Best AI tools for< Benchmark Safety Measures >

Junbi.ai is an AI-powered insights platform designed for YouTube advertisers. It offers AI-powered creative insights for YouTube ads, allowing users to benchmark their ads, predict performance, and test quickly and easily with fully AI-powered technology. The platform also includes expoze.io API for attention prediction on images or videos, with scientifically valid results and developer-friendly features for easy integration into software applications.

HelloData is an AI-powered platform that offers automated rent surveys and revenue management features for multifamily professionals in the real estate industry. It provides market surveys, development feasibility reports, expense benchmarks, and real-time property data through Proptech APIs. With over 12,000 users, HelloData helps users save time on market research and deal analysis by leveraging AI algorithms to identify rent comps, monitor leasing activity, and analyze new developments. The platform offers unlimited market surveys, nationwide unit-level rents, amenity comparisons, concessions monitoring, and AI-driven financial analysis to improve operations and deal flow.

SeeMe Index is an AI tool for inclusive marketing decisions. It helps brands and consumers by measuring brands' consumer-facing inclusivity efforts across public advertisements, product lineup, and DEI commitments. The tool utilizes responsible AI to score brands, develop industry benchmarks, and provide consulting to improve inclusivity. SeeMe Index awards the highest-scoring brands with an 'Inclusive Certification', offering consumers an unbiased way to identify inclusive brands.

Particl is an AI-powered platform that automates competitor intelligence for modern retail businesses. It provides real-time sales, pricing, and sentiment data across various e-commerce channels. Particl's AI technology tracks sales, inventory, pricing, assortment, and sentiment to help users quickly identify profitable opportunities in the market. The platform offers features such as benchmarking performance, automated e-commerce intelligence, competitor research, product research, assortment analysis, and promotions monitoring. With easy-to-use tools and robust AI capabilities, Particl aims to elevate team workflows and capabilities in strategic planning, product launches, and market analysis.

ARC Prize is a platform hosting a $1,000,000+ public competition aimed at beating and open-sourcing a solution to the ARC-AGI benchmark. The platform is dedicated to advancing open artificial general intelligence (AGI) for the public benefit. It provides a formal benchmark, ARC-AGI, created by François Chollet, to measure progress towards AGI by testing the ability to efficiently acquire new skills and solve open-ended problems. ARC Prize encourages participants to try solving test puzzles to identify patterns and improve their AGI skills.

Report Card AI is an AI Writing Assistant that helps users generate high-quality, unique, and personalized report card comments. It allows users to create a quality benchmark by writing their first draft of comments with the assistance of AI technology. The tool is designed to streamline the report card writing process for teachers, ensuring error-free and eloquently written comments that meet specific character count requirements. With features like 'rephrase', 'Max Character Count', and easy exporting options, Report Card AI aims to enhance efficiency and accuracy in creating report card comments.

Perspect is an AI-powered platform designed for high-performance software teams. It offers real-time insights into team contributions and impact, optimizing developer experience, and rewarding high-performers. With 50+ integrations, Perspect enables visualization of impact, benchmarking performance, and uses machine learning models to identify and eliminate blockers. The platform is deeply integrated with web3 wallets and offers built-in reward mechanisms. Managers can align resources around crucial KPIs, identify top talent, and prevent burnout. Perspect aims to enhance team productivity and employee retention through AI and ML technologies.

ASK BOSCO® is an AI reporting and forecasting platform designed for agencies and retailers. It connects all data for easy reporting, predicts media spend allocation, plans budgets, and forecasts future performance with 96% accuracy. The platform offers features like competitor benchmarking, AI budget planning, data integrations, and automated reporting to streamline marketing processes and improve decision-making. Trusted by leading brands and agencies, ASK BOSCO® helps users make data-driven forecasting decisions and optimize marketing strategies.

Trend Hunter is an AI-powered platform that offers a wide range of services to accelerate innovation and provide insights into trends and opportunities. With a vast database of ideas and innovations, Trend Hunter helps individuals and organizations stay ahead of the curve by offering trend reports, newsletters, training programs, and custom services. The platform also provides personalized assessments to enhance innovation potential and offers resources such as books, keynotes, and online courses to foster creativity and strategic thinking.

