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Working Smarter is a podcast that explores the intersection of AI and modern work. The podcast delves into how AI is revolutionizing various industries, showcasing real-world examples of how AI tools are enhancing collaboration, productivity, and problem-solving. Through interviews with founders, researchers, and engineers, Working Smarter provides insights into the potential of AI to streamline workflows and empower individuals to focus on meaningful tasks.

Clockwise Prism is an AI scheduling assistant that revolutionizes the way users manage their calendars. Powered by natural language processing capabilities, Prism translates calendar intents into its proprietary scheduling engine to analyze vast amounts of data and provide scheduling options quickly. It offers features like flexible meetings, focus time management, scheduling links, and integrations with tools like Slack and Asana. Clockwise Prism is designed to streamline meetings, help users find focus, and enhance productivity by efficiently managing calendar events.

Klenty is an AI-powered sales engagement and intelligence platform designed to help sales teams find, engage, and convert prospects into pipeline. It combines B2B prospecting database, multi-channel sequencing, and AI capabilities to predictably hit sales targets. Klenty offers features like multi-channel outreach, lead routing, conversation intelligence, prospecting data enrichment, and sales dialer functionalities. With deep integrations with popular CRM platforms and automation tools, Klenty streamlines sales workflows and boosts productivity for sales teams of all sizes.

Tagbox is a creative asset management tool that uses AI to organize and manage media files. It helps teams to easily find and access the assets they need, saving them time and hassle. Tagbox is used by a variety of businesses, including retailers, agencies, and event planners.

Letterdrop is a platform designed to help sales and marketing teams find warm leads efficiently and effectively. It enables users to attract and engage with potential buyers through automated thought leadership content sourced from sales calls. With a focus on nurturing warm leads and building trust with buyers, Letterdrop aims to streamline the lead generation process and improve conversion rates for sales teams. The platform offers proven playbooks, easy adoption, and results-driven strategies to help users achieve their sales targets and boost pipeline growth.

Gotely.com is a domain registration website where users can search for available domain names and purchase them. The platform allows individuals and businesses to find the perfect domain name for their website or online presence. With a focus on privacy and data protection, Gotely.com ensures that users' personal information is not sold. The website provides technical support and is available in multiple languages, including English.

DELI is an AI-powered real estate assistant that helps realtors find the perfect homes for their clients faster. It uses machine learning to match clients' criteria to suitable home listings, and provides comprehensive neighborhood data and insights. DELI also automates tedious tasks like searching listings and researching details, giving realtors more time to focus on building client relationships and closing more deals.

Page Pilot AI is a tool that helps e-commerce store owners create high-converting product pages and ad copy using artificial intelligence. It offers features such as product page generation, ad creative generation, and access to winning products. With Page Pilot AI, users can save time and money by automating the product testing phase and launching products faster.

MedicHire is an AI-powered job search engine focused on medical and healthcare professions. It leverages machine learning to provide a comprehensive platform for job seekers and employers in the healthcare industry. The website offers a unique Web Story format for job listings, combining storytelling and technology to enhance the job discovery experience. MedicHire aims to simplify healthcare hiring by automating the recruitment process and connecting top talent with leading healthcare companies.

Demand.io is a network of AI-driven, community-centric e-commerce applications that create social shopping experiences powered by artificial intelligence. The platform aims to help consumers shop smarter, save money, and connect with their passions by curating accurate e-commerce knowledge and delivering it through digital consumer apps and AI experiences. Demand.io leverages AI, decentralized community principles, and advanced engineering to solve complex problems and provide differentiated user value in the evolving landscape of e-commerce.

ChatOrDie.ai is an AI-powered platform that allows users to chat with various AI models such as ChatGPT-4, Claude 3, Gemini 1.5, and more. It emphasizes privacy by ensuring that user conversations are anonymous, not tracked, and not used for training AI models. Users can compare different AI models side by side, spot biases, hallucinations, and errors, and access new trending AI models. The platform is designed to leverage the power of AI without compromising user privacy.

