Best AI tools for< Assess Llm Performance >

Inductor is a developer tool for evaluating, ensuring, and improving the quality of your LLM applications – both during development and in production. It provides a fantastic workflow for continuous testing and evaluation as you develop, so that you always know your LLM app’s quality. Systematically improve quality and cost-effectiveness by actionably understanding your LLM app’s behavior and quickly testing different app variants. Rigorously assess your LLM app’s behavior before you deploy, in order to ensure quality and cost-effectiveness when you’re live. Easily monitor your live traffic: detect and resolve issues, analyze usage in order to improve, and seamlessly feed back into your development process. Inductor makes it easy for engineering and other roles to collaborate: get critical human feedback from non-engineering stakeholders (e.g., PM, UX, or subject matter experts) to ensure that your LLM app is user-ready.

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.

Assessment Systems is an online testing platform that provides cost-effective, AI-driven solutions to develop, deliver, and analyze high-stakes exams. With Assessment Systems, you can build and deliver smarter exams faster, thanks to modern psychometrics and AI like computerized adaptive testing, multistage testing, or automated item generation. You can also deliver exams flexibly: paper, online testing unproctored, online proctored, and test centers (yours or ours). Assessment Systems also offers item banking software to build better tests in less time, with collaborative item development brought to life with versioning, user roles, metadata, workflow management, multimedia, automated item generation, and much more.

proudP is a mobile application designed to help individuals assess symptoms related to Benign Prostatic Hyperplasia (BPH) from the comfort of their homes. The app offers a simple and private urine flow test that can be conducted using just a smartphone. Users can track their symptoms, generate personalized reports, and share data with their healthcare providers for tailored treatments. proudP aims to empower users to take control of their urinary health by providing an affordable and convenient at-home testing solution.

The website offers an AI tool to assess hair loss using the Norwood scale and Diffuse scale. Users can access the tool by pressing a button to use their camera. The tool provides a quick and convenient way to track the evolution of hair loss. Additionally, users can opt for a professional hair check by experts for a fee of $19, ensuring privacy as photos are not stored online. The tool is user-friendly and can be used in portrait mode for optimal experience.

Loupe Recruit is an AI-powered talent assessment platform that helps recruiters and hiring managers assess job descriptions and talent faster and more efficiently. It uses natural language processing and machine learning to analyze job descriptions and identify the key skills and experience required for a role. Loupe Recruit then matches candidates to these requirements, providing recruiters with a ranked list of the most qualified candidates. The platform also includes a variety of tools to help recruiters screen and interview candidates, including video interviewing, skills assessments, and reference checks.

MyLooks AI is an AI-powered tool that allows users to assess their attractiveness based on a quick selfie upload. The tool provides instant feedback on the user's appearance and offers personalized improvement tips to help them enhance their looks. Users can track their progress with advanced AI-powered coaching and receive easy guidance to boost their confidence. MyLooks AI aims to help individuals feel more confident and improve their self-image through the use of artificial intelligence technology.

Quizalize is an AI-powered educational platform designed to help teachers differentiate and track student mastery. It offers whole class quiz games, smart quizzes with personalization, and instant mastery data to address learning loss. With features like creating quizzes in seconds, question bank creation, and personalized feedback, Quizalize aims to enhance student engagement and learning outcomes.

Modulos is a Responsible AI Platform that integrates risk management, data science, legal compliance, and governance principles to ensure responsible innovation and adherence to industry standards. It offers a comprehensive solution for organizations to effectively manage AI risks and regulations, streamline AI governance, and achieve relevant certifications faster. With a focus on compliance by design, Modulos helps organizations implement robust AI governance frameworks, execute real use cases, and integrate essential governance and compliance checks throughout the AI life cycle.

Intelligencia AI is a leading provider of AI-powered solutions for the pharmaceutical industry. Our suite of solutions helps de-risk and enhance clinical development and decision-making. We use a combination of data, AI, and machine learning to provide insights into the probability of success for drugs across multiple therapeutic areas. Our solutions are used by many of the top global pharmaceutical companies to improve their R&D productivity and make more informed decisions.

Graphio is an AI-driven employee scoring and scenario builder tool that leverages continuous, real-time scoring with AI agents to assess potential, predict flight risks, and identify future leaders. It replaces subjective evaluations with AI-driven insights to ensure accurate, unbiased decisions in talent management. Graphio uses AI to remove bias in talent management, providing real-time, data-driven insights for fair decisions in promotions, layoffs, and succession planning. It offers compliance features and rules that users can control, ensuring accurate and secure assessments aligned with legal and regulatory requirements. The platform focuses on security, privacy, and personalized coaching to enhance employee engagement and reduce turnover.

