Best AI tools for< Verification Engineer >

The website is a platform that requires JavaScript to be enabled in order to verify that the user is not a robot. It prompts the user to enable JavaScript and reload the page to proceed further.

KBY-AI is an advanced Identity Verification SDK provider offering powerful solutions for Face Recognition, Face Liveness Detection, and ID Card Recognition. Their cutting-edge AI technology ensures foolproof protection without disrupting the user's flow. The SDKs are designed to be lightweight, highly effective, and ideal for commercial applications like KYC automation, time and attendance systems, and video surveillance. KBY-AI's solutions support various ID documents from 200+ countries and are compatible with Android, iOS, and web platforms.

The website is a platform that requires users to enable JavaScript in order to verify that they are not a robot. It seems to be a security measure to prevent automated bots from accessing the site. Users are prompted to enable JavaScript and reload the page to proceed further.

medium.engineering is a website that focuses on verifying the security of user connections before allowing access to the site. It ensures that users are human by conducting a verification process that may take a few seconds. The site emphasizes the importance of enabling JavaScript and cookies for a seamless browsing experience. Powered by Cloudflare, medium.engineering prioritizes performance and security for its users.

MiniAiLive is a provider of Touchless Biometrics Authentication and ID verification solutions. They offer strong security solutions with cutting-edge technologies for facial recognition, liveness detection, and ID document recognition. MiniAiLive ensures seamless integration with clients' existing systems. The application caters to various industries and provides solutions for identity verification, biometric authentication, and fraud prevention. MiniAiLive stands out for its global coverage, configurability, speed, and accuracy in identity verification services.

Theresanaiforthat.com is a website that provides a platform for users to verify their identity as human users before accessing the content. The site ensures security by reviewing the connection and requires enabling JavaScript and cookies for continued access. It utilizes Cloudflare for performance and security measures.

Nametag is an identity verification solution designed specifically for IT helpdesks. It helps businesses prevent social engineering attacks, account takeovers, and data breaches by verifying the identity of users at critical moments, such as password resets, MFA resets, and high-risk transactions. Nametag's unique approach to identity verification combines mobile cryptography, device telemetry, and proprietary AI models to provide unmatched security and better user experiences.

Imandra is a company that provides automated logical reasoning for Large Language Models (LLMs). Imandra's technology allows LLMs to build mental models and reason about them, unlocking the potential of generative AI for industries where correctness and compliance matter. Imandra's platform is used by leading financial firms, the US Air Force, and DARPA.

Valispace is an AI-powered platform that streamlines the entire engineering process, from requirements engineering to system design, test, verification, and validation. It modernizes classic engineering practices, enabling fast design iterations and automatic verifications. The platform assists in removing mundane and manual engineering tasks, saving engineering hours and enhancing collaboration among engineers and stakeholders.

Facia.ai is a cutting-edge AI application that specializes in fast and accurate face recognition with 3D liveness detection. It offers solutions for businesses and governments to prevent identity fraud, deepfake manipulation, and enhance security through facial biometric analysis. The platform provides advanced features such as face matching, ID document verification, deepfake detection, age estimation, and iris recognition. Facia.ai stands out for its industry-leading accuracy, customizable integration, and user-driven design philosophy, ensuring a reliable and secure experience for users.

Ambient.ai is an AI-powered physical security software that utilizes computer vision intelligence to prevent security incidents. It offers real-time threat detection, automated false alarm clearance, and accelerated investigations. The platform monitors cameras for suspicious activities, detects threats like firearms and unauthorized entries, and enables rapid response. Ambient.ai also reduces false alarms, accelerates investigations, and integrates with existing security infrastructure to streamline operations. The application prioritizes operational efficiency, enterprise-grade privacy, and has been recognized as a leader in AI for physical security since 2017.

AmyGB Platform Services offers Gen AI-powered Document Processing and API Services to supercharge productivity for businesses. Their trendsetting digital products have revolutionized how organizations handle data and streamline workflows, enabling businesses to easily optimize operations 24x7, enhance data accuracy, and improve customer satisfaction. The platform empowers business operations by driving automation revolution, providing 8x productivity, 70% cost efficiency, 80% higher accuracy, and 95% automation. AmyGB's AI-powered document processing solutions help convert documents into digital assets, extract data, and enhance customer fulfillment through automated software solutions.

