Best AI tools for< Assess Content >

The website offers content moderation and image analysis products using powerful APIs to automatically assess, filter, and moderate images, videos, and text. It provides features such as image moderation, video moderation, text moderation, AI image detection, and video anonymization. The application helps in detecting unwanted content, AI-generated images, and personal information in videos. It also offers tools to identify near-duplicates, spam, and abusive links, and prevent phishing and circumvention attempts. The platform is fast, scalable, accurate, easy to integrate, and privacy compliant, making it suitable for various industries like marketplaces, dating apps, and news platforms.

InVID is a knowledge verification platform that helps detect emerging stories and assess the reliability of newsworthy video files and content spread via social media. It provides tools and services to help users verify the authenticity of videos and identify potential misinformation.

RankU is a mobile application designed to help users grow on YouTube by leveraging the power of AI. The app provides insights, probabilistic results, and tailored recommendations to assist users in validating channel or video ideas, understanding competition, and creating a successful plan. With RankU, users can take their YouTube journey to the next level with personalized recommendations and data-driven strategies.

Plagiarism Checker is an online plagiarism detector that helps check text originality, verify authorship, trace AI-generated content, and improve writing. It scans for plagiarism to indicate similarities in any text and provides an unbiased similarity report. Plagiarism Checker offers solutions for organizations and individuals, including K-12 schools, higher education institutions, students, writers, and content creators. With advanced algorithms, unlimited text length, interactive results, downloadable reports, and strict confidentiality, Plagiarism Checker is a reliable tool for ensuring academic integrity and originality in writing.

H2O.ai is an AI platform that offers a convergence of the world's best predictive and generative AI solutions. It provides end-to-end GenAI platform for air-gapped, on-premises, or cloud VPC deployments, allowing users to own every part of the stack. With features like h2oGPTe, h2oGPT, H2O Danube3, H2O Eval Studio, and GenAI App Store, H2O.ai empowers users to customize and deploy AI models, assess performance, develop safe applications, and more. The platform is known for democratizing AI with automated machine learning and open-source distributed machine learning.

AI Image Detector is an advanced tool that allows users to upload images to determine if they were generated by artificial intelligence or humans. The tool provides a detailed percentage breakdown, showing the likelihood of AI and human creation. It offers a user-friendly interface, quick detection, and image authenticity detection using advanced AI models. Users can verify the origins of their images effortlessly without requiring technical skills.

Fifth Dimension AI is an AI application designed for real estate marketing. Ellie AI, the AI-powered assistant, helps real estate professionals with tasks such as content creation, optimization, drafting briefs, assessing pitches, ensuring brand alignment, generating content ideas, and more. The application aims to streamline marketing processes, enhance brand messaging, and stand out in a competitive market.

This AI-driven solution revolutionizes course development by streamlining and enhancing the entire process. It provides a comprehensive suite of tools that empower educators to create engaging and effective learning experiences with greater efficiency and ease. By leveraging the power of AI, this solution automates repetitive tasks, provides personalized recommendations, and offers real-time insights, enabling educators to focus on what matters most: delivering exceptional learning outcomes.

DUNNO is an AI-powered quiz platform that uses GPT-based models to generate quizzes and intellectual games. With DUNNO, you can quickly create your own quizzes based on any text, topic, or personal notes. After creating a quiz, you can either play alone or invite friends. DUNNO is suitable for various scenarios, including learning, work, and entertainment. It offers features such as quiz creation, quiz results tracking, and multiple game modes to make learning more engaging and interactive.

ROASTLI is an AI tool designed to analyze LinkedIn profiles and posts using advanced AI technology like ChatGPT. It generates a detailed analysis of the user's personality based on their LinkedIn activity. Additionally, ROASTLI is built on Wordware, an IDE for creating custom AI agents using natural language, making it suitable for various applications such as legal contract generation, marketing automation, and invoice analysis. It is ideal for cross-functional teams working on LLM applications, including non-technical members who require prompt outputs and quick iterations. ROASTLI empowers domain experts to shape LLM outputs without coding, particularly beneficial for scenarios like lawyers developing legal SaaS products. Developers can leverage ROASTLI to build sophisticated AI agents swiftly, offering features like loops, conditional logic, structured generation, and custom API integrations.

CreateMyTest is an online tool that uses artificial intelligence to automatically convert documents and YouTube videos into tests. It offers various question types, including multiple choice, true/false, matching, and fill in the blank. The platform aims to enhance studying by helping users retain knowledge through practice testing and reduce test anxiety.

