Best AI tools for< Selectively Integrate Data Enhancements >

Podwise is an AI-powered podcast tool that helps users extract structured knowledge from podcasts. It offers features such as AI-powered summarization, mind mapping, outlining, transcription, and integration with popular knowledge management tools. Podwise aims to enhance the podcast listening experience by providing users with a more efficient and effective way to learn and retain information from podcasts.

AIPodNav is an AI-powered tool designed to enhance your podcast listening experience by providing features such as mind maps, summaries, takeaways, keywords, chapters, and transcriptions. It accelerates knowledge acquisition by 10 times faster than traditional podcast listening methods. AIPodNav aims to revolutionize how users engage with podcasts by offering innovative AI-driven functionalities.

Creaition is an AI-powered visual creation tool that allows users to effortlessly create stunning designs in a completely visual workflow. With advanced AI technology, users can explore endless design variations, blend designs seamlessly, and selectively regenerate parts of images while keeping the overall design intact. The tool offers a curated feed of inspirations, a natural design environment, and a personalized palette of ingredients for design freedom. Creaition is revolutionizing the design process by providing a comprehensive overview of the creative journey and enhancing the user experience through cutting-edge AI technology.

Kahuna AI is an AI-powered platform designed to provide superpowers for event-driven investing. It caters to top hedge funds and selectively onboards users daily. The platform is made with love in NYC by Kahuna AI, Inc.

InstaRoom is an AI-based instant interior decoration tool that allows users to design and visualize their rooms effortlessly. The application combines AI design with seamless Photoshop-like editing capabilities, enabling users to transform their spaces with just a few clicks. With over 20 design styles for both interiors and exteriors, InstaRoom offers a wide range of options to cater to different preferences. Users can render exterior architecture from a sketch, add furniture to empty rooms, and selectively redesign specific parts of a room. InstaRoom provides a user-friendly experience, allowing users to capture a photo of their room on any device and immediately start redesigning. The tool has gained popularity among both professionals and amateurs, making interior design accessible to everyone.

Genesis Therapeutics is a cutting-edge platform that leverages molecular AI technology to discover and develop highly potent and selective medicines. Their proprietary Generative AI for Drug Discovery (GEMS) platform combines AI and physics research to identify drug candidates against challenging targets with unprecedented speed and accuracy. The company's innovative approach, powered by collaborative minds across AI and biotech, is revolutionizing the drug discovery process.

DeepSwapper is a free online AI tool that allows users to instantly swap faces in photos and videos. With high-quality and realistic results, users can easily swap faces with celebrities, models, or friends. The tool offers single and multiple face swapping options, clear and realistic video face swaps, and versatile usage for social media, product promotions, or fun. DeepSwapper guarantees instant results, multiple face swaps in one click, and selective face swapping for group photos. Users can enjoy the service for free or opt for premium features for enhanced experience.

Joba is an AI-powered platform that revolutionizes the future of work by empowering individuals to curate their identity and find opportunities in a decentralized job marketplace. It utilizes blockchain technology to ensure trustless hiring through on-chain contracts and offers features like invoice tracking, borderless credentials, and crypto payments. Joba aims to provide financial inclusion for remote workers and boasts a highly selective process with a 98% trial-to-hire success rate. The platform is user-friendly, secure, and fosters a global community of top talents and innovative companies.

Reflection-Tuning is a project focused on improving the quality of instruction-tuning data through a reflection-based method. It introduces Selective Reflection-Tuning, where the student model can decide whether to accept the improvements made by the teacher model. The project aims to generate high-quality instruction-response pairs by defining specific criteria for the oracle model to follow and respond to. It also evaluates the efficacy and relevance of instruction-response pairs using the r-IFD metric. The project provides code for reflection and selection processes, along with data and model weights for both V1 and V2 methods.

This repository is dedicated to the pruning of large language models (LLMs). It aims to serve as a comprehensive resource for researchers and practitioners interested in the efficient reduction of model size while maintaining or enhancing performance. The repository contains various papers, summaries, and links related to different pruning approaches for LLMs, along with author information and publication details. It covers a wide range of topics such as structured pruning, unstructured pruning, semi-structured pruning, and benchmarking methods. Researchers and practitioners can explore different pruning techniques, understand their implications, and access relevant resources for further study and implementation.

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 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.

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.

A collection of papers related to knowledge distillation of large language models (LLMs). The repository focuses on techniques to transfer advanced capabilities from proprietary LLMs to smaller models, compress open-source LLMs, and refine their performance. It covers various aspects of knowledge distillation, including algorithms, skill distillation, verticalization distillation in fields like law, medical & healthcare, finance, science, and miscellaneous domains. The repository provides a comprehensive overview of the research in the area of knowledge distillation of LLMs.

This repository contains a collection of papers related to tool learning with large language models (LLMs). The papers are organized according to the survey paper 'Tool Learning with Large Language Models: A Survey'. The survey focuses on the benefits and implementation of tool learning with LLMs, covering aspects such as task planning, tool selection, tool calling, response generation, benchmarks, evaluation, challenges, and future directions in the field. It aims to provide a comprehensive understanding of tool learning with LLMs and inspire further exploration in this emerging area.

Recent LLM (Large Language Models)-based CV and multi-modal works.

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.

Creates detailed vintage illustrations with selective color highlights.