connect with their target audience and gain valuable insights to drive innovation. The company serves various industries, including tech, consumer goods, healthcare, and research agencies.

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.

AIM Research is a leading platform providing insights and analysis on the Artificial Intelligence industry. The website offers a comprehensive range of resources, including research reports, event coverage, news articles, and expert opinions. AIM Research focuses on highlighting the latest trends, innovations, and key players in the AI sector, catering to professionals, researchers, and enthusiasts seeking in-depth knowledge and understanding of AI technologies and applications.

Opus Research is a leading provider of market research, consulting, and advisory services to the global digital communications and collaboration sectors. The company's research focuses on the convergence of emerging technologies, including artificial intelligence (AI), machine learning (ML), and natural language processing (NLP), with the communications and collaboration industries.

Cartesia Sonic Team Blog Research Playground is an AI application that offers real-time multimodal intelligence for every device. The application aims to build the next generation of AI by providing ubiquitous, interactive intelligence that can run on any device. It features the fastest, ultra-realistic generative voice API and is backed by research on simple linear attention language models and state-space models. The founding team, who met at the Stanford AI Lab, has invented State Space Models (SSMs) and scaled it up to achieve state-of-the-art results in various modalities such as text, audio, video, images, and time-series data.

VideoLLaMA 2 is a project focused on advancing spatial-temporal modeling and audio understanding in video-LLMs. It provides tools for multi-choice video QA, open-ended video QA, and video captioning. The project offers model zoo with different configurations for visual encoder and language decoder. It includes training and evaluation guides, as well as inference capabilities for video and image processing. The project also features a demo setup for running a video-based Large Language Model web demonstration.

This repository contains code released by Google Research. All datasets in this repository are released under the CC BY 4.0 International license, which can be found here: https://creativecommons.org/licenses/by/4.0/legalcode. All source files in this repository are released under the Apache 2.0 license, the text of which can be found in the LICENSE file.

PandasAI is a Python library that makes it easy to ask questions to your data in natural language. It helps you to explore, clean, and analyze your data using generative AI.

This repository is a collection of research lectures and experience sharing posts from frontline researchers in the field of AI. It aims to help individuals upgrade their research skills and knowledge through insightful talks and experiences shared by experts. The content covers various topics such as evaluating research papers, choosing research directions, research methodologies, and tips for writing high-quality scientific papers. The repository also includes discussions on academic career paths, research ethics, and the emotional aspects of research work. Overall, it serves as a valuable resource for individuals interested in advancing their research capabilities in the field of AI.

Aria is a Zotero plugin that serves as an AI Research Assistant powered by Large Language Models (LLMs). It offers features like drag-and-drop referencing, autocompletion for creators and tags, visual analysis using GPT-4 Vision, and saving chats as notes and annotations. Aria requires the OpenAI GPT-4 model family and provides a configurable interface through preferences. Users can install Aria by downloading the latest release from GitHub and activating it in Zotero. The tool allows users to interact with Zotero library through conversational AI and probabilistic models, with the ability to troubleshoot errors and provide feedback for improvement.

Jupyter Quant is a dockerized environment tailored for quantitative research, equipped with essential tools like statsmodels, pymc, arch, py_vollib, zipline-reloaded, PyPortfolioOpt, numpy, pandas, sci-py, scikit-learn, yellowbricks, shap, optuna, ib_insync, Cython, Numba, bottleneck, numexpr, jedi language server, jupyterlab-lsp, black, isort, and more. It does not include conda/mamba and relies on pip for package installation. The image is optimized for size, includes common command line utilities, supports apt cache, and allows for the installation of additional packages. It is designed for ephemeral containers, ensuring data persistence, and offers volumes for data, configuration, and notebooks. Common tasks include setting up the server, managing configurations, setting passwords, listing installed packages, passing parameters to jupyter-lab, running commands in the container, building wheels outside the container, installing dotfiles and SSH keys, and creating SSH tunnels.

The 'machine-learning-research' repository is a comprehensive collection of resources related to mathematics, machine learning, deep learning, artificial intelligence, data science, and various scientific fields. It includes materials such as courses, tutorials, books, podcasts, communities, online courses, papers, and dissertations. The repository covers topics ranging from fundamental math skills to advanced machine learning concepts, with a focus on applications in healthcare, genetics, computational biology, precision health, and AI in science. It serves as a valuable resource for individuals interested in learning and researching in the fields of machine learning and related disciplines.

Jupyter Quant is a dockerized environment tailored for quantitative research, equipped with essential tools like statsmodels, pymc, arch, py_vollib, zipline-reloaded, PyPortfolioOpt, numpy, pandas, sci-py, scikit-learn, yellowbricks, shap, optuna, and more. It provides Interactive Broker connectivity via ib_async and includes major Python packages for statistical and time series analysis. The image is optimized for size, includes jedi language server, jupyterlab-lsp, and common command line utilities. Users can install new packages with sudo, leverage apt cache, and bring their own dot files and SSH keys. The tool is designed for ephemeral containers, ensuring data persistence and flexibility for quantitative analysis tasks.

