Best AI tools for< Get To The Ski Resort >

SummarizeYT is a YouTube summary tool that uses ChatGPT to generate summaries of YouTube videos. It is a free and easy-to-use tool that can help you save time and get the most out of your YouTube viewing experience.

BLUF is an AI-powered web page assistant that provides concise answers, summaries, and explanations of web pages. It helps users to quickly and easily get the information they need from any web page, without having to read through irrelevant or unnecessary content. BLUF is available as a browser extension for Chrome and Firefox, and it can be used to summarize or explain any web page with a single click.

Nobinge is a tool that helps you summarize and chat with YouTube videos. It uses artificial intelligence to bypass ads, sponsors, chit-chat, and get to the point. Nobinge also allows you to ask unlimited questions and get unlimited answers about the video you're watching. You can also listen to your summaries thanks to true-to-life voices in a variety of languages. Nobinge is a great tool for anyone who wants to save time and learn faster.

Briefly is an AI-powered briefing platform that helps users write effective briefs faster. It offers features like FastDrafts for quick draft generation, tailored feedback for improvement, personalized effectiveness case studies for inspiration, and business intelligence engine for strategic alignment. The platform ensures compliance, security, and measurable ROI, with fine-grained admin controls and personalized onboarding. Briefly is trusted by marketers worldwide, from startups to Fortune 500 companies, to enhance their marketing strategies and productivity.

Laxis is a revolutionary AI Meeting Assistant designed to capture and distill key insights from every customer interaction effortlessly. It seamlessly integrates across platforms, from online meetings to CRM updates, all with a user-friendly interface. Laxis empowers revenue teams to maximize every customer conversation, ensuring no valuable detail is missed. With Laxis, sales teams can close more deals with AI note-taking and insights from client conversations, business development teams can engage prospects more effectively and grow their business faster, marketing teams can repurpose podcasts, webinars, and meetings into engaging content with a single click, product and market researchers can conduct better research interviews that get to the "aha!" moment faster, project managers can remember key takeaways and status updates, and capture them for progress reports, and product and UX designers can capture and organize insights from their interviews and user research.

Pods.ee is a comprehensive platform that utilizes AI to enhance the podcast listening experience. It offers a range of AI-powered features, including transcripts, mindmaps, summaries, and outlines, enabling users to easily access and understand the key insights from podcasts. With Pods.ee, users can read along with the podcast using AI-generated transcripts, visualize ideas through mindmaps, and get to the point with concise summaries. The platform provides free and paid subscription plans, catering to both individuals and podcast enthusiasts.

Rizemail is an AI-powered email summarization tool that helps users quickly get to the core of their unread newsletters, long email threads, and cluttered commercial communications. By forwarding an email to [email protected], the tool uses AI to summarize the content and returns the key information you need, all within your inbox. Rizemail aims to save users time by providing fast and secure email summarization services, with a focus on user privacy and convenience.

Summary Cat is a YouTube summarizer tool created by Bing Dai in Vancouver, Canada. It allows users to summarize videos and paragraphs into point form. The tool is designed to help users quickly grasp the key points of lengthy content, making it easier to digest and understand. With a user-friendly interface, Summary Cat is a handy tool for anyone looking to save time and get to the core of the information.

InboxChat is an AI-powered email management tool that helps users sort, chat, and summarize their emails. It integrates with Google Accounts and offers a range of features to streamline email workflow, including: - Chat with Your Inbox: Draft emails, summarize lengthy threads, and organize data in tables. - Automate your workflow: Create automations to organize incoming emails, extract important data, create tasks, and prepare automated responses. - Quick skim: See emails at a glance with concise, customizable summaries. - Thread Summary: Get to-the-point summaries of all email threads. - Email Summaries: Quickly skim through emails. - Contact History: Access a summarized timeline of interactions with each contact. - Smart Contact Groups: Auto-tag contacts into manageable groups.

Ask2End is an AI-powered question-answering tool that provides comprehensive and accurate answers to any question you may have. It is designed to be user-friendly and accessible, allowing you to get the information you need quickly and easily.

The AI Blueprint is a weekly newsletter that provides insights and updates on the world of AI and machine learning. Created by Avi Roshkovan, the newsletter covers a range of topics from practical tips to theoretical concepts, making it a valuable resource for startups looking to leverage technology effectively. With a focus on simplicity and practicality, The AI Blueprint aims to demystify AI and make it accessible to a wider audience.

MikeAI is a personalized AI fitness coach designed to help users achieve their fitness goals. It provides personalized meal plans, workout plans, recipes, and access to FitnessGPT, an AI chatbot that can answer fitness-related questions. MikeAI is suitable for both beginners and experienced fitness enthusiasts looking to take their training to the next level.

