Best AI tools for< Prevent Data Loss >

Concentric AI is a Managed Data Security Posture Management tool that utilizes Semantic Intelligence to provide comprehensive data security solutions. The platform offers features such as autonomous data discovery, data risk identification, centralized remediation, easy deployment, and data security posture management. Concentric AI helps organizations protect sensitive data, prevent data loss, and ensure compliance with data security regulations. The tool is designed to simplify data governance and enhance data security across various data repositories, both in the cloud and on-premises.

Lakera is the world's most advanced AI security platform that offers cutting-edge solutions to safeguard GenAI applications against various security threats. Lakera provides real-time security controls, stress-testing for AI systems, and protection against prompt attacks, data loss, and insecure content. The platform is powered by a proprietary AI threat database and aligns with global AI security frameworks to ensure top-notch security standards. Lakera is suitable for security teams, product teams, and LLM builders looking to secure their AI applications effectively and efficiently.

Spin.AI is an AI-powered SaaS security platform that provides full visibility and control over mission-critical applications. With features such as SSPM, DSPM, ransomware detection & response, data leak prevention, and backup & disaster recovery, Spin.AI offers comprehensive protection for SaaS data. Trusted by over 1,500 organizations across 100+ countries, Spin.AI helps enhance cyber resilience, security operations, and cost efficiency for businesses.

The website is an AI-powered cybersecurity platform that aims to empower and secure every user and every action. It provides total protection through an integrated cloud platform, offering features such as secure access to web and cloud apps, threat detection and mitigation, advanced data protection, secure remote worker solutions, and AI-powered security leveraging intelligence about user activity and devices. The platform helps businesses anticipate threats, manage vulnerabilities, and protect users worldwide.

Lakera is the world's most advanced AI security platform designed to protect organizations from AI threats. It offers solutions for prompt injection detection, unsafe content identification, PII and data loss prevention, data poisoning prevention, and insecure LLM plugin design. Lakera is recognized for setting global AI security standards and is trusted by leading enterprises, foundation model providers, and startups. The platform is powered by a proprietary AI threat database and aligns with global AI security frameworks.

Nightfall AI is a comprehensive data security platform that leverages AI technology to protect sensitive data in the AI-driven enterprise. It offers solutions for data loss prevention, data protection, and data privacy for AI applications. Nightfall scans all types of enterprise data, monitors high-risk activities, and enables secure, AI-driven productivity without hindering end-users. The platform integrates seamlessly with enterprise apps and devices, providing immediate response to data exposure incidents. Nightfall is trusted by innovative organizations for its holistic approach to data security and compliance.

The AI Seed Phrase Finder & BTC balance checker tool for Windows PC is an innovative application designed to prevent the loss of access to Bitcoin wallets. Leveraging advanced algorithms and artificial intelligence techniques, this program efficiently analyzes vast amounts of data to pre-train AI models. Consequently, it generates and searches for mnemonic phrases that grant access to abandoned Bitcoin wallets holding nonzero balances. With the “AI Seed Finder tool for Windows PC”, locating a complete 12-word seed phrase for a specific Bitcoin wallet becomes effortless. Even if you possess only partial knowledge of the mnemonic phrase or individual words comprising it, this tool can swiftly identify the entire seed phrase. Furthermore, by providing the address of a specific Bitcoin wallet you wish to regain access to, the program narrows down the search area. This targeted approach significantly enhances the program’s efficiency and reduces the time required to ascertain the correct mnemonic phrase.

DTiQ is a leading provider of loss prevention and intelligent video solutions for businesses in the United States and globally. Their video surveillance and loss prevention solutions help businesses manage key aspects from any device, resulting in increased profits. DTiQ offers SmartAudit™, SmartAnalysis, and SmartAssurance products to enhance operational quality, save time, and provide innovative loss prevention solutions. Trusted by hundreds of brands, DTiQ prioritizes security, integrity, and support to help businesses run smarter and more efficiently.

DataVisor is a modern, end-to-end fraud and risk SaaS platform powered by AI and advanced machine learning for financial institutions and large organizations. It provides a comprehensive suite of capabilities to combat a variety of fraud and financial crimes in real time. DataVisor's hyper-scalable, modern architecture allows you to leverage transaction logs, user profiles, dark web and other identity signals with real-time analytics to enrich and deliver high quality detection in less than 100-300ms. The platform is optimized to scale to support the largest enterprises with ultra-low latency. DataVisor enables early detection and adaptive response to new and evolving fraud attacks combining rules, machine learning, customizable workflows, device and behavior signals in an all-in-one platform for complete protection. Leading with an Unsupervised approach, DataVisor is the only proven, production-ready solution that can proactively stop fraud attacks before they result in financial loss.

DataVisor is a modern, end-to-end fraud and risk SaaS platform powered by AI and advanced machine learning for financial institutions and large organizations. It helps businesses combat various fraud and financial crimes in real time. DataVisor's platform provides comprehensive fraud detection and prevention capabilities, including account onboarding, application fraud, ATO prevention, card fraud, check fraud, FinCrime and AML, and ACH and wire fraud detection. The platform is designed to adapt to new fraud incidents immediately with real-time data signal orchestration and end-to-end workflow automation, minimizing fraud losses and maximizing fraud detection coverage.

