Best AI tools for< Develop Policy Strategies >

Policy-Insider.AI is an AI-powered web application that revolutionizes public policy monitoring and analysis. It offers real-time, multilingual, and multinational insights by leveraging advanced AI technology. Users can access comprehensive policy documents and analysis in multiple languages, receive instant alerts on policy changes, and gain a global perspective with data from numerous countries and international institutions. The application provides tailored solutions for policy development, advocacy progress measurement, and stakeholder engagement, enhancing public affairs strategies and decision-making processes.

The Center for a New American Security (CNAS) is a bipartisan, non-profit think tank that focuses on national security and defense policy. CNAS conducts research, analysis, and policy development on a wide range of topics, including defense strategy, nuclear weapons, cybersecurity, and energy security. CNAS also provides expert commentary and analysis on current events and policy debates.

KPMG is an AI tool that helps clients harness the power and potential of AI, from strategy to implementation. With over 150 years of industry insights, KPMG assists in identifying AI opportunities, developing business cases, optimizing value streams, and providing workforce education and training. The tool supports the development, deployment, and management of AI systems, offering services such as data collection, use case development, and technical integration. KPMG also focuses on organizational change management, workforce shaping, and building sector-specific AI solutions to transform enterprises. Additionally, KPMG ensures ethical and compliant AI initiatives through its Trusted AI framework, empowering and augmenting human capabilities while enhancing the employee experience. The tool has been instrumental in helping clients across various sectors expedite customer responses, transform procurement processes, and manage policy effectively with AI.

The OECD Observatory of Public Sector Innovation (OPSI) is a website that provides resources and tools to help governments and public servants explore new possibilities for innovation. OPSI's work areas include European Commission Collaboration, Anticipatory Innovation, Cross-Border Government Innovation, Behavioural Insights, Innovative Capacity, Innovation Trends, Innovation Portfolios, Mission-Oriented Innovation, Innovation Management, and Systems Approaches. OPSI also has a number of resources available, including a Toolkit Navigator, Case Study Library, Portfolio Exploration Tool, and Anticipatory Innovation Resource (AIR).

Stanford HAI is a research institute at Stanford University dedicated to advancing AI research, education, and policy to improve the human condition. The institute brings together researchers from a variety of disciplines to work on a wide range of AI-related projects, including developing new AI algorithms, studying the ethical and societal implications of AI, and creating educational programs to train the next generation of AI leaders. Stanford HAI is committed to developing human-centered AI technologies and applications that benefit all of humanity.

The OECD Artificial Intelligence Policy Observatory, also known as OECD.AI, is a platform that focuses on AI policy issues, risks, and accountability. It provides resources, tools, and metrics to build and deploy trustworthy AI systems. The platform aims to promote innovative and trustworthy AI through collaboration with countries, stakeholders, experts, and partners. Users can access information on AI incidents, AI principles, policy areas, publications, and videos related to AI. OECD.AI emphasizes the importance of data privacy, generative AI management, AI computing capacities, and AI's potential futures.

The Coalition for Health AI (CHAI) is an AI application that provides guidelines for the responsible use of AI in health. It focuses on developing best practices and frameworks for safe and equitable AI in healthcare. CHAI aims to address algorithmic bias and collaborates with diverse stakeholders to drive the development, evaluation, and appropriate use of AI in healthcare.

The U.S. Chamber of Commerce is the world's largest business organization, representing the interests of more than 3 million businesses of all sizes, sectors, and regions. The Chamber's mission is to promote economic growth and prosperity for all Americans.

The Future of Privacy Forum (FPF) is an AI tool that serves as a catalyst for privacy leadership and scholarship, advancing principled data practices in support of emerging technologies. It provides resources, training sessions, and guidance on AI-related topics, online advertising, youth privacy legislation, and more. FPF brings together industry, academics, civil society, policymakers, and other stakeholders to explore challenges posed by emerging technologies and develop privacy protections, ethical norms, and best practices.

Climate Change AI is a community platform dedicated to leveraging artificial intelligence to address the challenges of climate change. The platform serves as a hub for researchers, practitioners, and policymakers to collaborate, share knowledge, and develop AI solutions for mitigating the impacts of climate change. By harnessing the power of AI technologies, Climate Change AI aims to accelerate the transition to a sustainable and resilient future.

The Montreal AI Ethics Institute (MAIEI) is an international non-profit organization founded in 2018, dedicated to democratizing AI ethics literacy. It equips citizens concerned about artificial intelligence and its impact on society to take action through research summaries, columns, and AI applications in various fields.

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.

Climate Change AI is a global non-profit organization that focuses on catalyzing impactful work at the intersection of climate change and machine learning. They provide resources, reports, events, and grants to support the use of machine learning in addressing climate change challenges.

Global Plastic Watch (GPW) is a digital platform that maps the world's plastic pollution in near real-time using a unique combination of satellite imagery and artificial intelligence. It provides a comprehensive view of the global plastic waste crisis, including the location and size of plastic waste sites, the types of plastic waste, and the impact of plastic pollution on the environment and human health.