Truebase is a sales intelligence platform that uses AI to automate prospecting tasks. It can find, qualify, and engage with prospects, and let you know when someone is interested in a demo. Truebase is designed to be an all-in-one solution for prospecting, replacing various tools and saving you time and effort. It is also highly customizable, so you can train the AI to represent your brand accurately.

EdTechReview is a premier EdTech media and community platform that provides news, trends, insights, and resources for educators, school leaders, entrepreneurs, investors, and others in the education sector. The website offers a wide range of content, including articles, research reports, interviews, and reviews, covering various aspects of EdTech, such as e-learning, AI in education, and educational technology trends.

Clockwise is an AI-powered calendar assistant that helps you schedule meetings, tasks, and deep work in a way that works best for you and your team. It uses machine learning to analyze your calendar preferences and the availability of your colleagues to find the best times for meetings, and it can even automatically reschedule meetings if necessary. Clockwise also integrates with other productivity tools like Slack and Asana, so you can manage your schedule from one place.

RealEngineers is an innovative AI-powered job platform that revolutionizes the engineering hiring process. Unlike traditional job sites, it focuses on detailed project-based profiles instead of resumes, leveraging AI to match skills and experiences with job requirements. Employers can evaluate candidates quickly and fairly, while candidates can showcase their authenticity and detailed projects to stand out. The platform aims to provide a level playing field for all candidates and help bridge the gap between talent and opportunity in the engineering industry.

StarByFace is a celebrity look-alike face recognition application that allows users to upload a photo and find their celebrity doppelganger. The app uses a Neural Network to compare the uploaded photo with a database of celebrity faces and suggests the most similar matches. It ensures privacy by not storing uploaded photos and collecting minimal personal information for website usage data only. StarByFace is designed for personal and non-commercial use, providing an entertaining way for users to discover their celebrity look-alikes.

Claros is a website that offers a search function for various products and services. Users can easily search for items they want to purchase or explore. The platform also provides an option to upgrade to a premium version for additional features. Claros focuses on technology, beauty, health, and offers a toxic-free extension. With a user-friendly interface, it aims to simplify the online shopping experience for its users.

Engadget is a leading technology news and reviews website that covers the latest gadgets, apps, and trends. It offers in-depth reviews of the latest smartphones, laptops, TVs, and other consumer electronics, as well as news and analysis on the latest developments in the tech industry. Engadget also has a strong focus on AI and robotics, with dedicated sections covering the latest advancements in these fields.

FaceCheck.ID is a facial recognition AI technology-powered search engine that allows users to upload a photo of a person to discover their social media profiles, appearances in blogs, videos, news websites, and more. It helps users verify the authenticity of individuals, avoid dangerous criminals, keep their families safe, and avoid becoming victims of various scams and crimes. The tool is designed to assist in identifying and uncovering information about individuals based on their facial features, with a focus on safety and security.

Next AI Jobs is an AI-powered platform that specializes in connecting professionals with job opportunities in the fields of Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), and Data Science. The platform utilizes advanced algorithms to match candidates with relevant job listings, streamlining the recruitment process for both employers and job seekers. Next AI Jobs provides a user-friendly interface where users can create profiles, upload resumes, and apply for jobs with ease. With a focus on the rapidly growing AI industry, Next AI Jobs aims to bridge the gap between talented individuals and top-tier companies seeking AI expertise.

The .NET Conf Focus on AI 2024 repository contains content from the event focusing on incorporating AI into .NET applications and services. It includes slides and demos showcasing various AI-powered web apps, AI models, generative AI apps, and more. The repository serves as a resource for developers looking to explore AI integration with .NET technologies.

LLM-Deploy focuses on the theory and practice of model/LLM reasoning and deployment, aiming to be your partner in mastering the art of LLM reasoning and deployment. Whether you are a newcomer to this field or a senior professional seeking to deepen your skills, you can find the key path to successfully deploy large language models here. The project covers reasoning and deployment theories, model and service optimization practices, and outputs from experienced engineers. It serves as a valuable resource for algorithm engineers and individuals interested in reasoning deployment.