Simbo AI is a Gen AI platform designed for healthcare enterprises, offering autonomous applications for medical practice automation. It combines LLM and symbolic knowledge bases to provide hallucination-free responses. The platform is fully controllable, consistent, secure, and responsible, ensuring accurate and reliable AI interactions. Simbo AI utilizes Symbolic RAG technology with Lossless NLU for exact search and fact-checking capabilities. It aims to automate medical practices, reduce costs, and improve patient care, ultimately enhancing the lives of doctors and patients.

Fraud.net is an AI-powered fraud detection and prevention platform designed for enterprises. It offers a comprehensive and customizable solution to manage and prevent various types of fraud, such as account takeover, application fraud, and payment fraud. The platform utilizes AI and machine learning technologies to provide real-time monitoring, analytics, and reporting, helping businesses reduce fraud losses and improve customer trust. Fraud.net is trusted by various industries, including financial services, e-commerce, gaming, government, and insurance, to combat fraud schemes and ensure secure transactions.

EchoMark is a cloud-based data leak prevention solution that uses invisible forensic watermarks to protect sensitive information from unauthorized access and exfiltration. It allows organizations to securely share and collaborate on documents and emails without compromising privacy and security. EchoMark's advanced investigation tools can trace the source of a leaked document or email, even if it has been shared via printout or photo.

OpenBuckets is a web application designed to help users find and secure open buckets in cloud storage systems. It provides a user-friendly interface for scanning and identifying publicly accessible buckets, allowing users to take necessary actions to secure their data. With OpenBuckets, users can easily detect misconfigured buckets and prevent potential data breaches. The application offers a simple yet effective solution for enhancing cloud security and protecting sensitive information stored in cloud storage platforms.

ZeroTrusted.ai is a cybersecurity platform that offers an AI Firewall to protect users from data exposure and exploitation by unethical providers or malicious actors. The platform provides features such as anonymity, security, reliability, integrations, and privacy to safeguard sensitive information. ZeroTrusted.ai empowers organizations with cutting-edge encryption techniques, AI & ML technologies, and decentralized storage capabilities for maximum security and compliance with regulations like PCI, GDPR, and NIST.

Wing Security is a SaaS Security Posture Management (SSPM) solution that helps businesses protect their data by providing full visibility and control over applications, users, and data. The platform offers features such as automated remediation, AI discovery, real-time SaaS visibility, vendor risk management, insider risk management, and more. Wing Security enables organizations to eliminate risky applications, manage user behavior, and protect sensitive data from unauthorized access. With a focus on security first, Wing Security helps businesses leverage the benefits of SaaS while staying protected.

Qypt AI is an advanced tool designed to elevate privacy and empower security through secure file sharing and collaboration. It offers end-to-end encryption, AI-powered redaction, and privacy-preserving queries to ensure confidential information remains protected. With features like zero-trust collaboration and client confidentiality, Qypt AI is built by security experts to provide a secure platform for sharing sensitive data. Users can easily set up the tool, define sharing permissions, and invite collaborators to review documents while maintaining control over access. Qypt AI is a cutting-edge solution for individuals and businesses looking to safeguard their data and prevent information leaks.

Lightup is a cloud data quality monitoring tool with AI-powered anomaly detection, incident alerts, and data remediation capabilities for modern enterprise data stacks. It specializes in helping large organizations implement successful and sustainable data quality programs quickly and easily. Lightup's pushdown architecture allows for monitoring data content at massive scale without moving or copying data, providing extreme scalability and optimal automation. The tool empowers business users with democratized data quality checks and enables automatic fixing of bad data at enterprise scale.

AI Spend is an AI application designed to help users monitor their AI costs and prevent surprises. It allows users to keep track of their OpenAI usage and costs, providing fast insights, a beautiful dashboard, cost insights, notifications, usage analytics, and details on models and tokens. The application ensures simple pricing with no additional costs and securely stores API keys. Users can easily remove their data if needed, emphasizing privacy and security.

Greip is an AI-powered fraud prevention tool that offers a range of services to detect and prevent fraudulent activities in payments. It provides features such as credit card fraud detection, BIN/IIN lookup, IBAN validation, profanity detection, VPN/proxy detection, IP geolocation, ASN lookup, and country lookup. Greip's cutting-edge AI-based technology helps safeguard app's financial security by preventing payment fraud. Users can integrate Greip with thousands of apps, access educational resources, and gain valuable insights through the intuitive dashboard.

Data-to-paper is an AI-driven framework designed to guide users through the process of conducting end-to-end scientific research, starting from raw data to the creation of comprehensive and human-verifiable research papers. The framework leverages a combination of LLM and rule-based agents to assist in tasks such as hypothesis generation, literature search, data analysis, result interpretation, and paper writing. It aims to accelerate research while maintaining key scientific values like transparency, traceability, and verifiability. The framework is field-agnostic, supports both open-goal and fixed-goal research, creates data-chained manuscripts, involves human-in-the-loop interaction, and allows for transparent replay of the research process.

