Best AI tools for< Policy Researcher >

The EU Artificial Intelligence Act website provides up-to-date developments and analyses of the EU AI Act. It offers tools such as the AI Act Explorer to browse the full AI Act text online and the Compliance Checker to understand how the AI Act will impact users. The website aims to inform users about the European regulation on artificial intelligence, categorizing AI applications based on risk levels and legal requirements. It also highlights the importance of AI governance and its global implications.

Climate Policy Radar is an AI-powered application that serves as a live, searchable database containing over 5,000 national climate laws, policies, and UN submissions. The app aims to organize, analyze, and democratize climate data by providing open data, code, and machine learning models. It promotes a responsible approach to AI, fosters a climate NLP community, and offers an API for organizations to utilize the data. The tool addresses the challenge of sparse and siloed climate-related information, empowering decision-makers with evidence-based policies to accelerate climate action.

Google Public Policy is a website dedicated to showcasing Google's public policy initiatives and priorities. It provides information on various topics such as consumer choice, economic opportunity, privacy, responsible AI, security, sustainability, and trustworthy information & content. The site highlights Google's efforts in advancing bold and responsible AI, strengthening security, and promoting a more sustainable future. It also features news updates, research briefs, and collaborations with organizations to address societal challenges through technology and innovation.

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 International Journal for Educational Integrity is an AI tool that focuses on publishing articles related to academic integrity, ethics, and plagiarism. It features original research articles, reviews, and thematic collections on topics such as machine-based plagiarism, contract cheating, and the impact of emergencies on educational integrity. The journal aims to address emerging threats to academic integrity and promote ethical practices in education.

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 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.

Dobb·E is an open-source, general framework for learning household robotic manipulation. It aims to create a 'generalist machine' for homes that can adapt and learn various tasks cost-effectively. Dobb·E can learn a new task in just five minutes of demonstration, thanks to a tool called 'The Stick' for data collection. The system achieved an 81% success rate in completing 109 tasks across 10 homes in New York City. Dobb·E is designed to accelerate research on home robots and make robot assistants a common sight in households.

MacWhisper is a native macOS application that utilizes OpenAI's Whisper technology for transcribing audio files into text. It offers a user-friendly interface for recording, transcribing, and editing audio, making it suitable for various use cases such as transcribing meetings, lectures, interviews, and podcasts. The application is designed to protect user privacy by performing all transcriptions locally on the device, ensuring that no data leaves the user's machine.

blog.biocomm.ai is an AI safety blog that focuses on the existential threat posed by uncontrolled and uncontained AI technology. It curates and organizes information related to AI safety, including the risks and challenges associated with the proliferation of AI. The blog aims to educate and raise awareness about the importance of developing safe and regulated AI systems to ensure the survival of humanity.

AI Elections Accord is a tech accord aimed at combating the deceptive use of AI in the 2024 elections. It sets expectations for managing risks related to deceptive AI election content on large-scale platforms. The accord focuses on prevention, provenance, detection, responsive protection, evaluation, public awareness, and resilience to safeguard the democratic process. It emphasizes collective efforts, education, and the development of defensive tools to protect public debate and build societal resilience against deceptive AI content.

Epoch AI is a research institute dedicated to investigating key trends and questions that will shape the trajectory and governance of AI. They provide essential insights for policymakers, conduct rigorous analysis of trends in AI and machine learning, and produce reports, papers, models, and visualizations to advance evidence-based discussions about AI. Epoch AI collaborates with stakeholders and collects key data on machine learning models to analyze historical and contemporary progress in AI. They are known for their thoughtful and best-researched survey work in the industry.

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.

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 website focuses on the intersection of artificial intelligence (AI) and inclusion, exploring the impact of AI technologies on marginalized populations and global digital inequalities. It provides resources, research findings, and ideas on themes like health, education, and humanitarian crisis mitigation. The site showcases the work of the Ethics and Governance of AI initiative in collaboration with the MIT Media Lab, incorporating perspectives from experts in the field. It aims to address challenges and opportunities related to AI and inclusion through research, events, and multi-stakeholder dialogues.

CrowdPrisma is an AI-powered survey analysis tool that revolutionizes the way insights are extracted from free-text responses. It utilizes a cutting-edge TextEngine to automatically group responses into coherent themes and topics, providing users with quantitative insights in minutes. The platform offers an interactive dashboard for in-depth data exploration, multilingual support, and fair billing practices. CrowdPrisma is ideal for market research, customer experience analysis, human resources investigations, policy research, and more.

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.

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.

Otio is an AI research and writing partner powered by GPT-4o, Claude 3.5, and Mistral. It offers a fast and efficient way to summarize and chat with documents, write and edit in an AI text editor, and automate complex workflows. Otio is loved by over 80,000 researchers and students for its ability to extract insights from research quickly, provide detailed AI summaries, automate repetitive tasks, and enhance writing and editing processes with AI technology.