Limbic is a clinical AI application designed for mental healthcare providers to save time, improve outcomes, and maximize impact. It offers a suite of tools developed by a team of therapists, physicians, and PhDs in computational psychiatry. Limbic is known for its evidence-based approach, safety focus, and commitment to patient care. The application leverages AI technology to enhance various aspects of the mental health pathway, from assessments to therapeutic content delivery. With a strong emphasis on patient safety and clinical accuracy, Limbic aims to support clinicians in meeting the rising demand for mental health services while improving patient outcomes and preventing burnout.

Breakout Learning is an AI-powered educational platform that transforms traditional case studies into engaging, multifaceted experiences. It empowers professors with AI insights into small-group discussions, enabling them to customize lectures and foster deeper student comprehension. Students benefit from rich content, peer-led discussions, and AI assessment that provides personalized feedback and tracks their progress.

PDF2Quiz is an AI-powered tool that allows users to convert PDF documents into interactive quizzes. Users can upload a PDF, specify the number of questions, select the language, and set the difficulty level to transform the PDF into an engaging quiz. The tool utilizes Optical Character Recognition (OCR) to create quizzes from PDFs with non-selectable text, making it easy for users to assess their knowledge and share quizzes with others. With multilingual quiz conversion capabilities, PDF2Quiz caters to users from various linguistic backgrounds. The tool also offers features such as reviewing scores and answers, challenging users with automatically generated multiple-choice questions, and enabling offline use by saving quizzes and answers as PDFs.

SC Training, formerly known as EdApp, is a mobile learning management system that offers a comprehensive platform for creating, delivering, and tracking training courses. The application provides features such as admin control, content creation tools, analytics tracking, AI course generation, microlearning courses, gamification elements, and support for various industries. SC Training aims to deliver efficient and engaging training experiences to users, with a focus on bite-sized learning and accessibility across devices. The platform also offers course libraries, practical assessments, rapid course refresh, and group training options. Users can customize courses, integrate with existing tools, and access a range of resources through the help center and blog.

BS Detector is an AI tool designed to help users determine the credibility of information by analyzing text or images for misleading or false content. Users can input a link, upload a screenshot, or paste text to receive a BS (Bullshit) rating. The tool leverages AI algorithms to assess the accuracy and truthfulness of the provided content, offering users a quick and efficient way to identify potentially deceptive information.

Grantable is an AI grant writing tool designed to assist grant professionals in drafting high-quality grant proposals efficiently. It offers a Smart Content Library, solutions for various sectors like nonprofits, agencies, academic institutions, government, and businesses. Grantable helps users secure non-dilutive funding by providing AI assistance in writing, organizing source material, and navigating application materials. The tool aims to streamline the grant writing process, save time, and improve the quality of proposals.

Khanmigo is an AI-powered teaching assistant and tutor developed by Khan Academy, a trusted education nonprofit. It offers personalized learning experiences for teachers, learners, and parents across various subjects such as math, science, coding, and humanities. Khanmigo aims to revolutionize education by providing on-demand support, engaging content, and ethical design focused on safety and learning. With features tailored for educators and students, Khanmigo simplifies workflows, challenges critical thinking, and guides learners to discover answers independently.

SC Training, formerly known as EdApp, is a mobile learning management system that offers a wide range of features to enhance the training experience for both administrators and learners. The platform provides tools for creating, managing, and tracking training courses, with a strong focus on microlearning and gamification. SC Training aims to deliver bite-sized, engaging content that can be accessed anytime, anywhere, on any device. The application also incorporates AI technology to streamline course creation and improve the learning experience. With a diverse course library, practical assessments, and group training capabilities, SC Training is designed to help organizations deliver effective and efficient training programs.

AI Tutor Pro is a cutting-edge AI-powered personal digital assistant developed by Contact North | Contact Nord. It offers a wide range of educational content in various subjects, allowing users to learn anytime, anywhere, and in multiple languages for free. The application helps users assess and enhance their knowledge and skills on diverse topics, ensuring privacy and confidentiality. Contact North | Contact Nord, a not-for-profit corporation established in 1986, is behind this innovative tool.

ChatGPT Queue Prompts is a collection of prompt chains designed to enhance interactions with large language models like ChatGPT. These prompt chains help build context for the AI before performing specific tasks, improving performance. Users can copy and paste prompt chains into the ChatGPT Queue extension to process prompts in sequence. The repository includes example prompt chains for tasks like conducting AI company research, building SEO optimized blog posts, creating courses, revising resumes, enriching leads for CRM, personal finance document creation, workout and nutrition plans, marketing plans, and more.

llm_benchmarks is a collection of benchmarks and datasets for evaluating Large Language Models (LLMs). It includes various tasks and datasets to assess LLMs' knowledge, reasoning, language understanding, and conversational abilities. The repository aims to provide comprehensive evaluation resources for LLMs across different domains and applications, such as education, healthcare, content moderation, coding, and conversational AI. Researchers and developers can leverage these benchmarks to test and improve the performance of LLMs in various real-world scenarios.