Mathify is an AI-powered educational platform that aims to make learning accessible, engaging, and rewarding for students across various subjects. With a focus on simplifying complex concepts and personalizing learning experiences, Mathify offers interactive adventures in Mathematics, Science, History, Geography, Languages, Literature, and Social Studies. The platform leverages AI technology to provide tailored support to students, helping them conquer challenges and build a strong foundation in each subject. Mathify's mission is to ignite a passion for learning and unlock the academic potential of every learner.

IntelliBar is an AI-powered assistant for Mac that allows users to ask questions, perform tasks, and edit text from anywhere on their Mac. It is optimized for keyboard use and supports GPT-4, DALL-E, TTS, and Whispers models. IntelliBar is secure by design and sends prompts directly to the OpenAI API.

Collato is an AI assistant designed to help product teams save time on writing documents, answering questions, and generating new content. It can find, summarize, and generate new content based on your own product knowledge, saving you hours in manual work. Collato is also self-hosted, so you can keep your data private and secure.

Cogram is an AI-powered tool that helps teams take notes, track action items, and summarize meetings, emails, and chats. It is designed to help users focus on their highest-impact work by automating the busywork of note-taking and follow-ups. Cogram integrates with popular video conferencing tools such as Zoom, Microsoft Teams, and Google Meet, and can be customized to meet the specific needs of each team. With Cogram, teams can save time, improve communication, and make better decisions.

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.

Kidgeni is an AI-powered creative platform designed for kids to unleash their imagination and turn their inspirations into art, stories, and more. With features like creating doodles, coloring pages, learning to draw, and writing stories, Kidgeni provides endless fun and magical experiences for children. The platform offers various subscription plans with credits that allow users to generate art, stories, and other creative content using AI technology. Kidgeni aims to inspire children to be lifelong learners and creators through engaging and interactive activities.

Retouch4me is an AI-powered photo retouching application that offers a range of tools for enhancing images effortlessly. With features like skin defect fixes, smoothing troubled skin, adding depth to portraits, and more, Retouch4me provides stunning results with minimal effort. The application is designed for both professionals and beginners, allowing users to retouch photos and videos with ease. Retouch4me's AI technology preserves the natural look of the subjects while streamlining the editing process. The application is available as Photoshop plugins and standalone apps, offering powerful retouching capabilities for various purposes.

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DOM to Semantic Markdown is a tool that converts HTML DOM to Semantic Markdown for use in Large Language Models (LLMs). It maximizes semantic information, token efficiency, and preserves metadata to enhance LLMs' processing capabilities. The tool captures rich web content structure, including semantic tags, image metadata, table structures, and link destinations. It offers customizable conversion options and supports both browser and Node.js environments.

The Machine Learning Road Map is a comprehensive guide designed to take individuals from various levels of machine learning knowledge to a basic understanding of machine learning principles using high-quality, free resources. It aims to simplify the complex and rapidly growing field of machine learning by providing a structured roadmap for learning. The guide emphasizes the importance of understanding AI for everyone, the need for patience in learning machine learning due to its complexity, and the value of learning from experts in the field. It covers five different paths to learning about machine learning, catering to consumers, aspiring AI researchers, ML engineers, developers interested in building ML applications, and companies looking to implement AI solutions.

MisguidedAttention is a collection of prompts designed to challenge the reasoning abilities of large language models by presenting them with modified versions of well-known thought experiments, riddles, and paradoxes. The goal is to assess the logical deduction capabilities of these models and observe any shortcomings or fallacies in their responses. The repository includes a variety of prompts that test different aspects of reasoning, such as decision-making, probability assessment, and problem-solving. By analyzing how language models handle these challenges, researchers can gain insights into their reasoning processes and potential biases.

The Cheshire Cat is a framework for building custom AIs on top of any language model. It provides an API-first approach, making it easy to add a conversational layer to your application. The Cat remembers conversations and documents, and uses them in conversation. It is extensible via plugins, and supports event callbacks, function calling, and conversational forms. The Cat is easy to use, with an admin panel that allows you to chat with the AI, visualize memory and plugins, and adjust settings. It is also production-ready, 100% dockerized, and supports any language model.

llm-finetuning is a repository that provides a serverless twist to the popular axolotl fine-tuning library using Modal's serverless infrastructure. It allows users to quickly fine-tune any LLM model with state-of-the-art optimizations like Deepspeed ZeRO, LoRA adapters, Flash attention, and Gradient checkpointing. The repository simplifies the fine-tuning process by not exposing all CLI arguments, instead allowing users to specify options in a config file. It supports efficient training and scaling across multiple GPUs, making it suitable for production-ready fine-tuning jobs.

