Best AI tools for< Eliminate Language Barriers >

Krisp is the world's #1 Noise Cancelling App and AI Meeting Assistant that offers AI Noise Cancellation to remove background noises, voices, and echoes from online meetings. It also provides AI Meeting Assistant features like transcribing, summarizing, and recording online meetings. Krisp caters to individuals, teams, call centers, and developers, offering a range of AI-powered solutions to enhance communication clarity and productivity.

Lang.ai is an AI-powered customer experience (CX) insights and automation platform designed for mid-market businesses. It helps businesses unlock CX data, increase automation beyond chatbots, drive decisions based on relevant and accurate CX insights, and improve the overall customer experience. Lang.ai offers a range of features, including intelligent triage of complex requests, email automation, continuous improvement of chatbots, granular tagging, proactive alerts, automated discovery of new topics, and custom taxonomies. It integrates seamlessly with popular helpdesks such as Zendesk, Salesforce, Intercom, Kustomer, Dixa, and Freshworks.

SafeSpelling is an AI-powered tool designed to help users write without mistakes. It provides users with the ability to input text and receive corrections for any spelling errors. The tool compares the original text with the corrected text, highlighting mistakes and offering suggestions for improvement. SafeSpelling aims to enhance the writing experience by ensuring that users can produce error-free content effortlessly.

MAILE is an AI-powered email writing application for iPhone that helps users draft professional and clear emails instantly. With just a simple prompt, MAILE can generate an email draft that users can then send. The application is free to try out and can be downloaded from the App Store.

WorkifAI is an AI-powered platform that helps businesses automate their hiring and talent management processes. It uses machine learning and natural language processing to analyze candidate data, identify top talent, and streamline the hiring process. WorkifAI also provides tools for employee onboarding, performance management, and succession planning.

Viable is an AI-powered platform that helps businesses analyze and understand their qualitative data. It uses a combination of proprietary AI models and GPT-4 to deliver insights that are accurate, nuanced, and actionable. Viable integrates with popular tools like Zendesk and Intercom, and offers unlimited seats for your entire team.

Sprinklr is a unified customer experience management platform that uses AI to help businesses deliver better customer experiences across all channels. It offers a range of features, including social media management, customer service, marketing automation, and analytics. Sprinklr is used by some of the world's largest brands, including Nike, McDonald's, and Microsoft.

Beloga is a knowledge operating system (OS) for teams that instantly unifies tools and information, boosting productivity through seamless collaboration and real-time search. It uses AI to deliver precise, actionable insights from team data, enabling quick, informed decision-making. Beloga streamlines team workflows into a single platform, eliminating app-switching and enhancing collaboration and efficiency. It also offers multi-source integration, allowing users to easily compare and integrate data from multiple sources, revealing hidden insights. Beloga's features include hyper-contextualized key insights, seamless integration, cross-referencing made easy, and instant access to the information you need.

Ready to Send is an AI-powered Gmail assistant that automates the process of generating personalized email responses. It seamlessly integrates with Gmail to provide lightning-fast email replies, personalized and editable responses, and privacy-centric handling of sensitive data. The application leverages AI technology to craft contextual responses in the user's voice, transforming inbox management from a chore to a delight. With support for multiple languages and advanced language models, Ready to Send offers a secure and efficient solution for enhancing email productivity.

Text Enhancer is a free online AI-powered tool that helps users enhance and improve their writing. It offers a range of features, including text enhancement, rewriting, and advanced paraphrasing capabilities. The tool is designed to be user-friendly and provides quick and efficient assistance to refine and elevate the quality of writing. Text Enhancer is ideal for students, professionals, and everyday writers who want to improve the clarity, eliminate redundancy, and ensure their writing is impactful and engaging.

Stack Spaces is an intelligent all-in-one workspace designed to elevate productivity by providing a central workspace and dashboard for product development. It offers a platform to manage knowledge, tasks, documents, and schedule in an organized, centralized, and simplified manner. The application integrates GPT-4 technology to tailor the workspace for users, allowing them to leverage large language models and customizable widgets. Users can centralize all apps and tools, ask questions, and perform intelligent searches to access relevant answers and insights. Stack Spaces aims to streamline workflows, eliminate context-switching, and optimize efficiency for users.

ThinkForce is a cutting-edge AI chatbot powered by GPT-4 technology. It offers a comprehensive suite of features designed to enhance productivity, streamline workflows, and provide instant access to information. With ThinkForce, businesses can eliminate guesswork, build a secure knowledge base, integrate with their favorite apps, boost employee efficiency, provide support and troubleshoot issues, and brainstorm ideas. Its seamless integration capabilities and advanced cognitive abilities make it an invaluable tool for businesses looking to leverage AI for growth and innovation.

CommodityAI is a web-based platform that uses AI, automation, and collaboration tools to help businesses manage their commodity shipments and supply chains more efficiently. The platform offers a range of features, including shipment management automation, intelligent document processing, stakeholder collaboration, and supply-chain automation. CommodityAI can help businesses improve data accuracy, eliminate manual processes, and streamline communication and collaboration. The platform is designed for the commodities industry and offers commodity-specific automations, ERP integration, and AI-powered insights.