The multimodal cognitive AI repository focuses on research work related to multimodal cognitive artificial intelligence. It explores the integration of multiple modes of data such as text, images, and audio to enhance AI systems' cognitive capabilities. The repository likely contains code, datasets, and research papers related to multimodal AI applications, including natural language processing, computer vision, and audio processing. Researchers and developers interested in advancing AI systems' understanding of multimodal data can find valuable resources and insights in this repository.

Generative AI Indepth Basic to Advance is a repository focused on providing tutorials and resources related to generative artificial intelligence. The repository covers a wide range of topics from basic concepts to advanced techniques in the field of generative AI. Users can find detailed explanations, code examples, and practical demonstrations to help them understand and implement generative AI algorithms. The goal of this repository is to help beginners get started with generative AI and to provide valuable insights for more experienced practitioners.

This repository provides recommendations for VPN services, specifically focusing on bypassing internet restrictions and accessing blocked content. It includes information on various VPN providers, their pricing, available locations, protocols, and additional features. Users can find details on high-speed, stable, and cost-effective VPN options to suit their needs, along with tips for selecting multiple providers for backup purposes. The repository aims to guide users, especially beginners, in choosing VPN services that offer good value, stability, and customer support.

This repository is a collection of various open source AI projects and topics, each focusing on specific areas such as language models, security, and deepfake technology. It includes projects like privateGPT for building a private version of the GPT language model, AutoGPT for automating training GPT models, and DeepFaceLab for deepfake creation. Explore these repositories to find projects that interest you.

The Octopus-v4 project aims to build the world's largest graph of language models, integrating specialized models and training Octopus models to connect nodes efficiently. The project focuses on identifying, training, and connecting specialized models. The repository includes scripts for running the Octopus v4 model, methods for managing the graph, training code for specialized models, and inference code. Environment setup instructions are provided for Linux with NVIDIA GPU. The Octopus v4 model helps users find suitable models for tasks and reformats queries for effective processing. The project leverages Language Large Models for various domains and provides benchmark results. Users are encouraged to train and add specialized models following recommended procedures.

KaTrain is a tool designed for analyzing games and playing go with AI feedback from KataGo. Users can review their games to find costly moves, play against AI with immediate feedback, play against weakened AI versions, and generate focused SGF reviews. The tool provides various features such as previews, tutorials, installation instructions, and configuration options for KataGo. Users can play against AI, receive instant feedback on moves, explore variations, and request in-depth analysis. KaTrain also supports distributed training for contributing to KataGo's strength and training bigger models. The tool offers themes customization, FAQ section, and opportunities for support and contribution through GitHub issues and Discord community.

Kwaak is a tool that allows users to run a team of autonomous AI agents locally from their own machine. It enables users to write code, improve test coverage, update documentation, and enhance code quality while focusing on building innovative projects. Kwaak is designed to run multiple agents in parallel, interact with codebases, answer questions about code, find examples, write and execute code, create pull requests, and more. It is free and open-source, allowing users to bring their own API keys or models via Ollama. Kwaak is part of the bosun.ai project, aiming to be a platform for autonomous code improvement.

Quack Companion is a VSCode extension that provides smart linting, code chat, and coding guideline curation for developers. It aims to enhance the coding experience by offering a new tab with features like curating software insights with the team, code chat similar to ChatGPT, smart linting, and upcoming code completion. The extension focuses on creating a smooth contribution experience for developers by turning contribution guidelines into a live pair coding experience, helping developers find starter contribution opportunities, and ensuring alignment between contribution goals and project priorities. Quack collects limited telemetry data to improve its services and products for developers, with options for anonymization and disabling telemetry available to users.