FoundationaLLM is a platform designed for deploying, scaling, securing, and governing generative AI in enterprises. It allows users to create AI agents grounded in enterprise data, integrate REST APIs, experiment with large language models, centrally manage AI agents and assets, deploy scalable vectorization data pipelines, enable non-developer users to create their own AI agents, control access with role-based access controls, and harness capabilities from Azure AI and Azure OpenAI. The platform simplifies integration with enterprise data sources, provides fine-grain security controls, load balances across multiple endpoints, and is extensible to new data sources and orchestrators. FoundationaLLM addresses the need for customized copilots or AI agents that are secure, licensed, flexible, and suitable for enterprise-scale production.

The discourse-chatbot is an original AI chatbot for Discourse forums that allows users to converse with the bot in posts or chat channels. Users can customize the character of the bot, enable RAG mode for expert answers, search Wikipedia, news, and Google, provide market data, perform accurate math calculations, and experiment with vision support. The bot uses cutting-edge Open AI API and supports Azure and proxy server connections. It includes a quota system for access management and can be used in RAG mode or basic bot mode. The setup involves creating embeddings to make the bot aware of forum content and setting up bot access permissions based on trust levels. Users must obtain an API token from Open AI and configure group quotas to interact with the bot. The plugin is extensible to support other cloud bots and content search beyond the provided set.

AutoGen is a framework that enables the development of LLM applications using multiple agents that can converse with each other to solve tasks. AutoGen agents are customizable, conversable, and seamlessly allow human participation. They can operate in various modes that employ combinations of LLMs, human inputs, and tools.

LLM-Minutes-of-Meeting is a project showcasing NLP & LLM's capability to summarize long meetings and automate the task of delegating Minutes of Meeting(MoM) emails. It converts audio/video files to text, generates editable MoM, and aims to develop a real-time python web-application for meeting automation. The tool features keyword highlighting, topic tagging, export in various formats, user-friendly interface, and uses Celery for asynchronous processing. It is designed for corporate meetings, educational institutions, legal and medical fields, accessibility, and event coverage.

This repository provides a hands-on lab for learning about Neo4j and Google Cloud Vertex AI. It is intended for data scientists and data engineers to deploy Neo4j and Vertex AI in a Google Cloud account, work with real-world datasets, apply generative AI, build a chatbot over a knowledge graph, and use vector search and index functionality for semantic search. The lab focuses on analyzing quarterly filings of asset managers with $100m+ assets under management, exploring relationships using Neo4j Browser and Cypher query language, and discussing potential applications in capital markets such as algorithmic trading and securities master data management.

The vscode-pddl extension provides comprehensive support for Planning Domain Description Language (PDDL) in Visual Studio Code. It enables users to model planning domains, validate them, industrialize planning solutions, and run planners. The extension offers features like syntax highlighting, auto-completion, plan visualization, plan validation, plan happenings evaluation, search debugging, and integration with Planning.Domains. Users can create PDDL files, run planners, visualize plans, and debug search algorithms efficiently within VS Code.

LLM Engineering is an 8-week course designed to help learners master AI and LLMs through a series of projects that gradually increase in complexity. The course covers setting up the environment, working with APIs, using Google Colab for GPU processing, and building an autonomous Agentic AI solution. Learners are encouraged to actively participate, run code cells, tweak code, and share their progress with the community. The emphasis is on practical, educational projects that teach valuable business skills.

Rakis is a decentralized verifiable AI network in the browser where nodes can accept AI inference requests, run local models, verify results, and arrive at consensus without servers. It is open-source, functional, multi-model, multi-chain, and browser-first, allowing anyone to participate in the network. The project implements an embedding-based consensus mechanism for verifiable inference. Users can run their own node on rakis.ai or use the compiled version hosted on Huggingface. The project is meant for educational purposes and is a work in progress.

AnnA is a Python script designed to create filtered decks in optimal review order for Anki flashcards. It uses Machine Learning / AI to ensure semantically linked cards are reviewed far apart. The script helps users manage their daily reviews by creating special filtered decks that prioritize reviewing cards that are most different from the rest. It also allows users to reduce the number of daily reviews while increasing retention and automatically identifies semantic neighbors for each note.

Unstract is a no-code platform that enables users to launch APIs and ETL pipelines to structure unstructured documents. With Unstract, users can go beyond co-pilots by enabling machine-to-machine automation. Unstract's Prompt Studio provides a simple, no-code approach to creating prompts for LLMs, vector databases, embedding models, and text extractors. Users can then configure Prompt Studio projects as API deployments or ETL pipelines to automate critical business processes that involve complex documents. Unstract supports a wide range of LLM providers, vector databases, embeddings, text extractors, ETL sources, and ETL destinations, providing users with the flexibility to choose the best tools for their needs.