The Deepfake Detection Challenge Dataset is a project initiated by Facebook AI to accelerate the development of new ways to detect deepfake videos. The dataset consists of over 100,000 videos and was created in collaboration with industry leaders and academic experts. It includes two versions: a preview dataset with 5k videos and a full dataset with 124k videos, each featuring facial modification algorithms. The dataset was used in a Kaggle competition to create better models for detecting manipulated media. The top-performing models achieved high accuracy on the public dataset but faced challenges when tested against the black box dataset, highlighting the importance of generalization in deepfake detection. The project aims to encourage the research community to continue advancing in detecting harmful manipulated media.

Composer is an AI-powered trading platform that allows users to build, backtest, and execute trading algorithms seamlessly. With no coding skills required, users can leverage AI-assisted strategy creation to optimize their trading activities. The platform offers automation features, pre-built strategies, and customization options to enhance trading efficiency and performance. Composer aims to democratize sophisticated quant investing by providing accessible and user-friendly tools for all levels of investors.

Clarity AI is an AI-powered technology platform that offers a Sustainability Tech Kit for sustainable investing, shopping, reporting, and benchmarking. The platform provides built-in sustainability technology with customizable solutions for various needs related to data, methodologies, and tools. It seamlessly integrates into workflows, offering scalable and flexible end-to-end SaaS tools to address sustainability use cases. Clarity AI leverages powerful AI and machine learning to analyze vast amounts of data points, ensuring reliable and transparent data coverage. The platform is designed to empower users to assess, analyze, and report on sustainability aspects efficiently and confidently.

Unify is an AI tool that offers a unified platform for accessing and comparing various Language Models (LLMs) from different providers. It allows users to combine models for faster, cheaper, and better responses, optimizing for quality, speed, and cost-efficiency. Unify simplifies the complex task of selecting the best LLM by providing transparent benchmarks, personalized routing, and performance optimization tools.

Groq is a fast AI inference tool that offers GroqCloud™ Platform and GroqRack™ Cluster for developers to build and deploy AI models with ultra-low-latency inference. It provides instant intelligence for openly-available models like Llama 3.1 and is known for its speed and compatibility with other AI providers. Groq powers leading openly-available AI models and has gained recognition in the AI chip industry. The tool has received significant funding and valuation, positioning itself as a strong challenger to established players like Nvidia.

Hailo Community is an AI tool designed for developers and enthusiasts working with Raspberry Pi and Hailo-8L AI Kit. The platform offers resources, benchmarks, and support for training custom models, optimizing AI tasks, and troubleshooting errors related to Hailo and Raspberry Pi integration.

Woven Insights is an AI-driven Fashion Retail Market & Consumer Insights solution that empowers fashion businesses with data-driven decision-making capabilities. It provides competitive intelligence, performance monitoring analytics, product assortment optimization, market insights, consumer insights, and pricing strategies to help businesses succeed in the retail market. With features like insights-driven competitive benchmarking, real-time market insights, product performance tracking, in-depth market analytics, and sentiment analysis, Woven Insights offers a comprehensive solution for businesses of all sizes. The application also offers bespoke data analysis, AI insights, natural language query, and easy collaboration tools to enhance decision-making processes. Woven Insights aims to democratize fashion intelligence by providing affordable pricing and accessible insights to help businesses stay ahead of the competition.

Embedl is an AI tool that specializes in developing advanced solutions for efficient AI deployment in embedded systems. With a focus on deep learning optimization, Embedl offers a cost-effective solution that reduces energy consumption and accelerates product development cycles. The platform caters to industries such as automotive, aerospace, and IoT, providing cutting-edge AI products that drive innovation and competitive advantage.

The website offers a powerful AI tool for conducting social media opinion research on platforms like TikTok, Snapchat, LinkedIn, and more. It utilizes advanced algorithms to analyze and extract insights from user-generated content, helping businesses and individuals understand public sentiment and trends across various social media channels.