The Petrie-Flom Center at Harvard Law School is a leading center for the study of health law and policy. The Center's mission is to improve the health of the public through research, teaching, and advocacy. The Center's work focuses on a wide range of health law and policy issues, including access to care, the regulation of health care providers, and the ethical and legal implications of new health technologies.

Awesome-Robotics-3D is a curated list of 3D Vision papers related to Robotics domain, focusing on large models like LLMs/VLMs. It includes papers on Policy Learning, Pretraining, VLM and LLM, Representations, and Simulations, Datasets, and Benchmarks. The repository is maintained by Zubair Irshad and welcomes contributions and suggestions for adding papers. It serves as a valuable resource for researchers and practitioners in the field of Robotics and Computer Vision.

This repository compiles a list of academic papers that evaluate, align, simulate, and provide surveys or perspectives on the use of Large Language Models (LLMs) in the field of Social Science. The papers cover various aspects of LLM research, including assessing their alignment with human values, evaluating their capabilities in tasks such as opinion formation and moral reasoning, and exploring their potential for simulating social interactions and addressing issues in diverse fields of Social Science. The repository aims to provide a comprehensive resource for researchers and practitioners interested in the intersection of LLMs and Social Science.

Pearl is a production-ready Reinforcement Learning AI agent library open-sourced by the Applied Reinforcement Learning team at Meta. It enables researchers and practitioners to develop Reinforcement Learning AI agents that prioritize cumulative long-term feedback over immediate feedback and can adapt to environments with limited observability, sparse feedback, and high stochasticity. Pearl offers a diverse set of unique features for production environments, including dynamic action spaces, offline learning, intelligent neural exploration, safe decision making, history summarization, and data augmentation.

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.

Awesome-Papers-Autonomous-Agent is a curated collection of recent papers focusing on autonomous agents, specifically interested in RL-based agents and LLM-based agents. The repository aims to provide a comprehensive resource for researchers and practitioners interested in intelligent agents that can achieve goals, acquire knowledge, and continually improve. The collection includes papers on various topics such as instruction following, building agents based on world models, using language as knowledge, leveraging LLMs as a tool, generalization across tasks, continual learning, combining RL and LLM, transformer-based policies, trajectory to language, trajectory prediction, multimodal agents, training LLMs for generalization and adaptation, task-specific designing, multi-agent systems, experimental analysis, benchmarking, applications, algorithm design, and combining with RL.

TorchRL is an open-source Reinforcement Learning (RL) library for PyTorch. It provides pytorch and **python-first** , low and high level abstractions for RL that are intended to be **efficient** , **modular** , **documented** and properly **tested**. The code is aimed at supporting research in RL. Most of it is written in python in a highly modular way, such that researchers can easily swap components, transform them or write new ones with little effort.

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.

The 'Awesome LLMs Planning Reasoning' repository is a curated collection focusing on exploring the capabilities of Large Language Models (LLMs) in planning and reasoning tasks. It includes research papers, code repositories, and benchmarks that delve into innovative techniques, reasoning limitations, and standardized evaluations related to LLMs' performance in complex cognitive tasks. The repository serves as a comprehensive resource for researchers, developers, and enthusiasts interested in understanding the advancements and challenges in leveraging LLMs for planning and reasoning in real-world scenarios.

The Arcade Learning Environment (ALE) is a simple framework that allows researchers and hobbyists to develop AI agents for Atari 2600 games. It is built on top of the Atari 2600 emulator Stella and separates the details of emulation from agent design. The ALE currently supports three different interfaces: C++, Python, and OpenAI Gym.

**Curated collection of papers and resources on how to unlock the reasoning ability of LLMs and MLLMs.** **Description in less than 400 words, no line breaks and quotation marks.** Large Language Models (LLMs) have revolutionized the NLP landscape, showing improved performance and sample efficiency over smaller models. However, increasing model size alone has not proved sufficient for high performance on challenging reasoning tasks, such as solving arithmetic or commonsense problems. This curated collection of papers and resources presents the latest advancements in unlocking the reasoning abilities of LLMs and Multimodal LLMs (MLLMs). It covers various techniques, benchmarks, and applications, providing a comprehensive overview of the field. **5 jobs suitable for this tool, in lowercase letters.** - content writer - researcher - data analyst - software engineer - product manager **Keywords of the tool, in lowercase letters.** - llm - reasoning - multimodal - chain-of-thought - prompt engineering **5 specific tasks user can use this tool to do, in less than 3 words, Verb + noun form, in daily spoken language.** - write a story - answer a question - translate a language - generate code - summarize a document

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.

EDA-AI is a repository containing implementations of cutting-edge research papers in the field of chip design. It includes DeepPlace, PRNet, HubRouter, and PreRoutGNN models for tasks such as placement, routing, timing prediction, and global routing. Researchers and practitioners can leverage these implementations to explore advanced techniques in chip design.

