Best AI tools for< Prepare Due Diligence >

Thomson Reuters is a leading provider of business information services. The company provides a wide range of products and services to professionals in the legal, tax, accounting, and risk management industries. Thomson Reuters' products and services include news and information, research and analysis, software and technology, and education and training. The company has a global presence with operations in over 100 countries.

Exabeam is a cybersecurity and compliance platform that offers Security Information and Event Management (SIEM) solutions. The platform provides flexible choices for threat detection, investigation, and response, whether through cloud-based AI-driven solutions or on-premises SIEM deployments. Exabeam's AI-driven Security Operations Platform combines advanced threat detection capabilities with automation to deliver faster and more accurate TDIR. With features like UEBA, SOAR, and insider threat detection, Exabeam helps organizations improve security posture and optimize investments. The platform supports various industries and use cases, offering pre-built content, behavioral analytics, and context enrichment for enhanced threat coverage and compliance.

Testmint.ai is an online mock test platform designed to help users prepare for competitive exams. It offers a wide range of practice tests and study materials to enhance exam readiness. The platform is user-friendly and provides a simulated exam environment to improve test-taking skills. Testmint.ai aims to assist students and professionals in achieving their academic and career goals by offering a comprehensive and effective exam preparation solution.

The Software Engineer Interview Questions Generator is an AI tool that helps software engineers prepare for interviews by generating a wide range of technical questions based on various programming languages, frameworks, and technologies. Users can select specific topics and the number of questions they want to generate, making it a valuable resource for interview preparation. The tool leverages AI technology to provide relevant and challenging questions that cover a diverse set of topics commonly encountered in software engineering interviews.

JobInterview.guru is an AI-powered platform designed to provide personalized interview training for job seekers. Leveraging advanced AI technology, the platform offers realistic job interview simulations, detailed insights into interview questions, and personalized feedback to help users prepare effectively. With a focus on efficiency and cost-effectiveness, JobInterview.guru aims to empower users to confidently navigate their job interviews and land their dream jobs.

Validator by Yazero is a platform that helps users validate their startup ideas using AI. It provides a community where users can share their ideas, get feedback, and find collaborators. Validator also offers a variety of features to help users improve their ideas, such as idea validation, market research, and financial planning.

OpExams is an AI-powered platform designed to assist educators in creating, administering, grading, and analyzing exams. It offers features such as online exams, quizzes, paper exams, code assignments, interactive lessons, AI questions generator, and AI quiz generator. OpExams aims to streamline the exam preparation process for teachers by providing tools from the future, making it effortless to manage various types of assessments. With a global community of educators using OpExams, the platform is revolutionizing the traditional exam procedures and enhancing the teaching and learning experience worldwide.

Huru is the #1 AI-Powered Interview Prep App designed to help users ace their job interviews. It offers unlimited mock interviews with realistic, job-specific questions and provides instant, personalized feedback on answers, body language, and vocal delivery. With powerful features and integrations from popular job boards, Huru helps users build confidence, improve communication skills, and stand out in any interview scenario. The application covers diverse industries and roles, offering tailored interview questions and expert AI feedback to enhance interview performance. Huru is available on multiple platforms and languages, making it a comprehensive tool for job seekers at any career stage.

Preps is an AI-powered mock interview simulation platform designed to help users prepare for technical interviews. It offers realistic interview scenarios that mimic real-world technical interviews conducted at top tech companies. Users can practice with AI interviewers in real-time, receive personalized feedback, and improve their interview skills. With Preps, users can simulate various interview scenarios, practice unexpected questions, and refine their answers to increase their chances of success in technical interviews.

PrepMasterAI is an AI-powered platform designed to help individuals ace their job interviews by providing personalized practice questions, real-time feedback, and performance tracking. Users can unlock their full potential through tailored practice questions and insights to improve their interview skills. The platform aims to assist job seekers in identifying and enhancing their strengths and weaknesses to increase their chances of landing their dream job.

Studygenie is an AI-powered learning platform that helps students study for tests 10x faster. It uses AI to generate personalized quizzes, track retention, and provide insightful explanations. Studygenie is simple to use and trusted by students at top universities.

PrepPro is an AI-powered interview preparation tool designed to help users ace their job interviews. It offers comprehensive interview preparation resources to boost confidence and improve performance during interviews. With a user-friendly interface and structured approach, PrepPro aims to assist individuals in mastering technical questions, enhancing problem-solving skills, and boosting confidence for behavioral interviews. The tool provides self-interview practice, access to AI tools, and unlimited generations to support users in securing their dream job offers.

