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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.

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.

Swinghub is the ultimate non-monogamous social network app. It is packed with powerful features to help you get started, including the ability to see who's near you, who's looked at you, and what events are happening around you. Swinghub also has a number of safety features in place, including AI technology to prevent catfish profiles and AI moderation to ensure that nothing illegal or outside the community guidelines is being posted.

CFR Explorer is an AI-powered tool that allows users to ask questions about regulations in Title 14 and receive answers from AI. Users can search for specific regulations, such as requirements for general aviation pilots or VFR weather requirements for Class C airspace. The tool is currently in beta, aiming to gather feedback for system improvement. Users are advised not to share private information in queries, and the tool's creators are not liable for the content generated.

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.

KERV is an AI-powered video and creative technology company that offers ad performance solutions, publisher revenue opportunities, in-show monetization solutions, and data and measurement services. Their patented image recognition and product correlation technology enable deeper relationships between publishers, brands, and consumers. KERV's AI technology makes any video explorable and shoppable with unrivaled speed and precision, delivering real business outcomes. They provide intelligent video solutions, active attention indexing, greater speed and precision, 1st party data insights, and brand safety measures.

Texthub is an AI-powered chatbot that allows users to engage in NSFW conversations and role-play scenarios. It is designed to provide a realistic and immersive experience, with the AI responding in a natural and engaging way. Texthub also offers a variety of features to enhance the user experience, such as the ability to customize the AI's appearance and personality.

Betterhalf is an AI-powered platform that offers end-to-end wedding planning services in India. It combines AI matchmaking services with wedding planning expertise to help individuals plan their perfect weddings. The platform provides personalized proposals, exclusive deals, expert insights, and stress-free experiences to ensure a seamless wedding planning process. With a focus on safety and user experience, Betterhalf offers transparent pricing and customizable packages to suit different budgets and preferences. Whether it's venue booking, decorator booking, photographers, or mehendi artists, Betterhalf caters to all wedding planning needs, making it a one-stop solution for couples looking to create memorable wedding experiences.

AI Girlfriend WTF is an ultimate AI roleplay chat application that allows users to interact with virtual AI girlfriends in various fantasy scenarios, from casual to extreme. Users can create their ideal girl, chat, and enjoy spicy images with personalized AI characters. The platform prioritizes user safety and privacy, offering a premium sexting AI chat and NSFW art experience. With cutting-edge artificial intelligence technology, AI Girlfriend WTF provides a realistic and engaging virtual companionship experience through AI chatting capabilities and an AI image generator.

eBicycles.ai is your personal e-bike expert providing guidance on purchasing an e-bike and maintaining your favorite bike. The website offers valuable information on topics such as the best e-bikes for city commuting, e-bike battery maintenance, safety accessories, and the latest trends in e-bike technology.

MindPeace AI is an AI-powered platform that serves as a personal mental wellbeing companion, offering therapeutic techniques to guide users towards self-reflection, relaxation, and emotional balance. It provides tools, exercises, and gentle reminders in a convenient, stigma-free environment. The platform is designed to complement traditional therapy by providing on-demand support, but it does not replace human therapists. MindPeace AI prioritizes privacy and safety, ensuring that conversations are private and personal information is never shared with third parties.

The website is a comprehensive platform providing medical news, articles, and resources covering a wide range of health topics such as COVID-19, artificial intelligence in healthcare, diseases, treatments, and medical advancements. It offers insights from experts, interviews, white papers, and newsletters in the fields of medicine and life sciences. Users can access information on various health categories, research findings, safety summaries, and trending stories in the medical and life sciences domains.

Health AI Partnership (HAIP) is an AI tool designed to empower healthcare professionals to effectively, safely, and equitably use AI through community-informed up-to-date standards. The platform offers resources, publications, events, and a practice network to advance the use of AI in healthcare and support professionals in implementing AI solutions.

Blush is an AI-powered dating simulator that helps users learn and practice relationship skills in a safe and fun environment. It offers a judgment-free space to refine relationship skills, engage with different personalities, practice communication skills, and receive personalized guidance. Users can experiment with different approaches to flirting and communication, gain a better understanding of relationships, and explore their desires safely. Blush allows users to meet potential matches with unique personalities and relationship styles, providing emotional support and companionship. The application aims to empower users to navigate real-world relationship dynamics with confidence and authenticity.