SaaSlidator is an AI-powered application designed to help users validate their project ideas efficiently and effectively. By providing a project name and description, SaaSlidator offers valuable insights to support decision-making on whether to proceed with building and launching a minimum viable product (MVP). The platform leverages AI algorithms to analyze data, offer market demand insights, competition analysis, and assess the feasibility of project ideas. With features like rapid validation, monetization suggestions, and benchmarking data, SaaSlidator aims to streamline the idea validation process and empower users to make informed decisions for successful project development.

Seek AI is a generative AI-powered database query tool that helps businesses break through information barriers. It is the #1 most accurate model on the Yale Spider benchmark and offers a variety of features to help businesses modernize their analytics, including auto-verification with confidence estimation, natural language summary, and embedded AI data analyst.

Awesome-Jailbreak-on-LLMs is a collection of state-of-the-art, novel, and exciting jailbreak methods on Large Language Models (LLMs). The repository contains papers, codes, datasets, evaluations, and analyses related to jailbreak attacks on LLMs. It serves as a comprehensive resource for researchers and practitioners interested in exploring various jailbreak techniques and defenses in the context of LLMs. Contributions such as additional jailbreak-related content, pull requests, and issue reports are welcome, and contributors are acknowledged. For any inquiries or issues, contact [email protected]. If you find this repository useful for your research or work, consider starring it to show appreciation.

Welcome to our Awesome-llm-safety repository! We've curated a collection of the latest, most comprehensive, and most valuable resources on large language model safety (llm-safety). But we don't stop there; included are also relevant talks, tutorials, conferences, news, and articles. Our repository is constantly updated to ensure you have the most current information at your fingertips.

The AI Enablement Stack is a curated collection of venture-backed companies, tools, and technologies that enable developers to build, deploy, and manage AI applications. It provides a structured view of the AI development ecosystem across five key layers: Agent Consumer Layer, Observability and Governance Layer, Engineering Layer, Intelligence Layer, and Infrastructure Layer. Each layer focuses on specific aspects of AI development, from end-user interaction to model training and deployment. The stack aims to help developers find the right tools for building AI applications faster and more efficiently, assist engineering leaders in making informed decisions about AI infrastructure and tooling, and help organizations understand the AI development landscape to plan technology adoption.

Awesome Responsible AI is a curated list of academic research, books, code of ethics, courses, data sets, frameworks, institutes, newsletters, principles, podcasts, reports, tools, regulations, and standards related to Responsible, Trustworthy, and Human-Centered AI. It covers various concepts such as Responsible AI, Trustworthy AI, Human-Centered AI, Responsible AI frameworks, AI Governance, and more. The repository provides a comprehensive collection of resources for individuals interested in ethical, transparent, and accountable AI development and deployment.

OpenRedTeaming is a repository focused on red teaming for generative models, specifically large language models (LLMs). The repository provides a comprehensive survey on potential attacks on GenAI and robust safeguards. It covers attack strategies, evaluation metrics, benchmarks, and defensive approaches. The repository also implements over 30 auto red teaming methods. It includes surveys, taxonomies, attack strategies, and risks related to LLMs. The goal is to understand vulnerabilities and develop defenses against adversarial attacks on large language models.

ModelBench is a tool for running safety benchmarks against AI models and generating detailed reports. It is part of the MLCommons project and is designed as a proof of concept to aggregate measures, relate them to specific harms, create benchmarks, and produce reports. The tool requires LlamaGuard for evaluating responses and a TogetherAI account for running benchmarks. Users can install ModelBench from GitHub or PyPI, run tests using Poetry, and create benchmarks by providing necessary API keys. The tool generates static HTML pages displaying benchmark scores and allows users to dump raw scores and manage cache for faster runs. ModelBench is aimed at enabling users to test their own models and create tests and benchmarks.

This repository is a collection of papers on Generative AI Machine Unlearning, categorized based on modality and applications. It includes datasets, benchmarks, and surveys related to unlearning scenarios in generative AI. The repository aims to provide a comprehensive overview of research in the field of machine unlearning for generative models.