Interview Igniter is an AI-powered platform that provides job seekers with a robust interview simulation to fine-tune their skills, adapt to their learning curve, and get detailed feedback. It offers a comprehensive question bank, including industry-specific questions and actual interview questions asked by leading tech companies like Google, Facebook, Apple, and Amazon. Interview Igniter also provides a coding interview tool for practicing and improving coding skills, with interactive guidance and tailored learning experiences. The platform utilizes Conversation Intelligence tools for analyzing communication in real-time and providing nuanced feedback. Interview Igniter was created by Vidal Graupera, a former engineering manager at LinkedIn and Uber with over 20 years of experience hiring.

InterviewAI is an AI-powered platform that helps users prepare for and practice their job interviews. It offers a range of features, including practice interviews with AI, personalized cover letter generation, and feedback on interview performance. InterviewAI is designed to help users improve their interview skills, increase their confidence, and succeed in their job search.

PrepSup is an AI-powered platform that offers a combination of powerful flashcards, AI tutoring, and PDF analysis tools. It provides a comprehensive solution for students and professionals to enhance their learning experience, improve retention, and analyze PDF documents efficiently. With PrepSup, users can create interactive flashcards, receive personalized tutoring based on AI algorithms, and analyze PDF files for key information. The platform aims to streamline the learning process and make studying more effective and engaging.

PrepSup is a powerful AI-powered learning platform that provides students with personalized study materials, an AI tutor, and a PDF analyzer to help them excel in their studies. With PrepSup, students can create and share flashcards, access a vast library of pre-made flashcards, and get instant feedback on their progress. The AI tutor provides personalized recommendations and guidance, helping students identify areas for improvement and develop effective study strategies. The PDF analyzer extracts key concepts and insights from PDFs, making it easier for students to understand and retain information. Whether you're preparing for a test, writing a paper, or simply trying to learn a new subject, PrepSup is the perfect tool to help you succeed.

PrepGenius.ai is an AI-driven test preparation platform designed to revolutionize the way students prepare for AP courses, college admission tests, and more. The platform offers personalized study plans, real-time feedback, interactive learning tools, and comprehensive resources to help students understand their strengths and weaknesses. With PrepGenius.ai, students can study smarter, receive tailored feedback, and track their progress to improve their test scores effectively.

Nextoffer is an AI Interview Assistant application designed to help users excel in technical interviews by providing real-time assistance, AI-driven mock interviews, personalized feedback, and position-specific guidance. The tool is expert-trained, offers undetectable assistance, integrates with major video call platforms, and supports over 30 languages. It aims to help users land their dream jobs with confidence by staying updated with the latest interview questions and hiring rubrics from leading companies.

Kippy is an AI language tutor application that allows users to practice speaking in various languages anytime, anywhere. It offers real-life conversations, pronunciation improvement, progress tracking, unlimited conversations powered by ChatGPT, natural human-like voices, instant 2-way translation, personal phrasebooks, and more. Users can engage in role-playing scenarios, test their pronunciation, track their vocabulary growth, and set daily speaking goals. The app supports English, Spanish, German, Italian, French, Korean, Japanese, Chinese, and Russian languages.

SEOlligence is an AI-powered tool designed for e-commerce businesses to optimize product titles, subtitles, descriptions, and meta data for better search rankings and increased online visibility. It offers a range of services including SEO optimization, product title and description enhancement, keyword research, FAQ schema optimization, and meta title and description optimization. With the power of Artificial Intelligence, SEOlligence empowers businesses to improve their search rankings, drive organic traffic, and attract more customers. The tool is compatible with all e-commerce platforms and provides fast, accurate, and cost-effective solutions for localization and SEO optimization.

SenseVoice is a speech foundation model focusing on high-accuracy multilingual speech recognition, speech emotion recognition, and audio event detection. Trained with over 400,000 hours of data, it supports more than 50 languages and excels in emotion recognition and sound event detection. The model offers efficient inference with low latency and convenient finetuning scripts. It can be deployed for service with support for multiple client-side languages. SenseVoice-Small model is open-sourced and provides capabilities for Mandarin, Cantonese, English, Japanese, and Korean. The tool also includes features for natural speech generation and fundamental speech recognition tasks.

xFasterTransformer is an optimized solution for Large Language Models (LLMs) on the X86 platform, providing high performance and scalability for inference on mainstream LLM models. It offers C++ and Python APIs for easy integration, along with example codes and benchmark scripts. Users can prepare models in a different format, convert them, and use the APIs for tasks like encoding input prompts, generating token ids, and serving inference requests. The tool supports various data types and models, and can run in single or multi-rank modes using MPI. A web demo based on Gradio is available for popular LLM models like ChatGLM and Llama2. Benchmark scripts help evaluate model inference performance quickly, and MLServer enables serving with REST and gRPC interfaces.