Redbox Copilot is a retrieval augmented generation (RAG) app that uses GenAI to chat with and summarise civil service documents. It increases organisational memory by indexing documents and can summarise reports read months ago, supplement them with current work, and produce a first draft that lets civil servants focus on what they do best. The project uses a microservice architecture with each microservice running in its own container defined by a Dockerfile. Dependencies are managed using Python Poetry. Contributions are welcome, and the project is licensed under the MIT License.

LLocal is an Electron application focused on providing a seamless and privacy-driven chatting experience using open-sourced technologies, particularly open-sourced LLM's. It allows users to store chats locally, switch between models, pull new models, upload images, perform web searches, and render responses as markdown. The tool also offers multiple themes, seamless integration with Ollama, and upcoming features like chat with images, web search improvements, retrieval augmented generation, multiple PDF chat, text to speech models, community wallpapers, lofi music, speech to text, and more. LLocal's builds are currently unsigned, requiring manual builds or using the universal build for stability.

Open Data QnA is a Python library that allows users to interact with their PostgreSQL or BigQuery databases in a conversational manner, without needing to write SQL queries. The library leverages Large Language Models (LLMs) to bridge the gap between human language and database queries, enabling users to ask questions in natural language and receive informative responses. It offers features such as conversational querying with multiturn support, table grouping, multi schema/dataset support, SQL generation, query refinement, natural language responses, visualizations, and extensibility. The library is built on a modular design and supports various components like Database Connectors, Vector Stores, and Agents for SQL generation, validation, debugging, descriptions, embeddings, responses, and visualizations.

This repository contains a minimal, clean code implementation of the Byte Pair Encoding (BPE) algorithm, commonly used in LLM tokenization. The BPE algorithm is "byte-level" because it runs on UTF-8 encoded strings. This algorithm was popularized for LLMs by the GPT-2 paper and the associated GPT-2 code release from OpenAI. Sennrich et al. 2015 is cited as the original reference for the use of BPE in NLP applications. Today, all modern LLMs (e.g. GPT, Llama, Mistral) use this algorithm to train their tokenizers. There are two Tokenizers in this repository, both of which can perform the 3 primary functions of a Tokenizer: 1) train the tokenizer vocabulary and merges on a given text, 2) encode from text to tokens, 3) decode from tokens to text. The files of the repo are as follows: 1. minbpe/base.py: Implements the `Tokenizer` class, which is the base class. It contains the `train`, `encode`, and `decode` stubs, save/load functionality, and there are also a few common utility functions. This class is not meant to be used directly, but rather to be inherited from. 2. minbpe/basic.py: Implements the `BasicTokenizer`, the simplest implementation of the BPE algorithm that runs directly on text. 3. minbpe/regex.py: Implements the `RegexTokenizer` that further splits the input text by a regex pattern, which is a preprocessing stage that splits up the input text by categories (think: letters, numbers, punctuation) before tokenization. This ensures that no merges will happen across category boundaries. This was introduced in the GPT-2 paper and continues to be in use as of GPT-4. This class also handles special tokens, if any. 4. minbpe/gpt4.py: Implements the `GPT4Tokenizer`. This class is a light wrapper around the `RegexTokenizer` (2, above) that exactly reproduces the tokenization of GPT-4 in the tiktoken library. The wrapping handles some details around recovering the exact merges in the tokenizer, and the handling of some unfortunate (and likely historical?) 1-byte token permutations. Finally, the script train.py trains the two major tokenizers on the input text tests/taylorswift.txt (this is the Wikipedia entry for her kek) and saves the vocab to disk for visualization. This script runs in about 25 seconds on my (M1) MacBook. All of the files above are very short and thoroughly commented, and also contain a usage example on the bottom of the file.

This repository contains self-trained single image super resolution (SISR) models. The models are trained on various datasets and use different network architectures. They can be used to upscale images by 2x, 4x, or 8x, and can handle various types of degradation, such as JPEG compression, noise, and blur. The models are provided as safetensors files, which can be loaded into a variety of deep learning frameworks, such as PyTorch and TensorFlow. The repository also includes a number of resources, such as examples, results, and a website where you can compare the outputs of different models.

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Ask about your documents to see how you could make them easier to read for everyone and more accessible for people with disabilities. NOTE: It does not always get everything right on the first go. Feel free to hit the regenerate button or ask for more info if you want to get richer feedback.

Automated interviews. To get started, type or say "Let's begin". When you ask the GPT to end the interview it will give you a transcript and summary of your conversation. This is a great way of getting thoughts out of your head and onto "paper". Have fun!

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Show me your job description or just describe what you do professionally, and I'll help you identify high value use cases for AI in your day-to-day work. I'll also coach you on simple techniques to get the best out of ChatGPT.

This GPT can generate code for you. For now it creates full-stack apps using Typescript. Just describe the feature you want and you will get a link to the Github code pull request and the live app deployed.

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