Best AI tools for< Research Ai Safety >
20 - AI tool Sites
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MIRI (Machine Intelligence Research Institute)
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.
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Athina AI
Athina AI is a platform that provides research and guides for building safe and reliable AI products. It helps thousands of AI engineers in building safer products by offering tutorials, research papers, and evaluation techniques related to large language models. The platform focuses on safety, prompt engineering, hallucinations, and evaluation of AI models.
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OpenAI
OpenAI is an artificial intelligence research laboratory consisting of the for-profit OpenAI LP and the non-profit OpenAI Inc. The organization focuses on conducting and promoting artificial intelligence research in a way that is safe and beneficial to humanity. OpenAI's mission is to ensure that artificial general intelligence benefits all of humanity. They aim to build safe and beneficial AGI, aligning with human values through research and collaboration. OpenAI is known for its cutting-edge research in natural language processing, reinforcement learning, and other AI domains.
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Center for AI Safety (CAIS)
The Center for AI Safety (CAIS) is a research and field-building nonprofit organization based in San Francisco. They conduct impactful research, advocacy projects, and provide resources to reduce societal-scale risks associated with artificial intelligence (AI). CAIS focuses on technical AI safety research, field-building projects, and offers a compute cluster for AI/ML safety projects. They aim to develop and use AI safely to benefit society, addressing inherent risks and advocating for safety standards.
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Anthropic
Anthropic is an AI safety and research company based in San Francisco. Our interdisciplinary team has experience across ML, physics, policy, and product. Together, we generate research and create reliable, beneficial AI systems.
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Frontier Model Forum
The Frontier Model Forum (FMF) is a collaborative effort among leading AI companies to advance AI safety and responsibility. The FMF brings together technical and operational expertise to identify best practices, conduct research, and support the development of AI applications that meet society's most pressing needs. The FMF's core objectives include advancing AI safety research, identifying best practices, collaborating across sectors, and helping AI meet society's greatest challenges.
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Center for AI Safety (CAIS)
The Center for AI Safety (CAIS) is a research and field-building nonprofit based in San Francisco. Their mission is to reduce societal-scale risks associated with artificial intelligence (AI) by conducting impactful research, building the field of AI safety researchers, and advocating for safety standards. They offer resources such as a compute cluster for AI/ML safety projects, a blog with in-depth examinations of AI safety topics, and a newsletter providing updates on AI safety developments. CAIS focuses on technical and conceptual research to address the risks posed by advanced AI systems.
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Inspect
Inspect is an open-source framework for large language model evaluations created by the UK AI Safety Institute. It provides built-in components for prompt engineering, tool usage, multi-turn dialog, and model graded evaluations. Users can explore various solvers, tools, scorers, datasets, and models to create advanced evaluations. Inspect supports extensions for new elicitation and scoring techniques through Python packages.
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Anthropic
Anthropic is an AI safety and research company based in San Francisco. Our interdisciplinary team has experience across ML, physics, policy, and product. Together, we generate research and create reliable, beneficial AI systems.
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OpenAI Strawberry Model
OpenAI Strawberry Model is a cutting-edge AI initiative that represents a significant leap in AI capabilities, focusing on enhancing reasoning, problem-solving, and complex task execution. It aims to improve AI's ability to handle mathematical problems, programming tasks, and deep research, including long-term planning and action. The project showcases advancements in AI safety and aims to reduce errors in AI responses by generating high-quality synthetic data for training future models. Strawberry is designed to achieve human-like reasoning and is expected to play a crucial role in the development of OpenAI's next major model, codenamed 'Orion.'
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BoodleBox
BoodleBox is a platform for group collaboration with generative AI (GenAI) tools like ChatGPT, GPT-4, and hundreds of others. It allows teams to connect multiple bots, people, and sources of knowledge in one chat to keep discussions engaging, productive, and educational. BoodleBox also provides access to over 800 specialized AI bots and offers easy team management and billing to simplify access and usage across departments, teams, and organizations.
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Google DeepMind
Google DeepMind is an AI research company that aims to develop artificial intelligence technologies to benefit the world. They focus on creating next-generation AI systems to solve complex scientific and engineering challenges. Their models like Gemini, Veo, Imagen 3, SynthID, and AlphaFold are at the forefront of AI innovation. DeepMind also emphasizes responsibility, safety, education, and career opportunities in the field of AI.