The AIGA AI Governance Framework is a practice-oriented framework for implementing responsible AI. It provides organizations with a systematic approach to AI governance, covering the entire process of AI system development and operations. The framework supports compliance with the upcoming European AI regulation and serves as a practical guide for organizations aiming for more responsible AI practices. It is designed to facilitate the development and deployment of transparent, accountable, fair, and non-maleficent AI systems.

Microsoft Responsible AI Toolbox is a suite of tools designed to assess, develop, and deploy AI systems in a safe, trustworthy, and ethical manner. It offers integrated tools and functionalities to help operationalize Responsible AI in practice, enabling users to make user-facing decisions faster and easier. The Responsible AI Dashboard provides a customizable experience for model debugging, decision-making, and business actions. With a focus on responsible assessment, the toolbox aims to promote ethical AI practices and transparency in AI development.

The AI Index is a comprehensive resource for data and insights on artificial intelligence. It provides unbiased, rigorously vetted, and globally sourced data for policymakers, researchers, journalists, executives, and the general public to develop a deeper understanding of the complex field of AI. The AI Index tracks, collates, distills, and visualizes data relating to artificial intelligence. This includes data on research and development, technical performance and ethics, the economy and education, AI policy and governance, diversity, public opinion, and more.

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.

C&EN, a publication of the American Chemical Society, provides the latest news and insights on the chemical industry, including research, technology, business, and policy. It covers a wide range of topics, including analytical chemistry, biological chemistry, business, careers, education, energy, environment, food, materials, people, pharmaceuticals, physical chemistry, policy, research integrity, safety, and synthesis.

Empler AI Inc is a website offering AI-powered products and services, including application programming interfaces, software tools, developer services, and documentation. The site collects Personal Information for various purposes, such as providing, analyzing, and improving services, conducting research, and ensuring security. Empler AI respects user privacy and complies with legal obligations. The site also offers aggregated information for analysis and research. Users can contact support for information updates or privacy rights. Empler AI implements security measures to protect Personal Information and may transfer data internationally.

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.

Paper-Reading-ConvAI is a repository that contains a list of papers, datasets, and resources related to Conversational AI, mainly encompassing dialogue systems and natural language generation. This repository is constantly updating.

This repository provides a systematic and comprehensive review of efficient LLMs research. We organize the literature in a taxonomy consisting of three main categories, covering distinct yet interconnected efficient LLMs topics from **model-centric** , **data-centric** , and **framework-centric** perspective, respectively. We hope our survey and this GitHub repository can serve as valuable resources to help researchers and practitioners gain a systematic understanding of the research developments in efficient LLMs and inspire them to contribute to this important and exciting field.

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.

ChatGPT Queue Prompts is a collection of prompt chains designed to enhance interactions with large language models like ChatGPT. These prompt chains help build context for the AI before performing specific tasks, improving performance. Users can copy and paste prompt chains into the ChatGPT Queue extension to process prompts in sequence. The repository includes example prompt chains for tasks like conducting AI company research, building SEO optimized blog posts, creating courses, revising resumes, enriching leads for CRM, personal finance document creation, workout and nutrition plans, marketing plans, and more.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

This repository contains a collection of papers and resources related to Large Language Models (LLMs), including their applications in various domains such as text generation, translation, question answering, and dialogue systems. The repository also includes discussions on the ethical and societal implications of LLMs. **Description** This repository is a collection of papers and resources related to Large Language Models (LLMs). LLMs are a type of artificial intelligence (AI) that can understand and generate human-like text. They have a wide range of applications, including text generation, translation, question answering, and dialogue systems. **For Jobs** - **Content Writer** - **Copywriter** - **Editor** - **Journalist** - **Marketer** **AI Keywords** - **Large Language Models** - **Natural Language Processing** - **Machine Learning** - **Artificial Intelligence** - **Deep Learning** **For Tasks** - **Generate text** - **Translate text** - **Answer questions** - **Engage in dialogue** - **Summarize text**

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.

System Attributes: Legacy System, Diplomatic Clearance, Special Purpose Executive Clearance, REDACTED, REDACTED

Analytics | Strategies | Frameworks

Your go-to AI for crafting sustainable energy solutions. From solar to wind, I'll help devise eco-friendly strategies! 🍃

ASESOR DE POLÍTICA PÚBLICA DE TELECOMUNICACIONES 2023 - 2025

A reference tool for UK energy transmission campaigners.

Especialista em dados de pós-graduação em Ciências Ambientais do Brasil.

Thinking partner on Just Transitions

Simulates a geo-political grand strategy game.

Energy Insights Lab is a multi-disciplinary team of dedicated professionals advising on energy markets, technologies, and decarbonization.

Analyzing export industries with detailed, historical, and global insights.

Expert on global biotech crops, policies, and trade data.

Expert in Austrian Economics, from theory to current applications, with access to key texts.

EU crypto regulation expert, adapting to user expertise and inquiry precision.

Advanced epidemiology expert with AI-driven data integration and dynamic visualization tools.

专注于成渝双城经济圈研究的指导者

Analyzing global health data for pandemic prediction and strategy.

Global Conflict Analyst that will provide a 'wartime update' on the worst global conflict atm.

Enhanced AI expert in dynamic, real-time Climate Science analysis.

A guide to visualizing Earth's future and climate change impact.

Healthcare futurist discussing trends, innovations, and predictions, inspired by space, resilience, and precision medicine.