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.

Black Marlin is a UCI compliant chess engine fully written in Rust by Doruk Sekercioglu. It supports Chess960 and features a variety of search algorithms, pruning techniques, and evaluation methods. Black Marlin is designed to be efficient and accurate, and it has been shown to perform well against other top chess engines.

DevOpsGPT is an AI-driven software development automation solution that combines Large Language Models (LLM) with DevOps tools to convert natural language requirements into working software. It improves development efficiency by eliminating the need for tedious requirement documentation, shortens development cycles, reduces communication costs, and ensures high-quality deliverables. The Enterprise Edition offers features like existing project analysis, professional model selection, and support for more DevOps platforms. The tool automates requirement development, generates interface documentation, provides pseudocode based on existing projects, facilitates code refinement, enables continuous integration, and supports software version release. Users can run DevOpsGPT with source code or Docker, and the tool comes with limitations in precise documentation generation and understanding existing project code. The product roadmap includes accurate requirement decomposition, rapid import of development requirements, and integration of more software engineering and professional tools for efficient software development tasks under AI planning and execution.

This repository contains an implementation of Ring Attention, a technique for processing large sequences in transformers. Ring Attention splits the data across the sequence dimension and applies ring reduce to the processing of the tiles of the attention matrix, similar to flash attention. It also includes support for Striped Attention, a follow-up paper that permutes the sequence for better workload balancing for autoregressive transformers, and grouped query attention, which saves on communication costs during the ring reduce. The repository includes a CUDA version of the flash attention kernel, which is used for the forward and backward passes of the ring attention. It also includes logic for splitting the sequence evenly among ranks, either within the attention function or in the external ring transformer wrapper, and basic test cases with two processes to check for equivalent output and gradients.

Implementation of Double DQN reinforcement learning for OpenAI Gym environments with discrete action spaces. The algorithm aims to improve sample efficiency by using two uncorrelated Q-Networks to prevent overestimation of Q-values. By updating parameters periodically, the model reduces computation time and enhances training performance. The tool is based on the Double DQN method proposed by Hasselt in 2010.

The 'gritlm' repository provides all materials for the paper Generative Representational Instruction Tuning. It includes code for inference, training, evaluation, and known issues related to the GritLM model. The repository also offers models for embedding and generation tasks, along with instructions on how to train and evaluate the models. Additionally, it contains visualizations, acknowledgements, and a citation for referencing the work.

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

abliterator.py is a simple Python library/structure designed to ablate features in large language models (LLMs) supported by TransformerLens. It provides capabilities to enter temporary contexts, cache activations with N samples, calculate refusal directions, and includes tokenizer utilities. The library aims to streamline the process of experimenting with ablation direction turns by encapsulating useful logic and minimizing code complexity. While currently basic and lacking comprehensive documentation, the library serves well for personal workflows and aims to expand beyond feature ablation to augmentation and additional features over time with community support.

Prime is a framework for efficient, globally distributed training of AI models over the internet. It includes features such as fault-tolerant training with ElasticDeviceMesh, asynchronous distributed checkpointing, live checkpoint recovery, custom Int8 All-Reduce Kernel, maximizing bandwidth utilization, PyTorch FSDP2/DTensor ZeRO-3 implementation, and CPU off-loading. The framework aims to optimize communication, checkpointing, and bandwidth utilization for large-scale AI model training.

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.

This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

OpenRedTeaming is a repository focused on red teaming for generative models, specifically large language models (LLMs). The repository provides a comprehensive survey on potential attacks on GenAI and robust safeguards. It covers attack strategies, evaluation metrics, benchmarks, and defensive approaches. The repository also implements over 30 auto red teaming methods. It includes surveys, taxonomies, attack strategies, and risks related to LLMs. The goal is to understand vulnerabilities and develop defenses against adversarial attacks on large language models.

This repository provides the latest implementation for the AI Horde Worker, allowing users to utilize their graphics card(s) to generate, post-process, or analyze images for others. It offers a platform where users can create images and earn 'kudos' in return, granting priority for their own image generations. The repository includes important details for setup, recommendations for system configurations, instructions for installation on Windows and Linux, basic usage guidelines, and information on updating the AI Horde Worker. Users can also run the worker with multiple GPUs and receive notifications for updates through Discord. Additionally, the repository contains models that are licensed under the CreativeML OpenRAIL License.

AIlice is a fully autonomous, general-purpose AI agent that aims to create a standalone artificial intelligence assistant, similar to JARVIS, based on the open-source LLM. AIlice achieves this goal by building a "text computer" that uses a Large Language Model (LLM) as its core processor. Currently, AIlice demonstrates proficiency in a range of tasks, including thematic research, coding, system management, literature reviews, and complex hybrid tasks that go beyond these basic capabilities. AIlice has reached near-perfect performance in everyday tasks using GPT-4 and is making strides towards practical application with the latest open-source models. We will ultimately achieve self-evolution of AI agents. That is, AI agents will autonomously build their own feature expansions and new types of agents, unleashing LLM's knowledge and reasoning capabilities into the real world seamlessly.

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