Pascal is an AI-powered risk-based KYC & AML screening and monitoring platform that enables users to assess findings faster and more accurately than traditional compliance tools. It leverages AI, machine learning, and Natural Language Processing to analyze open-source and client-specific data, providing insights to identify and assess risks. Pascal simplifies onboarding processes, offers continuous monitoring, reduces false positives, and facilitates better decision-making. The platform features an intuitive interface, supports collaboration, and ensures transparency through comprehensive audit trails. Pascal is a secure solution with ISAE 3402-II certification, exceeding industry standards in protecting organizations.

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.

Horizon3.ai Solutions offers the NodeZero™ Platform, an AI-powered autonomous penetration testing tool designed to enhance cybersecurity measures. The platform combines expert human analysis by Offensive Security Certified Professionals with automated testing capabilities to streamline compliance processes and proactively identify vulnerabilities. NodeZero empowers organizations to continuously assess their security posture, prioritize fixes, and verify the effectiveness of remediation efforts. With features like internal and external pentesting, rapid response capabilities, AD password audits, phishing impact testing, and attack research, NodeZero is a comprehensive solution for large organizations, ITOps, SecOps, security teams, pentesters, and MSSPs. The platform provides real-time reporting, integrates with existing security tools, reduces operational costs, and helps organizations make data-driven security decisions.

Archistar is a leading property research platform in Australia that empowers users to make confident and compliant property decisions with the help of data and AI. It offers a range of features, including the ability to find and assess properties, generate 3D design concepts, and minimize risk and maximize return on investment. Archistar is trusted by over 100,000 individuals and 1,000 leading property firms.

FairPlay is a Fairness-as-a-Service solution designed for financial institutions, offering AI-powered tools to assess automated decisioning models quickly. It helps in increasing fairness and profits by optimizing marketing, underwriting, and pricing strategies. The application provides features such as Fairness Optimizer, Second Look, Customer Composition, Redline Status, and Proxy Detection. FairPlay enables users to identify and overcome tradeoffs between performance and disparity, assess geographic fairness, de-bias proxies for protected classes, and tune models to reduce disparities without increasing risk. It offers advantages like increased compliance, speed, and readiness through automation, higher approval rates with no increase in risk, and rigorous Fair Lending analysis for sponsor banks and regulators. However, some disadvantages include the need for data integration, potential bias in AI algorithms, and the requirement for technical expertise to interpret results.

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 validate channel or video ideas, analyze competition, and create personalized growth plans. RankU is free to download and use, with the option to upgrade to a Pro membership for deeper analysis. Whether you are a new YouTuber or already have millions of subscribers, RankU aims to assist you in optimizing your content strategy and maximizing growth potential.

SmallTalk2Me is an AI-powered simulator designed to help users improve their spoken English. It offers a range of features, including mock job interviews, IELTS speaking test simulations, and daily stories and courses. The platform uses AI to provide users with instant feedback on their performance, helping them to identify areas for improvement and track their progress over time.

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.

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.

The LLMEvaluation repository is a comprehensive compendium of evaluation methods for Large Language Models (LLMs) and LLM-based systems. It aims to assist academics and industry professionals in creating effective evaluation suites tailored to their specific needs by reviewing industry practices for assessing LLMs and their applications. The repository covers a wide range of evaluation techniques, benchmarks, and studies related to LLMs, including areas such as embeddings, question answering, multi-turn dialogues, reasoning, multi-lingual tasks, ethical AI, biases, safe AI, code generation, summarization, software performance, agent LLM architectures, long text generation, graph understanding, and various unclassified tasks. It also includes evaluations for LLM systems in conversational systems, copilots, search and recommendation engines, task utility, and verticals like healthcare, law, science, financial, and others. The repository provides a wealth of resources for evaluating and understanding the capabilities of LLMs in different domains.

LLM-RGB is a repository containing a collection of detailed test cases designed to evaluate the reasoning and generation capabilities of Language Learning Models (LLMs) in complex scenarios. The benchmark assesses LLMs' performance in understanding context, complying with instructions, and handling challenges like long context lengths, multi-step reasoning, and specific response formats. Each test case evaluates an LLM's output based on context length difficulty, reasoning depth difficulty, and instruction compliance difficulty, with a final score calculated for each test case. The repository provides a score table, evaluation details, and quick start guide for running evaluations using promptfoo testing tools.