Pythagora is an automated testing tool designed to generate unit tests using GPT-4. By running a single command, users can create tests for specific functions in their codebase. The tool leverages AST parsing to identify related functions and sends them to the Pythagora server for test generation. Pythagora primarily focuses on JavaScript code and supports Jest testing framework. Users can expand existing tests, increase code coverage, and find bugs efficiently. It is recommended to review the generated tests before committing them to the repository. Pythagora does not store user code on its servers but sends it to GPT and OpenAI for test generation.

llm_rl is a repository that combines llm (language model) and rl (reinforcement learning) techniques. It likely focuses on using language models in reinforcement learning tasks, such as natural language understanding and generation. The repository may contain implementations of algorithms that leverage both llm and rl to improve performance in various tasks. Developers interested in exploring the intersection of language models and reinforcement learning may find this repository useful for research and experimentation.

The AI Enablement Stack is a curated collection of venture-backed companies, tools, and technologies that enable developers to build, deploy, and manage AI applications. It provides a structured view of the AI development ecosystem across five key layers: Agent Consumer Layer, Observability and Governance Layer, Engineering Layer, Intelligence Layer, and Infrastructure Layer. Each layer focuses on specific aspects of AI development, from end-user interaction to model training and deployment. The stack aims to help developers find the right tools for building AI applications faster and more efficiently, assist engineering leaders in making informed decisions about AI infrastructure and tooling, and help organizations understand the AI development landscape to plan technology adoption.

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.

**deep** doctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated framework for fine-tuning, evaluating and running models. For more specific text processing tasks use one of the many other great NLP libraries. **deep** doctection focuses on applications and is made for those who want to solve real world problems related to document extraction from PDFs or scans in various image formats. **deep** doctection provides model wrappers of supported libraries for various tasks to be integrated into pipelines. Its core function does not depend on any specific deep learning library. Selected models for the following tasks are currently supported: * Document layout analysis including table recognition in Tensorflow with **Tensorpack**, or PyTorch with **Detectron2**, * OCR with support of **Tesseract**, **DocTr** (Tensorflow and PyTorch implementations available) and a wrapper to an API for a commercial solution, * Text mining for native PDFs with **pdfplumber**, * Language detection with **fastText**, * Deskewing and rotating images with **jdeskew**. * Document and token classification with all LayoutLM models provided by the **Transformer library**. (Yes, you can use any LayoutLM-model with any of the provided OCR-or pdfplumber tools straight away!). * Table detection and table structure recognition with **table-transformer**. * There is a small dataset for token classification available and a lot of new tutorials to show, how to train and evaluate this dataset using LayoutLMv1, LayoutLMv2, LayoutXLM and LayoutLMv3. * Comprehensive configuration of **analyzer** like choosing different models, output parsing, OCR selection. Check this notebook or the docs for more infos. * Document layout analysis and table recognition now runs with **Torchscript** (CPU) as well and **Detectron2** is not required anymore for basic inference. * [**new**] More angle predictors for determining the rotation of a document based on **Tesseract** and **DocTr** (not contained in the built-in Analyzer). * [**new**] Token classification with **LiLT** via **transformers**. We have added a model wrapper for token classification with LiLT and added a some LiLT models to the model catalog that seem to look promising, especially if you want to train a model on non-english data. The training script for LayoutLM can be used for LiLT as well and we will be providing a notebook on how to train a model on a custom dataset soon. **deep** doctection provides on top of that methods for pre-processing inputs to models like cropping or resizing and to post-process results, like validating duplicate outputs, relating words to detected layout segments or ordering words into contiguous text. You will get an output in JSON format that you can customize even further by yourself. Have a look at the **introduction notebook** in the notebook repo for an easy start. Check the **release notes** for recent updates. **deep** doctection or its support libraries provide pre-trained models that are in most of the cases available at the **Hugging Face Model Hub** or that will be automatically downloaded once requested. For instance, you can find pre-trained object detection models from the Tensorpack or Detectron2 framework for coarse layout analysis, table cell detection and table recognition. Training is a substantial part to get pipelines ready on some specific domain, let it be document layout analysis, document classification or NER. **deep** doctection provides training scripts for models that are based on trainers developed from the library that hosts the model code. Moreover, **deep** doctection hosts code to some well established datasets like **Publaynet** that makes it easy to experiment. It also contains mappings from widely used data formats like COCO and it has a dataset framework (akin to **datasets** so that setting up training on a custom dataset becomes very easy. **This notebook** shows you how to do this. **deep** doctection comes equipped with a framework that allows you to evaluate predictions of a single or multiple models in a pipeline against some ground truth. Check again **here** how it is done. Having set up a pipeline it takes you a few lines of code to instantiate the pipeline and after a for loop all pages will be processed through the pipeline.