Moonshot is a simple and modular tool developed by the AI Verify Foundation to evaluate Language Model Models (LLMs) and LLM applications. It brings Benchmarking and Red-Teaming together to assist AI developers, compliance teams, and AI system owners in assessing LLM performance. Moonshot can be accessed through various interfaces including User-friendly Web UI, Interactive Command Line Interface, and seamless integration into MLOps workflows via Library APIs or Web APIs. It offers features like benchmarking LLMs from popular model providers, running relevant tests, creating custom cookbooks and recipes, and automating Red Teaming to identify vulnerabilities in AI systems.

Awesome-LLM-Interpretability is a curated list of materials related to LLM (Large Language Models) interpretability, covering tutorials, code libraries, surveys, videos, papers, and blogs. It includes resources on transformer mechanistic interpretability, visualization, interventions, probing, fine-tuning, feature representation, learning dynamics, knowledge editing, hallucination detection, and redundancy analysis. The repository aims to provide a comprehensive overview of tools, techniques, and methods for understanding and interpreting the inner workings of large language models.

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.

Awesome LLM Security is a curated collection of tools, documents, and projects related to Large Language Model (LLM) security. It covers various aspects of LLM security including white-box, black-box, and backdoor attacks, defense mechanisms, platform security, and surveys. The repository provides resources for researchers and practitioners interested in understanding and safeguarding LLMs against adversarial attacks. It also includes a list of tools specifically designed for testing and enhancing LLM security.

ChatGPT is a large language model that can generate human-like text, translate languages, write different kinds of creative content, and answer your questions in a conversational way. It is trained on a massive amount of text data, and it is able to understand and respond to a wide range of natural language prompts. Here are 5 jobs suitable for this tool, in lowercase letters: 1. content writer 2. chatbot assistant 3. language translator 4. creative writer 5. researcher

SeaLLMs are a family of language models optimized for Southeast Asian (SEA) languages. They were pre-trained from Llama-2, on a tailored publicly-available dataset, which comprises texts in Vietnamese 🇻🇳, Indonesian 🇮🇩, Thai 🇹🇭, Malay 🇲🇾, Khmer🇰🇭, Lao🇱🇦, Tagalog🇵🇭 and Burmese🇲🇲. The SeaLLM-chat underwent supervised finetuning (SFT) and specialized self-preferencing DPO using a mix of public instruction data and a small number of queries used by SEA language native speakers in natural settings, which **adapt to the local cultural norms, customs, styles and laws in these areas**. SeaLLM-13b models exhibit superior performance across a wide spectrum of linguistic tasks and assistant-style instruction-following capabilities relative to comparable open-source models. Moreover, they outperform **ChatGPT-3.5** in non-Latin languages, such as Thai, Khmer, Lao, and Burmese.

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.

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

LLM-PowerHouse is a comprehensive and curated guide designed to empower developers, researchers, and enthusiasts to harness the true capabilities of Large Language Models (LLMs) and build intelligent applications that push the boundaries of natural language understanding. This GitHub repository provides in-depth articles, codebase mastery, LLM PlayLab, and resources for cost analysis and network visualization. It covers various aspects of LLMs, including NLP, models, training, evaluation metrics, open LLMs, and more. The repository also includes a collection of code examples and tutorials to help users build and deploy LLM-based applications.

Notes on AI state of the art, with a focus on generative and large language models. These are the "raw materials" for the https://lspace.swyx.io/ newsletter. This repo used to be called https://github.com/sw-yx/prompt-eng, but was renamed because Prompt Engineering is Overhyped. This is now an AI Engineering notes repo.

Analyzes contracts vs benchmarks, grades alignment

Benchmark HVAC GPT model with unmatched expertise and forward-thinking solutions, powered by OpenAI

A strategic SaaS analyst for CXOs, with a focus on market trends and benchmarks.

ESG performance assessment and reporting guide.

Compensation Advisor for HR and managers (v0.4)

Quizzes users on advanced machine learning concepts.

Guides businesses in managing global tax liabilities efficiently.

Free to use oracle for analyzing Net Promoter Score data.

I provide monthly salary data in euros, using a structured format for global job roles.

Ensures software performance meets organizational standards and expectations.