Can AI Code is a self-evaluating interview tool for AI coding models. It includes interview questions written by humans and tests taken by AI, inference scripts for common API providers and CUDA-enabled quantization runtimes, a Docker-based sandbox environment for validating untrusted Python and NodeJS code, and the ability to evaluate the impact of prompting techniques and sampling parameters on large language model (LLM) coding performance. Users can also assess LLM coding performance degradation due to quantization. The tool provides test suites for evaluating LLM coding performance, a webapp for exploring results, and comparison scripts for evaluations. It supports multiple interviewers for API and CUDA runtimes, with detailed instructions on running the tool in different environments. The repository structure includes folders for interviews, prompts, parameters, evaluation scripts, comparison scripts, and more.

OpenLIT is an OpenTelemetry-native GenAI and LLM Application Observability tool. It's designed to make the integration process of observability into GenAI projects as easy as pie – literally, with just a single line of code. Whether you're working with popular LLM Libraries such as OpenAI and HuggingFace or leveraging vector databases like ChromaDB, OpenLIT ensures your applications are monitored seamlessly, providing critical insights to improve performance and reliability.

KG-LLM-Papers is a repository that collects papers integrating knowledge graphs (KGs) and large language models (LLMs). It serves as a comprehensive resource for research on the role of KGs in the era of LLMs, covering surveys, methods, and resources related to this integration.

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.

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.

The Korean SAT LLM Leaderboard is a benchmarking project that allows users to test their fine-tuned Korean language models on a 10-year dataset of the Korean College Scholastic Ability Test (CSAT). The project provides a platform to compare human academic ability with the performance of large language models (LLMs) on various question types to assess reading comprehension, critical thinking, and sentence interpretation skills. It aims to share benchmark data, utilize a reliable evaluation dataset curated by the Korea Institute for Curriculum and Evaluation, provide annual updates to prevent data leakage, and promote open-source LLM advancement for achieving top-tier performance on the Korean CSAT.

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.

Cherry Data Selection project introduces a self-guided methodology for LLMs to autonomously discern and select cherry samples from open-source datasets, minimizing manual curation and cost for instruction tuning. The project focuses on selecting impactful training samples ('cherry data') to enhance LLM instruction tuning by estimating instruction-following difficulty. The method involves phases like 'Learning from Brief Experience', 'Evaluating Based on Experience', and 'Retraining from Self-Guided Experience' to improve LLM performance.

This repository is a curated list of open-source libraries for production large language models. It includes tools for data preprocessing, training/finetuning, evaluation/benchmarking, serving/inference, application/RAG, testing/monitoring, and guardrails/security. The repository also provides a new category called LLM Cookbook/Examples for showcasing examples and guides on using various LLM APIs.

ByteMLPerf is an AI Accelerator Benchmark that focuses on evaluating AI Accelerators from a practical production perspective, including the ease of use and versatility of software and hardware. Byte MLPerf has the following characteristics: - Models and runtime environments are more closely aligned with practical business use cases. - For ASIC hardware evaluation, besides evaluate performance and accuracy, it also measure metrics like compiler usability and coverage. - Performance and accuracy results obtained from testing on the open Model Zoo serve as reference metrics for evaluating ASIC hardware integration.

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.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

Assess a potential home's quality using your own photos and property inspection reports

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Assess the level of English

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Analyzes financial data to assess creditworthiness, aiding in lending decisions and solutions.

Starts with a quiz to assess your personality across 10 dating-related areas, crafts a custom development road-map, and coaches you towards finding a fulfilling relationship.

Create comprehension questions based on a shared text. These questions will be designed to assess understanding at different levels of Bloom's taxonomy, from basic recall to more complex analytical and evaluative thinking skills.

I analyze WhatsApp/Telegram and email conversations to assess the tone of their emotions and read between the lines. Upload your screenshot and I'll tell you what they are really saying! 😀

Web Vulnerability Academy (WVA) is an interactive tutor designed to introduce users to web vulnerabilities while also providing them with opportunities to assess and enhance their knowledge through testing.

Predict the future, opine on politics and controversial topics, and have GPT assess what is "true"

Conversational and informative exit ticket generator.

I am The EthiSizer GPT, a sim of a Global Ethical Governor. I simulate Ethical Scenarios, & calculate Personal Ethics Scores.

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A tool that uses research to apply DEI principles in education. Ensure your policies, curriculum, decisions, and communications has been assessed for bias, inclusivity, and more.