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Google DeepMind
Google DeepMind is an AI research lab that aims to build AI responsibly to benefit humanity. They work on complex challenges in AI, focusing on breakthrough innovations and publications. The lab has developed various AI models like Gemini, Project Astra, Imagen, Veo, AlphaFold, and SynthID. Google DeepMind emphasizes responsibility, safety, education, and career opportunities in the AI field. They are committed to making the AI ecosystem more representative of society and ensuring AI benefits the world.
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Tavus
Tavus is an AI tool that offers digital twin APIs for video generation and conversational video interfaces. It allows users to create immersive AI-generated video experiences using cutting-edge AI technology. Tavus provides best-in-class models like Phoenix-2 for creating realistic digital replicas with natural face movements. The platform offers rapid training, instant inference, support for 30+ languages, and built-in security features to ensure user privacy and safety. Tavus is preferred by developers and product teams for its developer-first approach, ease of integration, and exceptional customer service.
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Research Center Trustworthy Data Science and Security
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.
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Nuro
Nuro is an autonomous technology company focused on revolutionizing mobility through robotics and AI. They offer cutting-edge AI-first autonomy solutions for automotive and mobility applications, including robotaxis and autonomous vehicles. Nuro's state-of-the-art AV technology, Nuro Driver™, is designed to drive safely and naturally on all roads using groundbreaking AI-first autonomy. The company prioritizes safety in all aspects of its operations, from hardware and software to testing and systems engineering. With 8 years of autonomy innovation, Nuro aims to transform the way goods and people move by empowering fleets with AI-first autonomous capabilities.
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Prompt Engineering
Prompt Engineering is a discipline focused on developing and optimizing prompts to efficiently utilize language models (LMs) for various applications and research topics. It involves skills to understand the capabilities and limitations of large language models, improving their performance on tasks like question answering and arithmetic reasoning. Prompt engineering is essential for designing robust prompting techniques that interact with LLMs and other tools, enhancing safety and building new capabilities by augmenting LLMs with domain knowledge and external tools.
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Noometic AI
Noometic AI is an AI tool that helps users discover creators using natural language processing. It goes beyond traditional keyword searches by analyzing text, images, and videos with its proprietary RAG system. The tool aims to provide a scalable solution similar to what talent agents do intuitively, enabling users to perform creator search, content analysis, and brand safety research.
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Glog
Glog is an AI application focused on making software more secure by providing remediation advice for security vulnerabilities in software code based on context. It is capable of automatically fixing vulnerabilities, thus reducing security risks and protecting against cyber attacks. The platform utilizes machine learning and AI to enhance software security and agility, ensuring system reliability, integrity, and safety.
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Converge360
Converge360 is a comprehensive platform that offers a wide range of AI news, training, and education services to professionals in various industries such as education, enterprise IT/development, occupational health & safety, and security. With over 20 media and event brands and more than 30 years of expertise, Converge360 provides top-quality programs tailored to meet the nuanced needs of businesses. The platform utilizes in-house prediction algorithms to gain market insights and offers scalable marketing solutions with cutting-edge technology.
20 - Open Source AI Tools
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awesome-generative-ai
A curated list of Generative AI projects, tools, artworks, and models
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Learn_Prompting
Learn Prompting is a platform offering free resources, courses, and webinars to master prompt engineering and generative AI. It provides a Prompt Engineering Guide, courses on Generative AI, workshops, and the HackAPrompt competition. The platform also offers AI Red Teaming and AI Safety courses, research reports on prompting techniques, and welcomes contributions in various forms such as content suggestions, translations, artwork, and typo fixes. Users can locally develop the website using Visual Studio Code, Git, and Node.js, and run it in development mode to preview changes.
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awesome-open-ended
A curated list of open-ended learning AI resources focusing on algorithms that invent new and complex tasks endlessly, inspired by human advancements. The repository includes papers, safety considerations, surveys, perspectives, and blog posts related to open-ended AI research.
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Awesome-LLM-Safety
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.
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AwesomeResponsibleAI
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.
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awesome-artificial-intelligence-guidelines
The 'Awesome AI Guidelines' repository aims to simplify the ecosystem of guidelines, principles, codes of ethics, standards, and regulations around artificial intelligence. It provides a comprehensive collection of resources addressing ethical and societal challenges in AI systems, including high-level frameworks, principles, processes, checklists, interactive tools, industry standards initiatives, online courses, research, and industry newsletters, as well as regulations and policies from various countries. The repository serves as a valuable reference for individuals and teams designing, building, and operating AI systems to navigate the complex landscape of AI ethics and governance.