ZEBCOIN is an AI-powered platform that focuses on decentralized identity verification, intellectual property rights, AI-driven decentralized finance (DeFi) and micro-lending, environmental sustainability, and transparency in supply chains. It aims to leverage AI and blockchain technology to offer innovative financial solutions, promote clean energy initiatives, ensure transparency in global supply chains, and provide decentralized identity verification services. The platform also plans to launch its own blockchain (ZEB Chain) with features like an explorer, decentralized exchanges (DEX) transparency, NFT marketplace, and lending and DeFi services. ZEBCOIN aims to revolutionize the blockchain space by integrating AI technology into various aspects of its ecosystem.

Seventh Sense is an AI company focused on providing cutting-edge AI solutions for secure and private identity verification. Their innovative technologies, such as SenseCrypt, OpenCV FR, and SenseVantage, offer advanced biometric verification, face recognition, and AI video analysis. With a mission to make self-sovereign identity accessible to all, Seventh Sense ensures privacy, security, and compliance through their AI algorithms and cryptographic solutions.

Vercel Security Checkpoint is a web application that provides a security verification process for users accessing the Vercel platform. It ensures the safety and integrity of the platform by verifying the user's browser and enabling JavaScript before proceeding. The checkpoint serves as a protective measure to prevent unauthorized access and potential security threats.

FaceOnLive is an AI-powered on-premises ID verification and biometrics solution provider. The platform offers a suite of SDKs for ID document recognition, face liveness detection, face recognition, and other AI solutions. With a focus on data security and compliance, FaceOnLive enables businesses to build custom ID verification systems while maintaining full control over customer data. The platform also provides touchless biometrics authentication solutions for secure and contact-free customer onboarding.

Dexa.ai is an AI-powered tool designed to verify user identity and ensure secure connections. It quickly verifies human users, reviews connection security, and provides real-time responses. By leveraging AI technology, Dexa.ai enhances performance and security for users. The tool is essential for websites that require user verification and secure connections to prevent unauthorized access and ensure data protection.

Sider.ai is a web application that focuses on security verification before allowing access to its services. It ensures a secure connection by reviewing the security measures of the user's connection. The platform may prompt users to enable JavaScript and cookies for a seamless experience. Sider.ai employs Cloudflare for performance and security enhancements.

Workera is an AI-powered platform that helps enterprises to build AI-ready workforces by accurately measuring competencies and providing insights into skills development. The platform offers skills intelligence, precise upskilling, and personalized learning plans to transform the workforce. Workera is trusted by global enterprises to enhance talent strategies and prepare the workforce for the future through continuous skills verification and dynamic insights.

Local AI Playground is a free and open-source native app designed for AI management, verification, and inferencing. It allows users to experiment with AI offline in a private environment without the need for a GPU. The application is memory-efficient and compact, with features like CPU inferencing, model management, and digest verification. Users can start a local streaming server for AI inferencing with just two clicks. Local AI Playground aims to simplify the AI development process and provide a user-friendly platform for AI enthusiasts.

LLM4EDA is a repository dedicated to showcasing the emerging progress in utilizing Large Language Models for Electronic Design Automation. The repository includes resources, papers, and tools that leverage LLMs to solve problems in EDA. It covers a wide range of applications such as knowledge acquisition, code generation, code analysis, verification, and large circuit models. The goal is to provide a comprehensive understanding of how LLMs can revolutionize the EDA industry by offering innovative solutions and new interaction paradigms.

LLM-PLSE-paper is a repository focused on the applications of Large Language Models (LLMs) in Programming Language and Software Engineering (PL/SE) domains. It covers a wide range of topics including bug detection, specification inference and verification, code generation, fuzzing and testing, code model and reasoning, code understanding, IDE technologies, prompting for reasoning tasks, and agent/tool usage and planning. The repository provides a comprehensive collection of research papers, benchmarks, empirical studies, and frameworks related to the capabilities of LLMs in various PL/SE tasks.