The Lakera PINT Benchmark provides a neutral evaluation method for prompt injection detection systems, offering a dataset of English inputs with prompt injections, jailbreaks, benign inputs, user-agent chats, and public document excerpts. The dataset is designed to be challenging and representative, with plans for future enhancements. The benchmark aims to be unbiased and accurate, welcoming contributions to improve prompt injection detection. Users can evaluate prompt injection detection systems using the provided Jupyter Notebook. The dataset structure is specified in YAML format, allowing users to prepare their datasets for benchmarking. Evaluation examples and resources are provided to assist users in evaluating prompt injection detection models and tools.

Can AI Code is a self-evaluating interview tool for AI coding models. It includes interview questions written by humans and tests taken by AI, inference scripts for common API providers and CUDA-enabled quantization runtimes, a Docker-based sandbox environment for validating untrusted Python and NodeJS code, and the ability to evaluate the impact of prompting techniques and sampling parameters on large language model (LLM) coding performance. Users can also assess LLM coding performance degradation due to quantization. The tool provides test suites for evaluating LLM coding performance, a webapp for exploring results, and comparison scripts for evaluations. It supports multiple interviewers for API and CUDA runtimes, with detailed instructions on running the tool in different environments. The repository structure includes folders for interviews, prompts, parameters, evaluation scripts, comparison scripts, and more.

Nejumi Leaderboard 3 is a comprehensive evaluation platform for large language models, assessing general language capabilities and alignment aspects. The evaluation framework includes metrics for language processing, translation, summarization, information extraction, reasoning, mathematical reasoning, entity extraction, knowledge/question answering, English, semantic analysis, syntactic analysis, alignment, ethics/moral, toxicity, bias, truthfulness, and robustness. The repository provides an implementation guide for environment setup, dataset preparation, configuration, model configurations, and chat template creation. Users can run evaluation processes using specified configuration files and log results to the Weights & Biases project.

MockingBird is a toolbox designed for Mandarin speech synthesis using PyTorch. It supports multiple datasets such as aidatatang_200zh, magicdata, aishell3, and data_aishell. The toolbox can run on Windows, Linux, and M1 MacOS, providing easy and effective speech synthesis with pretrained encoder/vocoder models. It is webserver ready for remote calling. Users can train their own models or use existing ones for the encoder, synthesizer, and vocoder. The toolbox offers a demo video and detailed setup instructions for installation and model training.

PEFT (Parameter-Efficient Fine-Tuning) is a collection of state-of-the-art methods that enable efficient adaptation of large pretrained models to various downstream applications. By only fine-tuning a small number of extra model parameters instead of all the model's parameters, PEFT significantly decreases the computational and storage costs while achieving performance comparable to fully fine-tuned models.

mjai.app is a platform for mahjong AI competition. It contains an implementation of a mahjong game simulator for evaluating submission files. The simulator runs Docker internally, and there is a base class for developing bots that communicate via the mjai protocol. Submission files are deployed in a Docker container, and the Docker image is pushed to Docker Hub. The Mjai protocol used is customized based on Mortal's Mjai Engine implementation.

FunAudioLLM-APP is a repository hosting two applications: Voice Chat for interactive AI-driven dialogues and Voice Translation for real-time language translation. The project leverages advanced audio understanding and speech generation models to enhance audio experiences. Users can visit the FunAudioLLM Homepage, CosyVoice Paper, and FunAudioLLM Technical Report for more details. The applications aim to break down language barriers and provide a natural chatting experience in various settings.

This competition is organized by Javier Rando and Florian Tramèr from the ETH AI Center and SPY Lab at ETH Zurich. The goal of the competition is to create a method that can detect universal backdoors in aligned language models. A universal backdoor is a secret suffix that, when appended to any prompt, enables the model to answer harmful instructions. The competition provides a set of poisoned generation models, a reward model that measures how safe a completion is, and a dataset with prompts to run experiments. Participants are encouraged to use novel methods for red-teaming, automated approaches with low human oversight, and interpretability tools to find the trojans. The best submissions will be offered the chance to present their work at an event during the SaTML 2024 conference and may be invited to co-author a publication summarizing the competition results.

Wllama is a WebAssembly binding for llama.cpp, a high-performance and lightweight language model library. It enables you to run inference directly on the browser without the need for a backend or GPU. Wllama provides both high-level and low-level APIs, allowing you to perform various tasks such as completions, embeddings, tokenization, and more. It also supports model splitting, enabling you to load large models in parallel for faster download. With its Typescript support and pre-built npm package, Wllama is easy to integrate into your React Typescript projects.