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nlp-phd-global-equality
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.
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Awesome-LLM-Eval
Awesome-LLM-Eval: a curated list of tools, benchmarks, demos, papers for Large Language Models (like ChatGPT, LLaMA, GLM, Baichuan, etc) Evaluation on Language capabilities, Knowledge, Reasoning, Fairness and Safety.
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awesome-transformer-nlp
This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.
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2025-AI-College-Jobs
2025-AI-College-Jobs is a repository containing a comprehensive list of AI/ML & Data Science jobs suitable for college students seeking internships or new graduate positions. The repository is regularly updated with positions posted within the last 120 days, featuring opportunities from various companies in the USA and internationally. The list includes positions in areas such as research scientist internships, quantitative research analyst roles, and other data science-related positions. The repository aims to provide a valuable resource for students looking to kickstart their careers in the field of artificial intelligence and machine learning.
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awesome-ai-tools
Awesome AI Tools is a curated list of popular tools and resources for artificial intelligence enthusiasts. It includes a wide range of tools such as machine learning libraries, deep learning frameworks, data visualization tools, and natural language processing resources. Whether you are a beginner or an experienced AI practitioner, this repository aims to provide you with a comprehensive collection of tools to enhance your AI projects and research. Explore the list to discover new tools, stay updated with the latest advancements in AI technology, and find the right resources to support your AI endeavors.
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llms-tools
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.
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LLMEvaluation
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.
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Awesome-GenAI-Unlearning
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.
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inspect_ai
Inspect AI is a framework developed by the UK AI Safety Institute for evaluating large language models. It offers various built-in components for prompt engineering, tool usage, multi-turn dialog, and model graded evaluations. Users can extend Inspect by adding new elicitation and scoring techniques through additional Python packages. The tool aims to provide a comprehensive solution for assessing the performance and safety of language models.
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SciCode
SciCode is a challenging benchmark designed to evaluate the capabilities of language models (LMs) in generating code for solving realistic scientific research problems. It contains 338 subproblems decomposed from 80 challenging main problems across 16 subdomains from 6 domains. The benchmark offers optional descriptions specifying useful scientific background information and scientist-annotated gold-standard solutions and test cases for evaluation. SciCode demonstrates a realistic workflow of identifying critical science concepts and facts and transforming them into computation and simulation code, aiming to help showcase LLMs' progress towards assisting scientists and contribute to the future building and evaluation of scientific AI.
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awesome-generative-ai-apis
Awesome Generative AI & LLM APIs is a curated list of useful APIs that allow developers to integrate generative models into their applications without building the models from scratch. These APIs provide an interface for generating text, images, or other content, and include pre-trained language models for various tasks. The goal of this project is to create a hub for developers to create innovative applications, enhance user experiences, and drive progress in the AI field.
20 - OpenAI Gpts
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GPT Safety Liaison
A liaison GPT for AI safety emergencies, connecting users to OpenAI experts.
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Chemistry Expert
Advanced AI for chemistry, offering innovative solutions, process optimizations, and safety assessments, powered by OpenAI.
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Töökeskkonna spetialist Eestis 2024
Sa tead kõike töökeskkonnast ja seadustest mis sellega kaasnevad
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AI Research Assistant
Designed to Provide Comprehensive Insights from the AI industry from Reputable Sources.
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AI-Driven Lab
recommends AI research these days in Japanese using AI-driven's-lab articles
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Ethical AI Insights
Expert in Ethics of Artificial Intelligence, offering comprehensive, balanced perspectives based on thorough research, with a focus on emerging trends and responsible AI implementation. Powered by Breebs (www.breebs.com)
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AI Industry Scout
AI and regulation news research assistant, finds all the AI-related industry information for and with you.
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AI Executive Order Explorer
Interact with President Biden's Executive Order on Artificial Intelligence.
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牛马审稿人-AI领域
Formal academic reviewer & writing advisor in cybersecurity & AI, detail-oriented.
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AI Product Hunter
Explore 7779 new global AI products with ease! / 7779個のAI productのDBをもとにリサーチ
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AI Chrome Extension Finder
Discover AI Chrome extensions simply by typing your requirements. Fast, customised, and readily deployable!
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AI Prompt Engineer
Tech-focused AI Prompt Engineer, providing insights on AI generation and best practices.
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AI Complexity Advancement Blueprint
Expert AI Architect for Advancing Complexities in AI Understanding