The LLM Engineer's Handbook is an official repository containing a comprehensive guide on creating an end-to-end LLM-based system using best practices. It covers data collection & generation, LLM training pipeline, a simple RAG system, production-ready AWS deployment, comprehensive monitoring, and testing and evaluation framework. The repository includes detailed instructions on setting up local and cloud dependencies, project structure, installation steps, infrastructure setup, pipelines for data processing, training, and inference, as well as QA, tests, and running the project end-to-end.

This project is a tutorial on developing large model applications for novice developers. It aims to provide a comprehensive introduction to large model development, focusing on Alibaba Cloud servers and integrating personal knowledge assistant projects. The tutorial covers the following topics: 1. **Introduction to Large Models**: A simplified introduction for novice developers on what large models are, their characteristics, what LangChain is, and how to develop an LLM application. 2. **How to Call Large Model APIs**: This section introduces various methods for calling APIs of well-known domestic and foreign large model products, including calling native APIs, encapsulating them as LangChain LLMs, and encapsulating them as Fastapi calls. It also provides a unified encapsulation for various large model APIs, such as Baidu Wenxin, Xunfei Xinghuo, and Zh譜AI. 3. **Knowledge Base Construction**: Loading, processing, and vector database construction of different types of knowledge base documents. 4. **Building RAG Applications**: Integrating LLM into LangChain to build a retrieval question and answer chain, and deploying applications using Streamlit. 5. **Verification and Iteration**: How to implement verification and iteration in large model development, and common evaluation methods. The project consists of three main parts: 1. **Introduction to LLM Development**: A simplified version of V1 aims to help beginners get started with LLM development quickly and conveniently, understand the general process of LLM development, and build a simple demo. 2. **LLM Development Techniques**: More advanced LLM development techniques, including but not limited to: Prompt Engineering, processing of multiple types of source data, optimizing retrieval, recall ranking, Agent framework, etc. 3. **LLM Application Examples**: Introduce some successful open source cases, analyze the ideas, core concepts, and implementation frameworks of these application examples from the perspective of this course, and help beginners understand what kind of applications they can develop through LLM. Currently, the first part has been completed, and everyone is welcome to read and learn; the second and third parts are under creation. **Directory Structure Description**: requirements.txt: Installation dependencies in the official environment notebook: Notebook source code file docs: Markdown documentation file figures: Pictures data_base: Knowledge base source file used

Auto-Gmail-Creator is an open-source automation script designed for Python enthusiasts to learn automation basics and for marketers to create multiple Google accounts efficiently. The script automates the process of creating Gmail accounts using sms-activate.org API for phone verification. It handles the download of Chromedriver or Geckodriver automatically and can be customized to prevent blocking. The tool is useful for projects related to automation, scraping, and machine learning.

Bugbug is a tool developed by Mozilla that leverages machine learning techniques to assist with bug and quality management, as well as other software engineering tasks like test selection and defect prediction. It provides various classifiers to suggest assignees, detect patches likely to be backed-out, classify bugs, assign product/components, distinguish between bugs and feature requests, detect bugs needing documentation, identify invalid issues, verify bugs needing QA, detect regressions, select relevant tests, track bugs, and more. Bugbug can be trained and tested using Python scripts, and it offers the ability to run model training tasks on Taskcluster. The project structure includes modules for data mining, bug/commit feature extraction, model implementations, NLP utilities, label handling, bug history playback, and GitHub issue retrieval.

DevDocs is a platform designed to simplify the process of digesting technical documentation for software engineers and developers. It automates the extraction and conversion of web content into markdown format, making it easier for users to access and understand the information. By crawling through child pages of a given URL, DevDocs provides a streamlined approach to gathering relevant data and integrating it into various tools for software development. The tool aims to save time and effort by eliminating the need for manual research and content extraction, ultimately enhancing productivity and efficiency in the development process.