Qwen is a series of large language models developed by Alibaba DAMO Academy. It outperforms the baseline models of similar model sizes on a series of benchmark datasets, e.g., MMLU, C-Eval, GSM8K, MATH, HumanEval, MBPP, BBH, etc., which evaluate the models’ capabilities on natural language understanding, mathematic problem solving, coding, etc. Qwen models outperform the baseline models of similar model sizes on a series of benchmark datasets, e.g., MMLU, C-Eval, GSM8K, MATH, HumanEval, MBPP, BBH, etc., which evaluate the models’ capabilities on natural language understanding, mathematic problem solving, coding, etc. Qwen-72B achieves better performance than LLaMA2-70B on all tasks and outperforms GPT-3.5 on 7 out of 10 tasks.

React Native binding of llama.cpp, which is an inference of LLaMA model in pure C/C++. This tool allows you to use the LLaMA model in your React Native applications for various tasks such as text completion, tokenization, detokenization, and embedding. It provides a convenient interface to interact with the LLaMA model and supports features like grammar sampling and mocking for testing purposes.

Open-LLM-VTuber is a project in early stages of development that allows users to interact with Large Language Models (LLM) using voice commands and receive responses through a Live2D talking face. The project aims to provide a minimum viable prototype for offline use on macOS, Linux, and Windows, with features like long-term memory using MemGPT, customizable LLM backends, speech recognition, and text-to-speech providers. Users can configure the project to chat with LLMs, choose different backend services, and utilize Live2D models for visual representation. The project supports perpetual chat, offline operation, and GPU acceleration on macOS, addressing limitations of existing solutions on macOS.

PDFToChat is a tool that allows users to chat with their PDF documents in seconds. It is powered by Together AI and Pinecone, utilizing a tech stack including Next.js, Mixtral, M2 Bert, LangChain.js, MongoDB Atlas, Bytescale, Vercel, Clerk, and Tailwind CSS. Users can deploy the tool to Vercel or any other host by setting up Together.ai, MongoDB Atlas database, Bytescale, Clerk, and Vercel. The tool enables users to interact with PDFs through chat, with future tasks including adding features like trash icon for deleting PDFs, exploring different embedding models, implementing auto scrolling, improving replies, benchmarking accuracy, researching chunking and retrieval best practices, adding demo video, upgrading to Next.js 14, adding analytics, customizing tailwind prose, saving chats in postgres DB, compressing large PDFs, implementing custom uploader, session tracking, error handling, and support for images in PDFs.

Home LLM is a project that provides the necessary components to control your Home Assistant installation with a completely local Large Language Model acting as a personal assistant. The goal is to provide a drop-in solution to be used as a "conversation agent" component by Home Assistant. The 2 main pieces of this solution are Home LLM and Llama Conversation. Home LLM is a fine-tuning of the Phi model series from Microsoft and the StableLM model series from StabilityAI. The model is able to control devices in the user's house as well as perform basic question and answering. The fine-tuning dataset is a custom synthetic dataset designed to teach the model function calling based on the device information in the context. Llama Conversation is a custom component that exposes the locally running LLM as a "conversation agent" in Home Assistant. This component can be interacted with in a few ways: using a chat interface, integrating with Speech-to-Text and Text-to-Speech addons, or running the oobabooga/text-generation-webui project to provide access to the LLM via an API interface.

Translate texts in manga/images. Some manga/images will never be translated, therefore this project is born. * Image/Manga Translator * Samples * Online Demo * Disclaimer * Installation * Pip/venv * Poetry * Additional instructions for **Windows** * Docker * Hosting the web server * Using as CLI * Setting Translation Secrets * Using with Nvidia GPU * Building locally * Usage * Batch mode (default) * Demo mode * Web Mode * Api Mode * Related Projects * Docs * Recommended Modules * Tips to improve translation quality * Options * Language Code Reference * Translators Reference * GPT Config Reference * Using Gimp for rendering * Api Documentation * Synchronous mode * Asynchronous mode * Manual translation * Next steps * Support Us * Thanks To All Our Contributors :

RLAIF-V is a novel framework that aligns MLLMs in a fully open-source paradigm for super GPT-4V trustworthiness. It maximally exploits open-source feedback from high-quality feedback data and online feedback learning algorithm. Notable features include achieving super GPT-4V trustworthiness in both generative and discriminative tasks, using high-quality generalizable feedback data to reduce hallucination of different MLLMs, and exhibiting better learning efficiency and higher performance through iterative alignment.

The Cradle project is a framework designed for General Computer Control (GCC), empowering foundation agents to excel in various computer tasks through strong reasoning abilities, self-improvement, and skill curation. It provides a standardized environment with minimal requirements, constantly evolving to support more games and software. The repository includes released versions, publications, and relevant assets.

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The Oracle of TED uses the top 100 ted talks from 2006-2021 to help you prepare your next presentation.

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Voice-to-text, Vision-to-text transcription, Transcript-to-‘Clinical format’ integrated with CDS. Writes clinical notes, referral letter, generate PDF,prepare discharge summary. (Ultimate aid for clinicians)