This repository is a curated list of research papers that explore the integration of Large Language Model (LLM) technology with tabular data. It aims to provide a comprehensive resource for researchers and practitioners interested in this emerging field. The repository includes papers on a wide range of topics, including table-to-text generation, table question answering, and tabular data classification. It also includes a section on related datasets and resources.

Qlib is an open-source, AI-oriented quantitative investment platform that supports diverse machine learning modeling paradigms, including supervised learning, market dynamics modeling, and reinforcement learning. It covers the entire chain of quantitative investment, from alpha seeking to order execution. The platform empowers researchers to explore ideas and implement productions using AI technologies in quantitative investment. Qlib collaboratively solves key challenges in quantitative investment by releasing state-of-the-art research works in various paradigms. It provides a full ML pipeline for data processing, model training, and back-testing, enabling users to perform tasks such as forecasting market patterns, adapting to market dynamics, and modeling continuous investment decisions.

ai-collective-tools is an open-source community dedicated to creating a comprehensive collection of AI tools for developers, researchers, and enthusiasts. The repository provides a curated selection of AI tools and resources across various categories such as 3D, Agriculture, Art, Audio Editing, Avatars, Chatbots, Code Assistant, Cooking, Copywriting, Crypto, Customer Support, Dating, Design Assistant, Design Generator, Developer, E-Commerce, Education, Email Assistant, Experiments, Fashion, Finance, Fitness, Fun Tools, Gaming, General Writing, Gift Ideas, HealthCare, Human Resources, Image Classification, Image Editing, Image Generator, Interior Designing, Legal Assistant, Logo Generator, Low Code, Models, Music, Paraphraser, Personal Assistant, Presentations, Productivity, Prompt Generator, Psychology, Real Estate, Religion, Research, Resume, Sales, Search Engine, SEO, Shopping, Social Media, Spreadsheets, SQL, Startup Tools, Story Teller, Summarizer, Testing, Text to Speech, Text to Image, Transcriber, Travel, Video Editing, Video Generator, Weather, Writing Generator, and Other Resources.

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.

This repository contains a collection of papers and code for the CVPR 2024 conference. The papers cover a wide range of topics in computer vision, including object detection, image segmentation, image generation, and video analysis. The code provides implementations of the algorithms described in the papers, making it easy for researchers and practitioners to reproduce the results and build upon the work of others. The repository is maintained by a team of researchers at the University of California, Berkeley.

This repository provides a curated list of papers, datasets, and resources related to the detection and mitigation of hallucinations in large language models (LLMs). Hallucinations refer to the generation of factually incorrect or nonsensical text by LLMs, which can be a significant challenge for their use in real-world applications. The resources in this repository aim to help researchers and practitioners better understand and address this issue.

ReST-MCTS is a reinforced self-training approach that integrates process reward guidance with tree search MCTS to collect higher-quality reasoning traces and per-step value for training policy and reward models. It eliminates the need for manual per-step annotation by estimating the probability of steps leading to correct answers. The inferred rewards refine the process reward model and aid in selecting high-quality traces for policy model self-training.

AIlice is a fully autonomous, general-purpose AI agent that aims to create a standalone artificial intelligence assistant, similar to JARVIS, based on the open-source LLM. AIlice achieves this goal by building a "text computer" that uses a Large Language Model (LLM) as its core processor. Currently, AIlice demonstrates proficiency in a range of tasks, including thematic research, coding, system management, literature reviews, and complex hybrid tasks that go beyond these basic capabilities. AIlice has reached near-perfect performance in everyday tasks using GPT-4 and is making strides towards practical application with the latest open-source models. We will ultimately achieve self-evolution of AI agents. That is, AI agents will autonomously build their own feature expansions and new types of agents, unleashing LLM's knowledge and reasoning capabilities into the real world seamlessly.

CYO KATSUI

Expert in environmental justice data, with specific response criteria.

Educational guide in government and political science, offering comprehensive yet accessible explanations.

Local government guide for Virginia.

Embrace the economics of ecosystems with EcoEconomist, balancing the scales between economic development and environmental stewardship.

Expert in wind energy insights and solutions

An unyielding champion against predatory financial practices, adept at analyzing and exposing complex financial mechanisms, and relentless in advocating for consumer rights and transparency.

Search and analyze Government of Canada departmental expenditures and full time employees, by program. Connected to Government of Canada API.

OpenAIのTerms of UseとPrivacy policyを参照できます(2023年12月14日適用分)

Expert and respectful guide on aging research and its societal impacts.

专注于成渝双城经济圈研究的指导者

Expert on foreign policy and military interventions, tailored for high school students.

I search Lambeth's planning site to provide links to policies and documents.

Education policy expert with firm boundaries.

Expert in climate policy, data analysis, roadmaps, and socio-economic impacts, providing up-to-date news and insights

Energy Policy AI

AI and cyber warfare expert, advising on policy, conflict, and technical trends

Chinese biopharma, healthcare, policy, and industrial park analysis expert.

AI Battle Realism Simulator | Realistic combat outcomes, with policy-compliant visuals