This repository contains a collection of papers and resources related to Large Language Models (LLMs), including their applications in various domains such as text generation, translation, question answering, and dialogue systems. The repository also includes discussions on the ethical and societal implications of LLMs. **Description** This repository is a collection of papers and resources related to Large Language Models (LLMs). LLMs are a type of artificial intelligence (AI) that can understand and generate human-like text. They have a wide range of applications, including text generation, translation, question answering, and dialogue systems. **For Jobs** - **Content Writer** - **Copywriter** - **Editor** - **Journalist** - **Marketer** **AI Keywords** - **Large Language Models** - **Natural Language Processing** - **Machine Learning** - **Artificial Intelligence** - **Deep Learning** **For Tasks** - **Generate text** - **Translate text** - **Answer questions** - **Engage in dialogue** - **Summarize text**

The Prompt Fuzzer is an open-source tool that helps you assess the security of your GenAI application's system prompt against various dynamic LLM-based attacks. It provides a security evaluation based on the outcome of these attack simulations, enabling you to strengthen your system prompt as needed. The Prompt Fuzzer dynamically tailors its tests to your application's unique configuration and domain. The Fuzzer also includes a Playground chat interface, giving you the chance to iteratively improve your system prompt, hardening it against a wide spectrum of generative AI attacks.

This repository contains scripts and tools for evaluating a chat app that uses the RAG architecture. It provides parameters to assess the quality and style of answers generated by the chat app, including system prompt, search parameters, and GPT model parameters. The tools facilitate running evaluations, with examples of evaluations on a sample chat app. The repo also offers guidance on cost estimation, setting up the project, deploying a GPT-4 model, generating ground truth data, running evaluations, and measuring the app's ability to say 'I don't know'. Users can customize evaluations, view results, and compare runs using provided tools.

OpenShield is a firewall designed for AI models to protect against various attacks such as prompt injection, insecure output handling, training data poisoning, model denial of service, supply chain vulnerabilities, sensitive information disclosure, insecure plugin design, excessive agency granting, overreliance, and model theft. It provides rate limiting, content filtering, and keyword filtering for AI models. The tool acts as a transparent proxy between AI models and clients, allowing users to set custom rate limits for OpenAI endpoints and perform tokenizer calculations for OpenAI models. OpenShield also supports Python and LLM based rules, with upcoming features including rate limiting per user and model, prompts manager, content filtering, keyword filtering based on LLM/Vector models, OpenMeter integration, and VectorDB integration. The tool requires an OpenAI API key, Postgres, and Redis for operation.

The Amazon Transcribe Live Call Analytics (LCA) with Agent Assist Sample Solution is designed to help contact centers assess and optimize caller experiences in real time. It leverages Amazon machine learning services like Amazon Transcribe, Amazon Comprehend, and Amazon SageMaker to transcribe and extract insights from contact center audio. The solution provides real-time supervisor and agent assist features, integrates with existing contact centers, and offers a scalable, cost-effective approach to improve customer interactions. The end-to-end architecture includes features like live call transcription, call summarization, AI-powered agent assistance, and real-time analytics. The solution is event-driven, ensuring low latency and seamless processing flow from ingested speech to live webpage updates.

MathVerse is an all-around visual math benchmark designed to evaluate the capabilities of Multi-modal Large Language Models (MLLMs) in visual math problem-solving. It collects high-quality math problems with diagrams to assess how well MLLMs can understand visual diagrams for mathematical reasoning. The benchmark includes 2,612 problems transformed into six versions each, contributing to 15K test samples. It also introduces a Chain-of-Thought (CoT) Evaluation strategy for fine-grained assessment of output answers.

This repository focuses on utilizing generative AI to bridge the gap between natural language questions and SQL queries, aiming to improve data consumption in enterprise data warehouses. It addresses challenges in SQL query generation, such as foreign key relationships and table joins, and highlights the importance of accuracy metrics like Execution Accuracy (EX) and Exact Set Match Accuracy (EM). The workshop content covers advanced prompt engineering, Retrieval Augmented Generation (RAG), fine-tuning models, and security measures against prompt and SQL injections.