Ludwig is a declarative deep learning framework designed for scale and efficiency. It is a low-code framework that allows users to build custom AI models like LLMs and other deep neural networks with ease. Ludwig offers features such as optimized scale and efficiency, expert level control, modularity, and extensibility. It is engineered for production with prebuilt Docker containers, support for running with Ray on Kubernetes, and the ability to export models to Torchscript and Triton. Ludwig is hosted by the Linux Foundation AI & Data.

This repository provides a comprehensive guide on building AI WhatsApp bots using Python and Flask. It covers setting up a Meta developer account, integrating webhook events for real-time message reception, and using OpenAI for AI responses. The tutorial includes steps for selecting phone numbers, sending messages with the API, configuring webhooks, integrating AI into the application, and adding a phone number. It also explains the process of creating a system user, obtaining access tokens, and validating verification requests and payloads for webhook security. The repository aims to help users create intelligent WhatsApp bots with Python and AI capabilities.

PartCAD is a tool for documenting manufacturable physical products, providing tools to maintain product information and streamline workflows at all product lifecycle phases. It is a next-generation CAD tool that focuses on specifying manufacturable physical products using computer-aided design in a more generic sense, including the use of AI models. PartCAD offers modular and reusable packages for product information, generating outputs like product documentation, bill of materials, sourcing information, and manufacturing process specifications. It integrates with third-party tools for iterative improvements, design validation, and manufacturing processes verification. PartCAD also offers supplementary products like a CRM and inventory tool for managing part manufacturing and assembly shops. By enabling easy switching between third-party tools, PartCAD creates a competitive environment for service providers and ensures data sovereignty for users.

VerifAI is a document-based question-answering system that addresses hallucinations in generative large language models and search engines. It retrieves relevant documents, generates answers with references, and verifies answers for accuracy. The engine uses generative search technology and a verification model to ensure no misinformation. VerifAI supports various document formats and offers user registration with a React.js interface. It is open-source and designed to be user-friendly, making it accessible for anyone to use.

LLM-for-misinformation-research is a curated paper list of misinformation research using large language models (LLMs). The repository covers methods for detection and verification, tools for fact-checking complex claims, decision-making and explanation, claim matching, post-hoc explanation generation, and other tasks related to combating misinformation. It includes papers on fake news detection, rumor detection, fact verification, and more, showcasing the application of LLMs in various aspects of misinformation research.

This repository contains course materials for T81 559: Applications of Generative Artificial Intelligence at Washington University in St. Louis. The course covers practical applications of Large Language Models (LLMs) and text-to-image networks using Python. Students learn about generative AI principles, LangChain, Retrieval-Augmented Generation (RAG) model, image generation techniques, fine-tuning neural networks, and prompt engineering. Ideal for students, researchers, and professionals in computer science, the course offers a transformative learning experience in the realm of Generative AI.

LLMInterviewQuestions is a repository containing over 100+ interview questions for Large Language Models (LLM) used by top companies like Google, NVIDIA, Meta, Microsoft, and Fortune 500 companies. The questions cover various topics related to LLMs, including prompt engineering, retrieval augmented generation, chunking, embedding models, internal working of vector databases, advanced search algorithms, language models internal working, supervised fine-tuning of LLM, preference alignment, evaluation of LLM system, hallucination control techniques, deployment of LLM, agent-based system, prompt hacking, and miscellaneous topics. The questions are organized into 15 categories to facilitate learning and preparation.

hongbomiao.com is a personal research and development (R&D) lab that facilitates the sharing of knowledge. The repository covers a wide range of topics including web development, mobile development, desktop applications, API servers, cloud native technologies, data processing, machine learning, computer vision, embedded systems, simulation, database management, data cleaning, data orchestration, testing, ops, authentication, authorization, security, system tools, reverse engineering, Ethereum, hardware, network, guidelines, design, bots, and more. It provides detailed information on various tools, frameworks, libraries, and platforms used in these domains.

