RESEARCHER A.I.

2023 AI TOOLS FOR RESEARCHERS

Scite.AI - a platform that uses AI to analyze and identify citations in scientific research papers. A researcher can use this tool to quickly identify relevant and important research papers for their own study.
Jenny.AI - a conversational AI tool that can assist researchers with tasks such as literature review, data analysis, and report writing. A researcher can use this tool to save time and increase efficiency in their research process.
HeyGPT - an AI-powered chatbot that can answer questions and provide information on a variety of topics. A researcher can use this tool to quickly find answers to their questions and get help with their research.
AutoGPT - an AI tool that can generate text content such as summaries, abstracts, and headlines. A researcher can use this tool to quickly generate summaries of research papers or to create headlines for their own research.
Agent GPT - an AI-powered assistant that can help researchers with tasks such as data analysis, literature review, and research paper writing. A researcher can use this tool to increase their productivity and streamline their research process.

MORE 2023 ARTIFICIAL INTELLIGENCE TOOLS FOR RESEARCHERS

GPT-3 - A language model that can generate human-like text, making it useful for tasks such as automated writing, content creation, and language translation. Researchers can use GPT-3 to generate summaries or paraphrase research findings, saving time and effort in the writing process.
Wordtune - A writing assistant tool that uses AI to suggest alternative wordings and edits to improve the clarity and impact of your writing. Researchers can use Wordtune to enhance the language used in their research papers, ensuring that their findings are communicated effectively to readers.
Consensus - An AI-powered platform for academic research that helps users extract insights and analyze data from scholarly articles. Researchers can use Consensus to identify key themes and trends within a given research area, enabling them to develop new hypotheses and research questions.
ChatGPT - A conversational AI platform that can assist with a wide range of tasks, including research and writing. Researchers can use ChatGPT to ask questions and receive answers, allowing them to quickly find the information they need for their research.
Scite - An AI-powered platform that uses machine learning to evaluate the reliability and quality of academic papers, providing users with a more comprehensive understanding of the research landscape. Researchers can use Scite to assess the impact and significance of research papers, helping them to make more informed decisions when selecting sources for their own work.
IBM Watson Discovery - An AI-powered search engine that helps users find relevant information and insights from large volumes of data, including academic research papers and articles. Researchers can use IBM Watson Discovery to search for articles, papers, and other resources related to their research topic, helping them to stay up-to-date on the latest research in their field.
Elicit Research Rabbit - An AI-powered search engine that helps researchers find relevant academic papers and articles based on their research question or topic. Researchers can use Elicit Research Rabbit to quickly locate the most relevant and useful research papers for their work, saving time and effort in the research process.
SciBite - An AI-powered platform that uses natural language processing to extract key concepts and entities from scientific literature. Researchers can use SciBite to identify important concepts and relationships within their research area, helping them to develop new research questions and hypotheses.
Provalis Research - An AI-powered text analytics tool that can be used to analyze and extract insights from large volumes of text data. Researchers can use Provalis Research to conduct sentiment analysis, content analysis, and other forms of text analysis on research papers, articles, and other sources, providing them with new insights and perspectives on their research area.

2023 AI TOOLS:

MORE AI TOOLS FOR RESEARCHERS:

IBM Watson: IBM Watson is an AI-powered platform that can help researchers analyze large amounts of data and generate insights. It has a natural language processing (NLP) feature that can understand and interpret human language, making it easier for researchers to interact with the data.
Google Scholar: Google Scholar is a search engine that specializes in academic literature. It uses AI to provide more accurate search results and can help researchers find relevant articles, books, and other resources.
EndNote: EndNote is a reference management tool that uses AI to help researchers organize and manage their bibliographic data. It can automatically format citations and bibliographies, saving researchers time and effort.
Mendeley: Mendeley is another reference management tool that uses AI to help researchers find and organize literature. It can suggest relevant articles based on a researcher's interests and can also analyze the text of documents to extract key information.
Grammarly: Grammarly is an AI-powered writing assistant that can help researchers improve their writing. It can check for spelling and grammar errors, suggest alternative phrasing, and even provide feedback on the clarity and effectiveness of the writing.
TensorFlow: TensorFlow is an open-source platform for building and training machine learning models. Researchers can use it to develop and test their own AI algorithms and models.
Microsoft Academic: Microsoft Academic is another search engine that specializes in academic literature. It uses AI to help researchers find relevant articles and can also provide metrics on the impact of a researcher's work.

Overall, these AI tools can help researchers save time, improve the accuracy of their work, and gain new insights from their data.

20 FREE AI TOOLS FOR RESEARCHERS:

TensorFlow - used for natural language processing, image recognition, and speech recognition. For example, it can be used to build a chatbot that can understand and respond to natural language queries.
Keras - used for building and experimenting with neural networks. For example, it can be used to build a convolutional neural network for image classification.
PyTorch - a machine learning library that is widely used for deep learning. For example, it can be used to build a neural network for object detection in images.
Caffe - a deep learning framework that is optimized for speed and efficiency. For example, it can be used to train a deep neural network to recognize faces in real-time video.
Theano - a Python library that is used for numerical computation and machine learning. For example, it can be used to build a deep neural network for sentiment analysis.
scikit-learn - a machine learning library that is used for data analysis and modeling. For example, it can be used to build a machine learning model that predicts the likelihood of a customer to churn.
Apache Mahout - a machine learning library that is used for clustering and collaborative filtering. For example, it can be used to build a recommendation system that suggests products to customers based on their past purchases.
H2O - a machine learning platform that is used for building predictive models. For example, it can be used to build a model that predicts the likelihood of a loan default.
Microsoft Cognitive Toolkit - a deep learning framework that is optimized for speed and scalability. For example, it can be used to build a neural network for speech recognition.
Apache MXNet - a deep learning framework that is designed for distributed computing. For example, it can be used to train a neural network on multiple GPUs or across multiple machines.
Torch - a scientific computing framework that is used for machine learning and computer vision. For example, it can be used to build a deep neural network for image recognition.
OpenCV - a computer vision library that is used for image and video processing. For example, it can be used to build a system that detects and tracks objects in video.
Gensim - a natural language processing library that is used for topic modeling and document similarity analysis. For example, it can be used to analyze and categorize large collections of text documents.
NLTK - a natural language processing library that is used for text classification, sentiment analysis, and named entity recognition. For example, it can be used to build a system that extracts key information from text documents.
Pandas - a Python library that is used for data manipulation and analysis. For example, it can be used to clean and preprocess data for machine learning models.
Apache Spark - a distributed computing platform that is used for big data processing and machine learning. For example, it can be used to build a machine learning model that analyzes large datasets.
RapidMiner - a data science platform that is used for data preparation, machine learning, and predictive analytics. For example, it can be used to build a model that predicts customer churn.
WEKA - a machine learning library that is used for data mining and predictive modeling. For example, it can be used to build a model that predicts the price of a stock.
Orange - a data mining and visualization platform that is used for machine learning and data analysis. For example, it can be used to build a model that predicts the likelihood of a disease based on medical test results.
ELKI - ELKI is an open source (AGPLv3) data mining software written in Java. The focus of ELKI is research in algorithms, with an emphasis on unsupervised methods in cluster analysis and outlier detection

BONUS: AI TOOLS FOR TEACHERS

https://www.unite.ai/10-best-ai-tools-for-education/