Best AI tools for< Conduct Ai Safety Research >

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.

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.

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.

The O.XYZ website is a platform dedicated to decentralized super intelligence, governance, research, and innovation for the O Ecosystem. It focuses on cutting-edge AI research, community-driven allocation, and treasury management. The platform aims to empower the O Ecosystem through decentralization and responsible, safe, and ethical development of Super AI.

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.

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.

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.

Modulate is a voice intelligence tool that provides proactive voice chat moderation solutions for various platforms, including gaming, delivery services, and social platforms. It uses advanced AI technology to detect and prevent harmful behaviors, ensuring a safer and more positive user experience. Modulate helps organizations comply with regulations, enhance user safety, and improve community interactions through its customizable and intelligent moderation tools.

Her Trip Planner is an AI-powered platform designed exclusively for women adventurers to streamline trip planning, curate personalized itineraries, and conduct in-depth safety reviews of destinations. The platform aims to empower women to craft memorable journeys with peace of mind by saving time on planning and addressing safety concerns.

Her Trip Planner is an AI-powered platform designed for women adventurers to streamline trip planning, curate personalized itineraries, and conduct safety reviews of destinations. The platform aims to empower women travelers to craft memorable journeys with peace of mind by providing tailored travel plans and safety assessments based on individual profiles.

PullRequest is an AI-powered code review as a service platform that offers on-demand code review from expert engineers enhanced by AI. It supports all languages and frameworks, helping development teams of any size ship better, more secure code faster through AI-assisted code reviews. PullRequest integrates with popular version control platforms like GitHub, GitLab, Bitbucket, and Azure DevOps, providing valuable knowledge sharing with senior engineers to improve code quality and security. The platform ensures code safety and security by adhering to best practices, strict procedures, and employing reviewers based in the US, the UK, or Canada.

Matrix AI Consulting Services is an expert AI consultancy firm based in New Zealand, offering bespoke AI consulting services to empower businesses and government entities to embrace responsible AI. With over 24 years of experience in transformative technology, the consultancy provides services ranging from AI business strategy development to seamless integration, change management, training workshops, and governance frameworks. Matrix AI Consulting Services aims to help organizations unlock the full potential of AI, enhance productivity, streamline operations, and gain a competitive edge through the strategic implementation of AI technologies.

Zavata is an AI tool designed for automating the hiring process through AI interviews. It offers features such as automated scheduling, AI-powered interviews, real-time feedback, and fair assessments. Zavata aims to optimize the recruitment journey for both employers and candidates by leveraging advanced AI technology. The platform provides personalized and engaging interview experiences, data-driven decision-making, and seamless integration with existing HR tools.

Random Walk is an advanced AI solutions provider for modern enterprises, offering AI consulting, integration services, and a range of AI tools tailored to various business functions and industries. The platform specializes in seamless AI integration, empowering businesses to maximize their potential through the adoption of AI technologies. With a focus on corporate AI fundamentals and managed services, Random Walk aims to simplify AI adoption and digital transformation for its clients.

Seedbox is an AI-based solution provider that crafts custom AI solutions to address specific challenges and boost businesses. They offer tailored AI solutions, state-of-the-art corporate innovation methods, high-performance computing infrastructure, secure and cost-efficient AI services, and maintain the highest security standards. Seedbox's expertise covers in-depth AI development, UX/UI design, and full-stack development, aiming to increase efficiency and create sustainable competitive advantages for their clients.

RoundOneAI is an AI-driven platform revolutionizing tech recruitment by offering unbiased and efficient candidate assessments, ensuring skill-based evaluations free from demographic biases. The platform streamlines the hiring process with tailored job descriptions, AI-powered interviews, and insightful analytics. RoundOneAI helps companies evaluate candidates simultaneously, make informed hiring decisions, and identify top talent efficiently.

HEROZ is a Japanese company that specializes in AI technology. They offer a variety of AI-related services, including AI/DX support, AI consulting, and AI development. HEROZ's mission is to use AI to solve various problems in different industries and create a better future.

