Best AI tools for< Mitigate Data Imbalances >

DVC is an open-source platform for managing machine learning data and experiments. It provides a unified interface for working with data from various sources, including local files, cloud storage, and databases. DVC also includes tools for versioning data and experiments, tracking metrics, and automating compute resources. DVC is designed to make it easy for data scientists and machine learning engineers to collaborate on projects and share their work with others.

Privado AI is a privacy engineering tool that bridges the gap between privacy compliance and software development. It automates personal data visibility and privacy governance, helping organizations to identify privacy risks, track data flows, and ensure compliance with regulations such as CPRA, MHMDA, FTC, and GDPR. The tool provides real-time visibility into how personal data is collected, used, shared, and stored by scanning the code of websites, user-facing applications, and backend systems. Privado offers features like Privacy Code Scanning, programmatic privacy governance, automated GDPR RoPA reports, risk identification without assessments, and developer-friendly privacy guidance.

Ergodic is an AI tool called Kepler that enables data-driven decisions for businesses. Kepler acts as an AI action engine, bridging the knowledge gap between business context and data to help optimize processes, identify opportunities, and mitigate risks. It goes beyond number crunching to build a digital version of the business, allowing users to create scenarios and evaluate outcomes. Kepler focuses on taking action directly, without the need for complex dashboards, providing insights on what needs to be done, why, and the potential outcomes. Ergodic aims to empower businesses with AI-driven solutions for strategic decision-making.

Perceive Now is the world's first Large Language Model fine-tuned with IP and Market Research data. It offers custom IP and Market reports for various industries, providing detailed insights and analysis to support decision-making processes. The platform helps in identifying market trends, conducting due diligence, managing deal flow, and maximizing IP and licensing opportunities. Perceive Now is a game-changer in prior art search, increasing the odds of patent grant success. It has significantly reduced research costs and time, accessing over 100M IP and market data sources and assisting in securing funding worth $500M.

Aporia is an AI control platform that provides real-time guardrails and security for AI applications. It offers features such as hallucination mitigation, prompt injection prevention, data leakage prevention, and more. Aporia helps businesses control and mitigate risks associated with AI, ensuring the safe and responsible use of AI technology.

Alteryx offers a leading AI Platform for Enterprise Analytics that delivers actionable insights by automating analytics. The platform combines the power of data preparation, analytics, and machine learning to help businesses make better decisions faster. With Alteryx, businesses can connect to a wide variety of data sources, prepare and clean data, perform advanced analytics, and build and deploy machine learning models. The platform is designed to be easy to use, even for non-technical users, and it can be deployed on-premises or in the cloud.

Intelligencia AI is a leading provider of AI-powered solutions for the pharmaceutical industry. Our suite of solutions helps de-risk and enhance clinical development and decision-making. We use a combination of data, AI, and machine learning to provide insights into the probability of success for drugs across multiple therapeutic areas. Our solutions are used by many of the top global pharmaceutical companies to improve their R&D productivity and make more informed decisions.

Sweephy is an AI tool for Regulation Monitoring that helps businesses stay ahead with instant notifications for upcoming regulations, mitigate risks of non-compliance, and avoid potential fines. It simplifies compliance management by integrating directly with regulatory data sources and streamlining monitoring and adaptation to changes through one platform. Sweephy provides comprehensive tools for region-specific compliance, automated data collection, custom notifications, and instant red flag alerts. The platform also offers real-time updates and insights from various publications, direct integration with regulatory databases, and an API for bringing regulatory data into internal systems. Clients from 5 different countries trust Sweephy for deciphering complex regulatory updates and ensuring compliance.

Kira Systems is a machine learning contract search, review, and analysis software that helps businesses identify, extract, and analyze content in their contracts and documents. It uses patented machine learning technology to extract concepts and data points with high efficiency and accuracy. Kira also has built-in intelligence that streamlines the contract review process with out-of-the-box smart fields. Businesses can also create their own smart fields to find specific data points using Kira's no-code machine learning tool. Kira's adaptive workflows allow businesses to organize, track, and export results. Kira has a partner ecosystem that allows businesses to transform how teams work with their contracts.

CrowdStrike is a cloud-based cybersecurity platform that provides endpoint protection, threat intelligence, and incident response services. It uses artificial intelligence (AI) to detect and prevent cyberattacks. CrowdStrike's platform is designed to be scalable and easy to use, and it can be deployed on-premises or in the cloud. CrowdStrike has a global customer base of over 23,000 organizations, including many Fortune 500 companies.

Trade Ideas is an AI-driven stock scanning and charting platform that provides unmatched precision in finding the biggest movers first. It offers AI-powered Buy/Sell signals, real-time market scanning, customizable alerts, advanced charting capabilities, and time-saving data visualization. Users can access the platform on any device, empowering them to make smarter trading decisions and stay ahead of the game. Trade Ideas also features a live trading room with expert market commentary and a simulator for practicing new trading strategies under actual market conditions. The platform is trusted by leading brokers and trading platforms, offering users a competitive edge in the market.

Fordi is an AI management tool that helps businesses avoid risks in real-time. It provides a comprehensive view of all AI systems, allowing businesses to identify and mitigate risks before they cause damage. Fordi also provides continuous monitoring and alerting, so businesses can be sure that their AI systems are always operating safely.