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.

Uhmegle is an AI-powered platform that serves as an alternative to Omegle for video and text chat. It allows users to connect with strangers based on shared interests or random selection. The platform offers a safe chatting experience through a combination of human moderation and artificial intelligence. Users can choose to chat via text or video, and have the option to add interests for better matching. Uhmegle also features a Country Selector for meeting strangers from different countries.

Explore AI is a semantic search engine that utilizes artificial intelligence technology to enhance search capabilities. The platform allows users to search for information in a more intuitive and context-aware manner, making it easier to find relevant content quickly. By leveraging AI algorithms, Explore AI provides a personalized search experience that adapts to the user's preferences and behavior. The platform aims to revolutionize the way people interact with search engines by offering advanced features and intelligent search capabilities.

Pornpen.ai is an AI tool that utilizes artificial intelligence technology to provide a platform for generating and analyzing pornographic content. The website offers various features for users to explore and interact with AI-generated adult content. Users can access a wide range of functionalities related to adult entertainment through the AI algorithms implemented on the platform.

Getin.AI is a platform that focuses on AI jobs, career paths, and company profiles in the fields of artificial intelligence, machine learning, and data science. Users can explore various job categories, such as Analyst, Consulting, Customer Service & Support, Data Science & Analytics, Engineering, Finance & Accounting, HR & Recruiting, Legal, Compliance and Ethics, Marketing & PR, Product, Sales And Business Development, Senior Management / C-level, Strategy & M&A, and UX, UI & Design. The platform provides a comprehensive list of remote job opportunities and features detailed job listings with information on job titles, companies, locations, job descriptions, and required skills.

Multi AI Chat is an AI-powered application that allows users to interact with various AI models by asking questions. The platform enables users to seek information, get answers, and engage in conversations with AI on a wide range of topics. With Multi AI Chat, users can explore the capabilities of different AI technologies and enhance their understanding of artificial intelligence.

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.

The Awesome-System2-Reasoning-LLM repository is dedicated to a survey paper titled 'From System 1 to System 2: A Survey of Reasoning Large Language Models'. It explores the development of reasoning Large Language Models (LLMs), their foundational technologies, benchmarks, and future directions. The repository provides resources and updates related to the research, tracking the latest developments in the field of reasoning LLMs.

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.

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.

A curated list of Generative AI projects, tools, artworks, and models

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.

This repository is a comprehensive survey of harmful fine-tuning attacks and defenses for large language models (LLMs). It provides a curated list of must-read papers on the topic, covering various aspects such as alignment stage defenses, fine-tuning stage defenses, post-fine-tuning stage defenses, mechanical studies, benchmarks, and attacks/defenses for federated fine-tuning. The repository aims to keep researchers updated on the latest developments in the field and offers insights into the vulnerabilities and safeguards related to fine-tuning LLMs.

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.

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.

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.

A repository that lists papers related to Large Language Model (LLM) based agents. The repository covers various topics including survey, planning, feedback & reflection, memory mechanism, role playing, game playing, tool usage & human-agent interaction, benchmark & evaluation, environment & platform, agent framework, multi-agent system, and agent fine-tuning. It provides a comprehensive collection of research papers on LLM-based agents, exploring different aspects of AI agent architectures and applications.

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

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.

Awesome-Attention-Heads is a platform providing the latest research on Attention Heads, focusing on enhancing understanding of Transformer structure for model interpretability. It explores attention mechanisms for behavior, inference, and analysis, alongside feed-forward networks for knowledge storage. The repository aims to support researchers studying LLM interpretability and hallucination by offering cutting-edge information on Attention Head Mining.

This repository is a collection of papers focused on understanding the internal mechanism of large language models (LLM). It includes research on topics such as how LLMs handle multilingualism, learn in-context, and handle factual associations. The repository aims to provide insights into the inner workings of transformer-based language models through a curated list of papers and surveys.

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.

A curated collection of papers and resources on Mixture of Experts in Large Language Models. The repository provides a chronological overview of several representative Mixture-of-Experts (MoE) models in recent years, structured according to release dates. It covers MoE models from various domains like Natural Language Processing (NLP), Computer Vision, Multimodal, and Recommender Systems. The repository aims to offer insights into Inference Optimization Techniques, Sparsity exploration, Attention mechanisms, and safety enhancements in MoE models.

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.

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