A repository sharing the panorama of the methodology literature on Transformer architecture upgrades in Large Language Models for handling extensive context windows, with real-time updating the newest published works. It includes a survey on advancing Transformer architecture in long-context large language models, flash-ReRoPE implementation, latest news on data engineering, lightning attention, Kimi AI assistant, chatglm-6b-128k, gpt-4-turbo-preview, benchmarks like InfiniteBench and LongBench, long-LLMs-evals for evaluating methods for enhancing long-context capabilities, and LLMs-learning for learning technologies and applicated tasks about Large Language Models.

Flower is a framework for building federated learning systems. It is designed to be customizable, extensible, framework-agnostic, and understandable. Flower can be used with any machine learning framework, for example, PyTorch, TensorFlow, Hugging Face Transformers, PyTorch Lightning, scikit-learn, JAX, TFLite, MONAI, fastai, MLX, XGBoost, Pandas for federated analytics, or even raw NumPy for users who enjoy computing gradients by hand.

Prompt4ReasoningPapers is a repository dedicated to reasoning with language model prompting. It provides a comprehensive survey of cutting-edge research on reasoning abilities with language models. The repository includes papers, methods, analysis, resources, and tools related to reasoning tasks. It aims to support various real-world applications such as medical diagnosis, negotiation, etc.

This repository contains the source code for the SIGIR 2023 paper 'Where to Go Next for Recommender Systems? ID- vs. Modality-based Recommender Models Revisited'. It provides resources for evaluating foundation, transferable, multi-modal, and LLM recommendation models, along with datasets, pre-trained models, and training strategies for IDRec and MoRec using in-batch debiased cross-entropy loss. The repository also offers large-scale datasets, code for SASRec with in-batch debias cross-entropy loss, and information on joining the lab for research opportunities.

This repository aims to promote global equality for individuals pursuing a PhD in NLP by providing resources and information on various aspects of the academic journey. It covers topics such as applying for a PhD, getting research opportunities, preparing for the job market, and succeeding in academia. The repository is actively updated and includes contributions from experts in the field.

Awesome-Colorful-LLM is a meticulously assembled anthology of vibrant multimodal research focusing on advancements propelled by large language models (LLMs) in domains such as Vision, Audio, Agent, Robotics, and Fundamental Sciences like Mathematics. The repository contains curated collections of works, datasets, benchmarks, projects, and tools related to LLMs and multimodal learning. It serves as a comprehensive resource for researchers and practitioners interested in exploring the intersection of language models and various modalities for tasks like image understanding, video pretraining, 3D modeling, document understanding, audio analysis, agent learning, robotic applications, and mathematical research.

The `Call-for-Reviewers` repository aims to collect the latest 'call for reviewers' links from various top CS/ML/AI conferences/journals. It provides an opportunity for individuals in the computer/ machine learning/ artificial intelligence fields to gain review experience for applying for NIW/H1B/EB1 or enhancing their CV. The repository helps users stay updated with the latest research trends and engage with the academic community.

This repository contains a collection of research papers related to watermarking techniques for text and images, specifically focusing on large language models (LLMs). The papers cover various aspects of watermarking LLM-generated content, including robustness, statistical understanding, topic-based watermarks, quality-detection trade-offs, dual watermarks, watermark collision, and more. Researchers have explored different methods and frameworks for watermarking LLMs to protect intellectual property, detect machine-generated text, improve generation quality, and evaluate watermarking techniques. The repository serves as a valuable resource for those interested in the field of watermarking for LLMs.

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.

This repository tracks the latest research on machine unlearning in large language models (LLMs). It offers a comprehensive list of papers, datasets, and resources relevant to the topic.

Cyclops is a toolkit for facilitating research and deployment of ML models for healthcare. It provides a few high-level APIs namely: data - Create datasets for training, inference and evaluation. We use the popular 🤗 datasets to efficiently load and slice different modalities of data models - Use common model implementations using scikit-learn and PyTorch tasks - Use common ML task formulations such as binary classification or multi-label classification on tabular, time-series and image data evaluate - Evaluate models on clinical prediction tasks monitor - Detect dataset shift relevant for clinical use cases report - Create model report cards for clinical ML models

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BNB data analyzer and predictor for PancakeSwap

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General Information Gatherer

Explains Arxiv papers with examples, analogies, and direct PDF links.

Your AI research aide for the latest in ML.

I improve marketing effectiveness by designing stunning research-led assets in a flash!

Your go-to source for well-researched information!

Spot emerging trends in the latest social science research ( (also see, just "Research Radar" for all disciplines))

Teaches and analyzes research methods with in-depth, academic insights.

Expert AI research question assistant.

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Designed to Provide Comprehensive Insights from the AI industry from Reputable Sources.

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Research Proposal Assistant Pro is designed to provide tailored assistance in research writing.

Upon uploading a research paper, I provide a concise section wise analysis covering Abstract, Lit Review, Findings, Methodology, and Conclusion. I also critique the work, highlight its strengths, and answer any open questions from my Knowledge base of Open source materials.

Expert in detailed, interactive, and multilingual research analysis.

Find and summarize recent papers in biology, chemistry, and biomedical sciences.

Your AI research assistant, for turning a problem into a research, developing research questions, generating plans, analyzing data and improving research workflows for project success

An assistant for all you research needs