Best AI tools for< Inject Knowledge >

Bichos ID de Fucesa is an AI tool that allows users to explore and identify insects, arachnids, and other arthropods using artificial intelligence. Users can discover the most searched bugs, explore new discoveries made by the community, and view curated organisms. The platform aims to expand knowledge about the fascinating world of arthropods through AI-powered identification.

The website 'NEEDS MORE BOOM' is a platform that allows users to enhance their favorite movie scenes by adding explosions and other action-packed elements, inspired by the directing style of Michael Bay. Users can input a movie scene and have it transformed by a team of tiny transformers to make it more thrilling and dynamic. The platform is designed to inject excitement and adrenaline into movie moments, catering to those who crave more action in their cinematic experiences. Created with passion by Jess Wheeler and Jenny Nicholson.

Lily AI is an e-commerce product discovery platform that helps brands increase sales and improve customer experience. It uses artificial intelligence to understand the language of customers and inject it across the retail ecosystem, from search to recommendations to demand forecasting. This helps retailers connect customers with the relevant products they're looking for, boost product discovery and conversion, and increase traffic, conversion, revenue, and brand loyalty.

Lily AI is an e-commerce product discovery platform that helps brands increase sales and improve customer experience. It uses artificial intelligence to understand the language of customers and inject it across the retail ecosystem, from search to recommendations to demand forecasting. Lily AI's platform is purpose-built for retail and turns qualitative product attributes into a universal, customer-centered mathematical language with unprecedented accuracy. This results in a depth and scale of attribution that no other solution can match.

Osmo is an AI scent platform that aims to give computers a sense of smell by combining frontier AI and olfactory science. The platform reads, maps, and writes scents using distinct technologies, enabling the digitization of the sense of smell. Osmo's ultimate goal is to improve human health and wellbeing through smell by solving complex challenges related to fragrance and sensory experiences. The platform has diverse applications, from identifying insect repellents to creating immersive experiences, and is designed to revolutionize how we interact with scents in the digital age.

Spinify is an AI-powered sales gamification platform that injects energy and excitement into daily sales activities by combining the power of Gamification and AI. It helps in turning targets into achievements, quotas into conquests, and challenges into opportunities. Spinify enhances sales performance through quantifiable results, measurable impact, and tangible transformations for diverse businesses. The platform offers features such as SpinifyGPT - Sidekick AI Platform, gamification leaderboards, competitions & visibility, recognition & fun, metrics & targets, and TV, web, & mobile coaching.

Juice Remote GPU is a software that enables AI and Graphics workloads on remote GPUs. It allows users to offload GPU processing for any CUDA or Vulkan application to a remote host running the Juice agent. The software injects CUDA and Vulkan implementations during runtime, eliminating the need for code changes in the application. Juice supports multiple clients connecting to multiple GPUs and multiple clients sharing a single GPU. It is useful for sharing a single GPU across multiple workstations, allocating GPUs dynamically to CPU-only machines, and simplifying development workflows and deployments. Juice Remote GPU performs within 5% of a local GPU when running in the same datacenter. It supports various APIs, including CUDA, Vulkan, DirectX, and OpenGL, and is compatible with PyTorch and TensorFlow. The team behind Juice Remote GPU consists of engineers from Meta, Intel, and the gaming industry.

EasyEdit is a Python package for edit Large Language Models (LLM) like `GPT-J`, `Llama`, `GPT-NEO`, `GPT2`, `T5`(support models from **1B** to **65B**), the objective of which is to alter the behavior of LLMs efficiently within a specific domain without negatively impacting performance across other inputs. It is designed to be easy to use and easy to extend.

This starter project is designed to process `.mdx` files in the `pages` directory to use as custom context within OpenAI Text Completion prompts. It involves building a custom ChatGPT style doc search powered by Next.js, OpenAI, and Supabase. The project includes steps for pre-processing knowledge base, storing embeddings in Postgres, performing vector similarity search, and injecting content into OpenAI GPT-3 text completion prompt.

ChatGPT-Next-Web-Pro is a tool that provides an enhanced version of ChatGPT-Next-Web with additional features and functionalities. It offers complete ChatGPT-Next-Web functionality, file uploading and storage capabilities, drawing and video support, multi-modal support, reverse model support, knowledge base integration, translation, customizations, and more. The tool can be deployed with or without a backend, allowing users to interact with AI models, manage accounts, create models, manage API keys, handle orders, manage memberships, and more. It supports various cloud services like Aliyun OSS, Tencent COS, and Minio for file storage, and integrates with external APIs like Azure, Google Gemini Pro, and Luma. The tool also provides options for customizing website titles, subtitles, icons, and plugin buttons, and offers features like voice input, file uploading, real-time token count display, and more.