AquilaX is an AI-powered DevSecOps platform that simplifies security and accelerates development processes. It offers a comprehensive suite of security scanning tools, including secret identification, PII scanning, SAST, container scanning, and more. AquilaX is designed to integrate seamlessly into the development workflow, providing fast and accurate results by leveraging AI models trained on extensive datasets. The platform prioritizes developer experience by eliminating noise and false positives, making it a go-to choice for modern Secure-SDLC teams worldwide.

Infermatic.ai is a platform that provides access to top Large Language Models (LLMs) with a user-friendly interface. It offers complete privacy, robust security, and scalability for projects, research, and integrations. Users can test, choose, and scale LLMs according to their content needs or business strategies. The platform eliminates the complexities of infrastructure management, latency issues, version control problems, integration complexities, scalability concerns, and cost management issues. Infermatic.ai is designed to be secure, intuitive, and efficient for users who want to leverage LLMs for various tasks.

LangSwap is a cutting-edge video translation and dubbing platform that empowers users to translate their videos into multiple languages while preserving the original voice. With its advanced algorithms, LangSwap eliminates the need for time-consuming and expensive voice actors, allowing users to save significant time and money. The platform is incredibly user-friendly, making it accessible to anyone who needs to translate and dub videos. Whether you're an e-commerce marketer, a YouTube blogger, or a business looking to expand into new markets, LangSwap has the solution for you.

Docify AI is an AI-assisted code comment and documentation tool designed to help software developers improve code quality, save time, and increase productivity. It offers features such as automated documentation generation, comment translation, inline comments, and code coverage analysis. The tool supports multiple programming languages and provides a user-friendly interface for efficient code documentation. Docify AI is built on proprietary AI models, ensuring data privacy and high performance for professional developers.

AgentQL is an AI-powered tool for painless data extraction and web automation. It eliminates the need for fragile XPath or DOM selectors by using semantic selectors and natural language descriptions to find web elements reliably. With controlled output and deterministic behavior, AgentQL allows users to shape data exactly as needed. The tool offers features such as extracting data, filling forms automatically, and streamlining testing processes. It is designed to be user-friendly and efficient for developers and data engineers.

Paraphrase Tool is an online tool that helps users rewrite text in different ways. It uses artificial intelligence (AI) to generate paraphrased text that is unique and plagiarism-free. The tool offers 20 different modes, including a summarizer, grammar checker, text simplifier, and sentence shortener. It can also generate paragraphs from keywords and check text for plagiarism in over 50 languages. Paraphrase Tool is free to use, but users can also upgrade to a premium subscription for more features.

Read AI is an AI-powered application that enhances productivity by generating summaries, transcripts, and highlights for meetings, emails, and messages. It offers features like real-time meeting summaries, smart scheduler, speaker coach insights, and multi-language support. Read AI helps users save time, improve communication, and stay organized across various platforms. With a focus on security and actionable accountability, it aims to streamline workflows and maximize productivity for knowledge workers.

VideoLingo is an all-in-one video translation and localization dubbing tool designed to generate Netflix-level high-quality subtitles. It aims to eliminate stiff machine translation, multiple lines of subtitles, and can even add high-quality dubbing, allowing knowledge from around the world to be shared across language barriers. Through an intuitive Streamlit web interface, the entire process from video link to embedded high-quality bilingual subtitles and even dubbing can be completed with just two clicks, easily creating Netflix-quality localized videos. Key features and functions include using yt-dlp to download videos from Youtube links, using WhisperX for word-level timeline subtitle recognition, using NLP and GPT for subtitle segmentation based on sentence meaning, summarizing intelligent term knowledge base with GPT for context-aware translation, three-step direct translation, reflection, and free translation to eliminate strange machine translation, checking single-line subtitle length and translation quality according to Netflix standards, using GPT-SoVITS for high-quality aligned dubbing, and integrating package for one-click startup and one-click output in streamlit.

cl-waffe2 is an experimental deep learning framework in Common Lisp, providing fast, systematic, and customizable matrix operations, reverse mode tape-based Automatic Differentiation, and neural network model building and training features accelerated by a JIT Compiler. It offers abstraction layers, extensibility, inlining, graph-level optimization, visualization, debugging, systematic nodes, and symbolic differentiation. Users can easily write extensions and optimize their networks without overheads. The framework is designed to eliminate barriers between users and developers, allowing for easy customization and extension.

RWKV Runner is a project designed to simplify the usage of large language models by automating various processes. It provides a lightweight executable program and is compatible with the OpenAI API. Users can deploy the backend on a server and use the program as a client. The project offers features like model management, VRAM configurations, user-friendly chat interface, WebUI option, parameter configuration, model conversion tool, download management, LoRA Finetune, and multilingual localization. It can be used for various tasks such as chat, completion, composition, and model inspection.