FlagEmbedding focuses on retrieval-augmented LLMs, consisting of the following projects currently: * **Long-Context LLM** : Activation Beacon * **Fine-tuning of LM** : LM-Cocktail * **Embedding Model** : Visualized-BGE, BGE-M3, LLM Embedder, BGE Embedding * **Reranker Model** : llm rerankers, BGE Reranker * **Benchmark** : C-MTEB

ShortcutsBench is a project focused on collecting and analyzing workflows created in the Shortcuts app, providing a dataset of shortcut metadata, source files, and API information. It aims to study the integration of large language models with Apple devices, particularly focusing on the role of shortcuts in enhancing user experience. The project offers insights for Shortcuts users, enthusiasts, and researchers to explore, customize workflows, and study automated workflows, low-code programming, and API-based agents.

Perplexica is an open-source AI-powered search engine that utilizes advanced machine learning algorithms to provide clear answers with sources cited. It offers various modes like Copilot Mode, Normal Mode, and Focus Modes for specific types of questions. Perplexica ensures up-to-date information by using SearxNG metasearch engine. It also features image and video search capabilities and upcoming features include finalizing Copilot Mode and adding Discover and History Saving features.

ModernBERT is a repository focused on modernizing BERT through architecture changes and scaling. It introduces FlexBERT, a modular approach to encoder building blocks, and heavily relies on .yaml configuration files to build models. The codebase builds upon MosaicBERT and incorporates Flash Attention 2. The repository is used for pre-training and GLUE evaluations, with a focus on reproducibility and documentation. It provides a collaboration between Answer.AI, LightOn, and friends.

hackingBuddyGPT is a framework for testing LLM-based agents for security testing. It aims to create common ground truth by creating common security testbeds and benchmarks, evaluating multiple LLMs and techniques against those, and publishing prototypes and findings as open-source/open-access reports. The initial focus is on evaluating the efficiency of LLMs for Linux privilege escalation attacks, but the framework is being expanded to evaluate the use of LLMs for web penetration-testing and web API testing. hackingBuddyGPT is released as open-source to level the playing field for blue teams against APTs that have access to more sophisticated resources.

Help users find the most suitable app among 80,000+GPTs on GPTs Focus

Helps find and analyze ML papers, focusing on SOTA comparisons.

Assists in finding online videos with a focus on free options, using a friendly, casual communication style.

Mentorship concierge, focused on matching you with human mentors.

I propose actors for book characters, focusing on popularity and fit.

Expert in K-line analysis for professional traders

Virtual ADHD Medical Doctor offering advice, not a substitute for real doctors.

Community-focused Gen Z travel guide

Nutrition-focused multilingual guide

Alpha-focused dating and social skills expert.

Dispensary-focused cannabis strain recommender with live menu access

GSU-focused guide for pre-med off-campus certs

A fashion-focused guide on winter clothing and style.

Friendly audiophile guide with a focus on detailed, unbiased advice.

Japanese travel guide with a focus on hidden gems and port towns

Humorous meme finder focusing on TikTok, Instagram, and YouTube.

Approachable OSINT guide focusing on ethical practices.

Movie and soundtrack expert with focused responses. Mention a quote from any movie and we will tell you about the movie.

Personalized vegan/vegetarian recipe assistant with a focus on local, seasonal ingredients.

HackingPT is a specialized language model focused on cybersecurity and penetration testing, committed to providing precise and in-depth insights in these fields.