OpenChat is a website that provides users with 10,000 ways to make money using ChatGPT and AI. The website offers a variety of resources, including personalized AI income ideas, a personal AI business coach, and standard email support. OpenChat also has a library of up to 10,000 AI income ideas that users can access. The website's slogan is "10,000 Ways to Make Money with ChatGPT and AI". Some of the features of OpenChat include the ability to save ideas for later use, access to a full library of up to 10,000 ideas, a personal AI business coach, and standard email support. Some of the advantages of using OpenChat include the ability to get personalized AI income ideas, access to a large library of AI income ideas, and the ability to get support from a personal AI business coach. Some of the disadvantages of using OpenChat include the fact that it is a paid service, and that the number of tokens that users can use each month is limited. Some of the frequently asked questions about OpenChat include how to use the website, how to get personalized AI income ideas, and how to get support from a personal AI business coach. The name of the application is OpenChat. Some of the jobs that are suitable for this tool include freelance AI business ideas, content creation AI income ideas, virtual assistance AI income ideas, mobile apps AI income ideas, web apps AI income ideas, finance AI income ideas, online survey AI income ideas, online course AI income ideas, social media AI income ideas, digital marketing AI income ideas, data entry AI income ideas, legal service AI income ideas, stock photography AI income ideas. Some of the AI keywords that are related to the application include AI business ideas, content creation, virtual assistance, mobile apps, web apps, finance, online surveys, online courses, social media, digital marketing, data entry, legal services, stock photography. Some of the tasks that users can use this tool to do include generating AI-driven content, creating AI-powered virtual assistants, developing AI-enhanced mobile apps, building AI-driven websites, offering AI-based financial advice, conducting AI-powered market research, creating AI-generated art, and providing AI-enabled customer support.

Lex Fridman is an AI tool developed by Lex Fridman, a Research Scientist at MIT, focusing on human-robot interaction and machine learning. The tool offers various resources such as podcasts, research publications, and studies related to AI-assisted driving data collection, autonomous vehicle systems, gaze estimation, and cognitive load estimation. It aims to provide insights into the safe and enjoyable interaction between humans and AI in driving scenarios.

GptSdk is an AI tool that simplifies incorporating AI capabilities into PHP projects. It offers dynamic prompt management, model management, bulk testing, collaboration chaining integration, and more. The tool allows developers to develop professional AI applications 10x faster, integrates with Laravel and Symfony, and supports both local and API prompts. GptSdk is open-source under the MIT License and offers a flexible pricing model with a generous free tier.

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.

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.

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.

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.

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.

FigStep is a black-box jailbreaking algorithm against large vision-language models (VLMs). It feeds harmful instructions through the image channel and uses benign text prompts to induce VLMs to output contents that violate common AI safety policies. The tool highlights the vulnerability of VLMs to jailbreaking attacks, emphasizing the need for safety alignments between visual and textual modalities.

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.

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.

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.

The Awesome-LLM-Post-training repository is a curated collection of influential papers, code implementations, benchmarks, and resources related to Large Language Models (LLMs) Post-Training Methodologies. It covers various aspects of LLMs, including reasoning, decision-making, reinforcement learning, reward learning, policy optimization, explainability, multimodal agents, benchmarks, tutorials, libraries, and implementations. The repository aims to provide a comprehensive overview and resources for researchers and practitioners interested in advancing LLM technologies.

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.

SLMs-Survey is a comprehensive repository that includes papers and surveys on small language models. It covers topics such as technology, on-device applications, efficiency, enhancements for LLMs, and trustworthiness. The repository provides a detailed overview of existing SLMs, their architecture, enhancements, and specific applications in various domains. It also includes information on SLM deployment optimization techniques and the synergy between SLMs and LLMs.

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.

Co-op Translator is a tool designed to facilitate communication between team members working on cooperative projects. It allows users to easily translate messages and documents in real-time, enabling seamless collaboration across language barriers. The tool supports multiple languages and provides accurate translations to ensure clear and effective communication within the team. With Co-op Translator, users can improve efficiency, productivity, and teamwork in their cooperative endeavors.

Chat with your data using OpenAI and AI Search. This solution accelerator uses an Azure OpenAI GPT model and an Azure AI Search index generated from your data, which is integrated into a web application to provide a natural language interface, including speech-to-text functionality, for search queries. Users can drag and drop files, point to storage, and take care of technical setup to transform documents. There is a web app that users can create in their own subscription with security and authentication.

CogAgent is an advanced intelligent agent model designed for automating operations on graphical interfaces across various computing devices. It supports platforms like Windows, macOS, and Android, enabling users to issue commands, capture device screenshots, and perform automated operations. The model requires a minimum of 29GB of GPU memory for inference at BF16 precision and offers capabilities for executing tasks like sending Christmas greetings and sending emails. Users can interact with the model by providing task descriptions, platform specifications, and desired output formats.

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.

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