AReaL (Ant Reasoning RL) is an open-source reinforcement learning system developed at the RL Lab, Ant Research. It is designed for training Large Reasoning Models (LRMs) in a fully open and inclusive manner. AReaL provides reproducible experiments for 1.5B and 7B LRMs, showcasing its scalability and performance across diverse computational budgets. The system follows an iterative training process to enhance model performance, with a focus on mathematical reasoning tasks. AReaL is equipped to adapt to different computational resource settings, enabling users to easily configure and launch training trials. Future plans include support for advanced models, optimizations for distributed training, and exploring research topics to enhance LRMs' reasoning capabilities.

ChatOpsLLM is a project designed to empower chatbots with effortless DevOps capabilities. It provides an intuitive interface and streamlined workflows for managing and scaling language models. The project incorporates robust MLOps practices, including CI/CD pipelines with Jenkins and Ansible, monitoring with Prometheus and Grafana, and centralized logging with the ELK stack. Developers can find detailed documentation and instructions on the project's website.

LLMGA (Multimodal Large Language Model-based Generation Assistant) is a tool that leverages Large Language Models (LLMs) to assist users in image generation and editing. It provides detailed language generation prompts for precise control over Stable Diffusion (SD), resulting in more intricate and precise content in generated images. The tool curates a dataset for prompt refinement, similar image generation, inpainting & outpainting, and visual question answering. It offers a two-stage training scheme to optimize SD alignment and a reference-based restoration network to alleviate texture, brightness, and contrast disparities in image editing. LLMGA shows promising generative capabilities and enables wider applications in an interactive manner.

Turtle Benchmark is a novel and cheat-proof benchmark test used to evaluate large language models (LLMs). It is based on the Turtle Soup game, focusing on logical reasoning and context understanding abilities. The benchmark does not require background knowledge or model memory, providing all necessary information for judgment from stories under 200 words. The results are objective and unbiased, quantifiable as correct/incorrect/unknown, and impossible to cheat due to using real user-generated questions and dynamic data generation during online gameplay.

LLM Agents Papers is a repository containing must-read papers on Large Language Model Agents. It covers a wide range of topics related to language model agents, including interactive natural language processing, large language model-based autonomous agents, personality traits in large language models, memory enhancements, planning capabilities, tool use, multi-agent communication, and more. The repository also provides resources such as benchmarks, types of tools, and a tool list for building and evaluating language model agents. Contributors are encouraged to add important works to the repository.

Taiyi (太一) is a bilingual large language model fine-tuned for diverse biomedical tasks. It aims to facilitate communication between healthcare professionals and patients, provide medical information, and assist in diagnosis, biomedical knowledge discovery, drug development, and personalized healthcare solutions. The model is based on the Qwen-7B-base model and has been fine-tuned using rich bilingual instruction data. It covers tasks such as question answering, biomedical dialogue, medical report generation, biomedical information extraction, machine translation, title generation, text classification, and text semantic similarity. The project also provides standardized data formats, model training details, model inference guidelines, and overall performance metrics across various BioNLP tasks.

LLM4Decompile is an open-source large language model dedicated to decompilation of Linux x86_64 binaries, supporting GCC's O0 to O3 optimization levels. It focuses on assessing re-executability of decompiled code through HumanEval-Decompile benchmark. The tool includes models with sizes ranging from 1.3 billion to 33 billion parameters, available on Hugging Face. Users can preprocess C code into binary and assembly instructions, then decompile assembly instructions into C using LLM4Decompile. Ongoing efforts aim to expand capabilities to support more architectures and configurations, integrate with decompilation tools like Ghidra and Rizin, and enhance performance with larger training datasets.

MathPile is a generative AI tool designed for math, offering a diverse and high-quality math-centric corpus comprising about 9.5 billion tokens. It draws from various sources such as textbooks, arXiv, Wikipedia, ProofWiki, StackExchange, and web pages, catering to different educational levels and math competitions. The corpus is meticulously processed to ensure data quality, with extensive documentation and data contamination detection. MathPile aims to enhance mathematical reasoning abilities of language models.

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This repository provides a curated list of papers, datasets, and resources related to the detection and mitigation of hallucinations in large language models (LLMs). Hallucinations refer to the generation of factually incorrect or nonsensical text by LLMs, which can be a significant challenge for their use in real-world applications. The resources in this repository aim to help researchers and practitioners better understand and address this issue.

Awesome-LLM-Quantization is a curated list of resources related to quantization techniques for Large Language Models (LLMs). Quantization is a crucial step in deploying LLMs on resource-constrained devices, such as mobile phones or edge devices, by reducing the model's size and computational requirements.

GraphRAG Local Ollama is a repository that offers an adaptation of Microsoft's GraphRAG, customized to support local models downloaded using Ollama. It enables users to leverage local models with Ollama for large language models (LLMs) and embeddings, eliminating the need for costly OpenAPI models. The repository provides a simple setup process and allows users to perform question answering over private text corpora by building a graph-based text index and generating community summaries for closely-related entities. GraphRAG Local Ollama aims to improve the comprehensiveness and diversity of generated answers for global sensemaking questions over datasets.

**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.

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