TrustLLM is a comprehensive study of trustworthiness in LLMs, including principles for different dimensions of trustworthiness, established benchmark, evaluation, and analysis of trustworthiness for mainstream LLMs, and discussion of open challenges and future directions. Specifically, we first propose a set of principles for trustworthy LLMs that span eight different dimensions. Based on these principles, we further establish a benchmark across six dimensions including truthfulness, safety, fairness, robustness, privacy, and machine ethics. We then present a study evaluating 16 mainstream LLMs in TrustLLM, consisting of over 30 datasets. The document explains how to use the trustllm python package to help you assess the performance of your LLM in trustworthiness more quickly. For more details about TrustLLM, please refer to project website.

STaRK is a large-scale semi-structure retrieval benchmark on Textual and Relational Knowledge Bases. It provides natural-sounding and practical queries crafted to incorporate rich relational information and complex textual properties, closely mirroring real-life scenarios. The benchmark aims to assess how effectively large language models can handle the interplay between textual and relational requirements in queries, using three diverse knowledge bases constructed from public sources.

DevQualityEval is an evaluation benchmark and framework designed to compare and improve the quality of code generation of Language Model Models (LLMs). It provides developers with a standardized benchmark to enhance real-world usage in software development and offers users metrics and comparisons to assess the usefulness of LLMs for their tasks. The tool evaluates LLMs' performance in solving software development tasks and measures the quality of their results through a point-based system. Users can run specific tasks, such as test generation, across different programming languages to evaluate LLMs' language understanding and code generation capabilities.

Raga LLM Hub is a comprehensive evaluation toolkit for Language and Learning Models (LLMs) with over 100 meticulously designed metrics. It allows developers and organizations to evaluate and compare LLMs effectively, establishing guardrails for LLMs and Retrieval Augmented Generation (RAG) applications. The platform assesses aspects like Relevance & Understanding, Content Quality, Hallucination, Safety & Bias, Context Relevance, Guardrails, and Vulnerability scanning, along with Metric-Based Tests for quantitative analysis. It helps teams identify and fix issues throughout the LLM lifecycle, revolutionizing reliability and trustworthiness.

BABILong is a generative benchmark designed to evaluate the performance of NLP models in processing long documents with distributed facts. It consists of 20 tasks that simulate interactions between characters and objects in various locations, requiring models to distinguish important information from irrelevant details. The tasks vary in complexity and reasoning aspects, with test samples potentially containing millions of tokens. The benchmark aims to challenge and assess the capabilities of Large Language Models (LLMs) in handling complex, long-context information.

Contoso Chat is a Python sample demonstrating how to build, evaluate, and deploy a retail copilot application with Azure AI Studio using Promptflow with Prompty assets. The sample implements a Retrieval Augmented Generation approach to answer customer queries based on the company's product catalog and customer purchase history. It utilizes Azure AI Search, Azure Cosmos DB, Azure OpenAI, text-embeddings-ada-002, and GPT models for vectorizing user queries, AI-assisted evaluation, and generating chat responses. By exploring this sample, users can learn to build a retail copilot application, define prompts using Prompty, design, run & evaluate a copilot using Promptflow, provision and deploy the solution to Azure using the Azure Developer CLI, and understand Responsible AI practices for evaluation and content safety.

LangCheck is a Python library that provides a suite of metrics and tools for evaluating the quality of text generated by large language models (LLMs). It includes metrics for evaluating text fluency, sentiment, toxicity, factual consistency, and more. LangCheck also provides tools for visualizing metrics, augmenting data, and writing unit tests for LLM applications. With LangCheck, you can quickly and easily assess the quality of LLM-generated text and identify areas for improvement.

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.

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.

Awesome-LLM-in-Social-Science is a repository that compiles papers evaluating Large Language Models (LLMs) from a social science perspective. It includes papers on evaluating, aligning, and simulating LLMs, as well as enhancing tools in social science research. The repository categorizes papers based on their focus on attitudes, opinions, values, personality, morality, and more. It aims to contribute to discussions on the potential and challenges of using LLMs in social science research.

Qwen is a series of large language models developed by Alibaba DAMO Academy. It outperforms the baseline models of similar model sizes on a series of benchmark datasets, e.g., MMLU, C-Eval, GSM8K, MATH, HumanEval, MBPP, BBH, etc., which evaluate the models’ capabilities on natural language understanding, mathematic problem solving, coding, etc. Qwen models outperform the baseline models of similar model sizes on a series of benchmark datasets, e.g., MMLU, C-Eval, GSM8K, MATH, HumanEval, MBPP, BBH, etc., which evaluate the models’ capabilities on natural language understanding, mathematic problem solving, coding, etc. Qwen-72B achieves better performance than LLaMA2-70B on all tasks and outperforms GPT-3.5 on 7 out of 10 tasks.

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