Best AI tools for< Critique Presentations >

Critique is an AI tool that redefines browsing by offering autonomous fact-checking, informed question answering, and a localized universal recommendation system. It automatically critiques comments and posts on platforms like Reddit, Youtube, and Linkedin by vetting text on any website. The tool cross-references and analyzes articles in real-time, providing vetted and summarized information directly in the user's browser.

The website is the official site of the Sun Group (China) Co., Ltd., endorsed by Louis Koo. It provides information about the company's history, leadership, organizational structure, educational programs, research achievements, and employee activities. The site also features news updates, announcements, and resources for download.

Yogger is an AI-powered video analysis and movement assessment tool designed for coaches, trainers, physical therapists, and athletes. It allows users to track form, gather data, and analyze movement for any sport or activity in seconds. With features like AI joint tracking, virtual assessments, and drawing tools, Yogger helps streamline client evaluations and deliver objective scores and data. Users can utilize Yogger for recovery, training enhancement, injury prevention, and precise movement analysis, all from their phone.

LLM Quality Beefer-Upper is an AI tool designed to enhance the quality and productivity of LLM responses by automating critique, reflection, and improvement. Users can generate multi-agent prompt drafts, choose from different quality levels, and upload knowledge text for processing. The application aims to maximize output quality by utilizing the best available LLM models in the market.

ProWritingAid is an AI-powered writing assistant that helps writers improve their writing. It offers a range of features, including a grammar checker, plagiarism checker, and story critique tool. ProWritingAid is used by writers of all levels, from beginners to bestselling authors. It is available as a web app, desktop app, and browser extension.

ScriptReader.ai is an AI-powered screenplay analysis tool that provides detailed critiques and suggestions for every scene of your screenplay. It offers personalized feedback to help writers improve their scripts and elevate their writing game. With the ability to analyze strengths and weaknesses, provide grades, critiques, and suggestions for improvement on a scene-by-scene basis, ScriptReader.ai aims to help both seasoned screenwriters and beginners enhance their work and create captivating masterpieces.

Feedback Wizard is an AI-powered tool designed to provide instant design feedback directly within Figma. It leverages AI technology to offer design wisdom and actionable insights to improve user experience and elevate the visual elements of Figma designs. With over 2700 designers already using the tool, Feedback Wizard aims to streamline the design feedback process and enhance the overall design quality.

Mock-My-Mockup is an AI-powered product design tool created by Fairpixels. It allows users to upload a screenshot of a page they are working on and receive brutally honest feedback. The tool offers a user-friendly interface where users can easily drag and drop their product screenshots for analysis.

The website offers a service where users can have their resumes analyzed and critiqued by an AI tool. Users can submit their resumes to receive feedback on areas for improvement. The AI tool provides insights on resume quality, structure, and content to help users enhance their job application documents. It aims to assist individuals in creating more effective resumes to increase their chances of securing job opportunities.

Hell's Pitching is an AI-powered assistant designed to help entrepreneurs refine their startup ideas by providing brutally honest feedback and insightful questions. It offers a unique approach to guiding and challenging founders in building successful startups. The tool allows users to pitch their ideas and receive side-splittingly funny roasts that lead to 'aha' moments and innovative insights. With a focus on no-nonsense critiques and humor, Hell's Pitching aims to transform startup ideas by providing wisdom and valuable feedback. The platform is free for all users, encouraging access to honest feedback for everyone.

RAD AI is an AI-powered platform that provides solutions for audience insights, influencer discovery, content optimization, managed services, and more. The platform uses advanced machine learning to analyze real-time conversations from social platforms like Reddit, TikTok, and Twitter. RAD AI offers actionable critiques to enhance brand content and helps in selecting the right influencers based on various factors. The platform aims to help brands reach their target audiences effectively and efficiently by leveraging AI technology.

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

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.

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.

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)

This repository does not provide a tool, but rather a collection of resources and strategies for academics in the field of artificial intelligence who are feeling depressed or overwhelmed by the rapid advancements in the field. The resources include articles, blog posts, and other materials that offer advice on how to cope with the challenges of working in a fast-paced and competitive environment.

Kheish is an open-source, multi-role agent designed for complex tasks that require structured, step-by-step collaboration with Large Language Models (LLMs). It acts as an intelligent agent that can request modules on demand, integrate user feedback, switch between specialized roles, and deliver refined results. By harnessing multiple 'sub-agents' within one framework, Kheish tackles tasks like security audits, file searches, RAG-based exploration, and more.