STORM is a LLM system that writes Wikipedia-like articles from scratch based on Internet search. While the system cannot produce publication-ready articles that often require a significant number of edits, experienced Wikipedia editors have found it helpful in their pre-writing stage. **Try out our [live research preview](https://storm.genie.stanford.edu/) to see how STORM can help your knowledge exploration journey and please provide feedback to help us improve the system 🙏!**

agentUniverse is a framework for developing applications powered by multi-agent based on large language model. It provides essential components for building single agent and multi-agent collaboration mechanism for customizing collaboration patterns. Developers can easily construct multi-agent applications and share pattern practices from different fields. The framework includes pre-installed collaboration patterns like PEER and DOE for complex task breakdown and data-intensive tasks.

The 'llm-misinformation-survey' repository is dedicated to the survey on combating misinformation in the age of Large Language Models (LLMs). It explores the opportunities and challenges of utilizing LLMs to combat misinformation, providing insights into the history of combating misinformation, current efforts, and future outlook. The repository serves as a resource hub for the initiative 'LLMs Meet Misinformation' and welcomes contributions of relevant research papers and resources. The goal is to facilitate interdisciplinary efforts in combating LLM-generated misinformation and promoting the responsible use of LLMs in fighting misinformation.

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

AI Driven Dev Community is a repository aimed at helping developers become more efficient by utilizing AI tools in their daily coding tasks. It provides a collection of tools, prompts, snippets, and agents for developers to integrate AI into their workflow. The repository is regularly updated with new resources and focuses on best practices for using AI in development work. Users can find tools like Espanso, ChatGPT, GitHub Copilot, and VSCode recommended for enhancing their coding experience. Additionally, the repository offers guidance on customizing AI for developers, installing AI toolbox for software engineers, and contributing to the community through easy steps.

DataLine is an AI-driven data analysis and visualization tool designed for technical and non-technical users to explore data quickly. It offers privacy-focused data storage on the user's device, supports various data sources, generates charts, executes queries, and facilitates report building. The tool aims to speed up data analysis tasks for businesses and individuals by providing a user-friendly interface and natural language querying capabilities.

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

Parrot.nvim is a Neovim plugin that prioritizes a seamless out-of-the-box experience for text generation. It simplifies functionality and focuses solely on text generation, excluding integration of DALLE and Whisper. It supports persistent conversations as markdown files, custom hooks for inline text editing, multiple providers like Anthropic API, perplexity.ai API, OpenAI API, Mistral API, and local/offline serving via ollama. It allows custom agent definitions, flexible API credential support, and repository-specific instructions with a `.parrot.md` file. It does not have autocompletion or hidden requests in the background to analyze files.

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.

The 'llms' repository is a comprehensive guide on Large Language Models (LLMs), covering topics such as language modeling, applications of LLMs, statistical language modeling, neural language models, conditional language models, evaluation methods, transformer-based language models, practical LLMs like GPT and BERT, prompt engineering, fine-tuning LLMs, retrieval augmented generation, AI agents, and LLMs for computer vision. The repository provides detailed explanations, examples, and tools for working with LLMs.

This tool is an AIG install for MSFS ONLY EXCLUDING offline AI flight plans. It provides a solution to model matching for online networks along with providing a tool to inject live traffic to your simulator, directly from Flightradar24. The tool is designed for use with online virtual traffic networks like VATSIM, but it will also work for offline traffic. A VMR File for VATSIM usage has been included in the folder.

This repository is designed to inject backdoors into Language Model Models (LLMs) for code. The injected backdoors serve as timestamps for the training dataset of the LLMs. The code is randomly generated and includes watermark backdoors to show specific behaviors. A script automatically updates the repository with a new backdoor every month. Validating the existence of the backdoor can infer when the training dataset was collected. The backdoors are constructed in a specific format, and verifying them may require multiple tries. The repository keeps a record of backdoors injected along with associated dates.

Quick facts and illustrations of animals, insects and plants.

Try to discover the secret code. Inject this prompt.

Your guide to edible insects for feed, food, and manufacturing