**Curated collection of papers and resources on how to unlock the reasoning ability of LLMs and MLLMs.** **Description in less than 400 words, no line breaks and quotation marks.** Large Language Models (LLMs) have revolutionized the NLP landscape, showing improved performance and sample efficiency over smaller models. However, increasing model size alone has not proved sufficient for high performance on challenging reasoning tasks, such as solving arithmetic or commonsense problems. This curated collection of papers and resources presents the latest advancements in unlocking the reasoning abilities of LLMs and Multimodal LLMs (MLLMs). It covers various techniques, benchmarks, and applications, providing a comprehensive overview of the field. **5 jobs suitable for this tool, in lowercase letters.** - content writer - researcher - data analyst - software engineer - product manager **Keywords of the tool, in lowercase letters.** - llm - reasoning - multimodal - chain-of-thought - prompt engineering **5 specific tasks user can use this tool to do, in less than 3 words, Verb + noun form, in daily spoken language.** - write a story - answer a question - translate a language - generate code - summarize a document

Academic_LLM_Sec_Papers is a curated collection of academic papers related to LLM Security Application. The repository includes papers sorted by conference name and published year, covering topics such as large language models for blockchain security, software engineering, machine learning, and more. Developers and researchers are welcome to contribute additional published papers to the list. The repository also provides information on listed conferences and journals related to security, networking, software engineering, and cryptography. The papers cover a wide range of topics including privacy risks, ethical concerns, vulnerabilities, threat modeling, code analysis, fuzzing, and more.

Bittensor is an internet-scale neural network that incentivizes computers to provide access to machine learning models in a decentralized and censorship-resistant manner. It operates through a token-based mechanism where miners host, train, and procure machine learning systems to fulfill verification problems defined by validators. The network rewards miners and validators for their contributions, ensuring continuous improvement in knowledge output. Bittensor allows anyone to participate, extract value, and govern the network without centralized control. It supports tasks such as generating text, audio, images, and extracting numerical representations.

Husky is a research-focused programming language designed for next-generation computing. It aims to provide a powerful and ergonomic development experience for various tasks, including system level programming, web/native frontend development, parser/compiler tasks, game development, formal verification, machine learning, and more. With a strong type system and support for human-in-the-loop programming, Husky enables users to tackle complex tasks such as explainable image classification, natural language processing, and reinforcement learning. The language prioritizes debugging, visualization, and human-computer interaction, offering agile compilation and evaluation, multiparadigm support, and a commitment to a good ecosystem.

Awesome LLM for APR is a repository dedicated to exploring the capabilities of Large Language Models (LLMs) in Automated Program Repair (APR). It provides a comprehensive collection of research papers, tools, and resources related to using LLMs for various scenarios such as repairing semantic bugs, security vulnerabilities, syntax errors, programming problems, static warnings, self-debugging, type errors, web UI tests, smart contracts, hardware bugs, performance bugs, API misuses, crash bugs, test case repairs, formal proofs, GitHub issues, code reviews, motion planners, human studies, and patch correctness assessments. The repository serves as a valuable reference for researchers and practitioners interested in leveraging LLMs for automated program repair.

Your digital design & verification guide. The conversation data will not be used for training.

I will provide guidance on testing, verification, and validation for QA roles.

Precise IoC search and summary with source URLs for verification.

Binary tools & Z3 CLI

Crafts detailed articles with structured word count verification.

Expert on extraterrestrial abductions and close encounters, with a verification process for accuracy.

Simple CustomGPT built on Vitals Inquiry Case in Malta, aimed to help journalists and citizens navigate the inquiry's large dataset in a neutral, informative fashion. Always cross-reference replies to actual data. Do not rely solely on this LLM for verification of facts.

Verifying Reality: I scrutinize text messages and media to reveal the real story, defeating misinformation and fake news.

Verify whether the Chinese brand you are interested in is mainstream by searching three Chinese business media with more than 10 million subscriptions. If you don't get any information, the "Chinese brand" is not well known in China.

Can you prove that you're not an AI? :O

Débunker d'infos, vérificateur de photos, avec analyse de sentiments, résumés automatiques, alertes personnalisées, cartographie des sources et éducation aux médias.

Checks if domains/emails are disposable using an API

Your guide to Content Credentials, Content Authenticity Initiative (CAI) and Coalition for Content Provenance and Authenticity (C2PA) at File.Baby.

A journalistic GPT that reports news, writes stories, and verifies information.