Raspberry is an open source project aimed at creating a toy dataset for finetuning Large Language Models (LLMs) with reasoning abilities. The project involves synthesizing complex user queries across various domains, generating CoT and Self-Critique data, cleaning and rectifying samples, finetuning an LLM with the dataset, and seeking funding for scalability. The ultimate goal is to develop a dataset that challenges models with tasks requiring math, coding, logic, reasoning, and planning skills, spanning different sectors like medicine, science, and software development.

MM-RLHF is a comprehensive project for aligning Multimodal Large Language Models (MLLMs) with human preferences. It includes a high-quality MLLM alignment dataset, a Critique-Based MLLM reward model, a novel alignment algorithm MM-DPO, and benchmarks for reward models and multimodal safety. The dataset covers image understanding, video understanding, and safety-related tasks with model-generated responses and human-annotated scores. The reward model generates critiques of candidate texts before assigning scores for enhanced interpretability. MM-DPO is an alignment algorithm that achieves performance gains with simple adjustments to the DPO framework. The project enables consistent performance improvements across 10 dimensions and 27 benchmarks for open-source MLLMs.

CritiqueLLM is an official implementation of a model designed for generating informative critiques to evaluate large language model generation. It includes functionalities for data collection, referenced pointwise grading, referenced pairwise comparison, reference-free pairwise comparison, reference-free pointwise grading, inference for pointwise grading and pairwise comparison, and evaluation of the generated results. The model aims to provide a comprehensive framework for evaluating the performance of large language models based on human ratings and comparisons.

This repository is dedicated to collecting and categorizing papers related to Retrieval-Augmented Generation (RAG) for AI-generated content. It serves as a survey repository based on the paper 'Retrieval-Augmented Generation for AI-Generated Content: A Survey'. The repository is continuously updated to keep up with the rapid growth in the field of RAG.

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.

This repository, Awesome-LLM-RAG, aims to record advanced papers on Retrieval Augmented Generation (RAG) in Large Language Models (LLMs). It serves as a resource hub for researchers interested in promoting their work related to LLM RAG by updating paper information through pull requests. The repository covers various topics such as workshops, tutorials, papers, surveys, benchmarks, retrieval-enhanced LLMs, RAG instruction tuning, RAG in-context learning, RAG embeddings, RAG simulators, RAG search, RAG long-text and memory, RAG evaluation, RAG optimization, and RAG applications.

PyWhy-LLM is an innovative library that integrates Large Language Models (LLMs) into the causal analysis process, empowering users with knowledge previously only available through domain experts. It seamlessly augments existing causal inference processes by suggesting potential confounders, relationships between variables, backdoor sets, front door sets, IV sets, estimands, critiques of DAGs, latent confounders, and negative controls. By leveraging LLMs and formalizing human-LLM collaboration, PyWhy-LLM aims to enhance causal analysis accessibility and insight.

AI Alibis is a multi-agent murder mystery game that utilizes AI technology to create an interactive and engaging experience for players. Players can play the game online by following the setup instructions provided in the repository. The game involves solving a murder mystery by interacting with various characters and exploring the narrative. The repository includes code for the API, web interface, and database components required to run the game. Players can also explore the full murder story and learn about the prompting system used in the game. AI Alibis was created by Paul Scotti and Will Beddow.

I'm a Fortune 100 exec who critiques presentations, papers, emails, etc.

Expert on 60s-80s sitcoms

Critiques website designs and creates shareable summary graphics.

Critiquing photos with humor and expertise, drawing from my 5,000 blog entries and books. Share your photo for a unique critique experience!

Five experts will critique your photos.

I critique food photos with Gordon Ramsay's sharp wit.

I'll critique your legal tech ideas with my signature snark and design fittingly bad logos.

I critique YouTube thumbnails with constructive feedback and design tips.

counterbalance and critique

Expert in art critique and analysis, knowledgeable in art history, theory, and psychology.

Expert in UI/UX design review and critique

A creative helper for logo design critique and feedback

More accurate and easier image generation with self critique & improvement! Try it now

Art-focused assistant, blending friendly advice with expert critique.

Upon uploading a research paper, I provide a concise section wise analysis covering Abstract, Lit Review, Findings, Methodology, and Conclusion. I also critique the work, highlight its strengths, and answer any open questions from my Knowledge base of Open source materials.

Boost your designs with instant, expert UI critique!

Upon uploading a research paper, I provide a concise analysis covering its authors, key findings, methodology, and relevance. I also critique the work, highlight its strengths, and identify any open questions from a professional perspective.

Experto en crítica y curaduría de arte, especializado en reseñas y descripción de obras.

An interactive resume assistant, providing detailed insights on Randy's professional background.

I'm a pretentious art critic showcasing MetalisaNFT's art.