Athina AI is a platform that provides research and guides for building safe and reliable AI products. It helps thousands of AI engineers in building safer products by offering tutorials, research papers, and evaluation techniques related to large language models. The platform focuses on safety, prompt engineering, hallucinations, and evaluation of AI models.

Brighterion AI, a Mastercard company, offers advanced AI solutions for financial institutions, merchants, and healthcare providers. With over 20 years of experience, Brighterion has revolutionized AI by providing market-ready models that enhance customer experience, reduce financial fraud, and mitigate risks. Their solutions are enriched with Mastercard's global network intelligence, ensuring scalability and powerful personalization. Brighterion's AI applications cater to acquirers, PSPs, issuers, and healthcare providers, offering custom AI solutions for transaction fraud monitoring, merchant monitoring, AML & compliance, and healthcare fraud detection. The company has received several prestigious awards for its excellence in AI and financial security.

Adversa AI is a platform that provides Secure AI Awareness, Assessment, and Assurance solutions for various industries to mitigate AI risks. The platform focuses on LLM Security, Privacy, Jailbreaks, Red Teaming, Chatbot Security, and AI Face Recognition Security. Adversa AI helps enable AI transformation by protecting it from cyber threats, privacy issues, and safety incidents. The platform offers comprehensive research, advisory services, and expertise in the field of AI security.

Protect AI is a comprehensive platform designed to secure AI systems by providing visibility and manageability to detect and mitigate unique AI security threats. The platform empowers organizations to embrace a security-first approach to AI, offering solutions for AI Security Posture Management, ML model security enforcement, AI/ML supply chain vulnerability database, LLM security monitoring, and observability. Protect AI aims to safeguard AI applications and ML systems from potential vulnerabilities, enabling users to build, adopt, and deploy AI models confidently and at scale.

Responsible AI Licenses (RAIL) is an initiative that empowers developers to restrict the use of their AI technology to prevent irresponsible and harmful applications. They provide licenses with behavioral-use clauses to control specific use-cases and prevent misuse of AI artifacts. The organization aims to standardize RAIL Licenses, develop collaboration tools, and educate developers on responsible AI practices.

CoFinance is an AI-driven legal intelligence and collaboration hub that revolutionizes legal and compliance research workflows. It combines semantic search, multi-faceted document analysis, and intelligent organization tools to provide precise and efficient research solutions. The platform leverages cutting-edge Regulatory Artificial Intelligence (RAI) technology to ensure that answers are sourced from real, authoritative data. CoFinance prioritizes simplifying regulatory complexity, mitigating compliance risks, accelerating research efficiency, and providing reliable partnership for long-term compliance success. It caters to organizations navigating complex regulatory landscapes, offering quick adaptation to changes and seamless compliance across various industries and jurisdictions.

ModelOp is the leading AI Governance software for enterprises, providing a single source of truth for all AI systems, automated process workflows, real-time insights, and integrations to extend the value of existing technology investments. It helps organizations safeguard AI initiatives without stifling innovation, ensuring compliance, accelerating innovation, and improving key performance indicators. ModelOp supports generative AI, Large Language Models (LLMs), in-house, third-party vendor, and embedded systems. The software enables visibility, accountability, risk tiering, systemic tracking, enforceable controls, workflow automation, reporting, and rapid establishment of AI governance.

AI Clearing is an AI-powered construction progress monitoring tool that specializes in digital field construction progress tracking. The platform leverages machine learning technology and drone-captured data to generate comprehensive 3D site reports, automate advanced geospatial analytics, and provide actionable insights through interactive dashboards and PDF reports. AI Clearing aims to streamline progress monitoring, reduce re-work costs, mitigate litigation risks, and improve communication with stakeholders in the construction industry.

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment interfaces and libraries for understanding AI systems. It empowers developers and stakeholders to develop and monitor AI responsibly, enabling better data-driven actions. The toolbox includes visualization widgets for model assessment, error analysis, interpretability, fairness assessment, and mitigations library. It also offers a JupyterLab extension for managing machine learning experiments and a library for measuring gender bias in NLP datasets.

A comprehensive repository focusing on 'Model Merging in LLMs, MLLMs, and Beyond', providing an exhaustive overview of model merging methods, theories, applications, and future research directions. The repository covers various advanced methods, applications in foundation models, different machine learning subfields, and tasks like pre-merging methods, architecture transformation, weight alignment, basic merging methods, and more.

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.

A public repository collecting links to state-of-the-art training sets, QA, benchmarks and other evaluations for various ML and LLM applications in materials science and chemistry. It includes datasets related to chemistry, materials, multimodal data, and knowledge graphs in the field. The repository aims to provide resources for training and evaluating machine learning models in the materials science and chemistry domains.

Guardrails is a Python framework that helps build reliable AI applications by performing two key functions: 1. Guardrails runs Input/Output Guards in your application that detect, quantify and mitigate the presence of specific types of risks. To look at the full suite of risks, check out Guardrails Hub. 2. Guardrails help you generate structured data from LLMs.

Fairlearn is a Python package designed to help developers assess and mitigate fairness issues in artificial intelligence (AI) systems. It provides mitigation algorithms and metrics for model assessment. Fairlearn focuses on two types of harms: allocation harms and quality-of-service harms. The package follows the group fairness approach, aiming to identify groups at risk of experiencing harms and ensuring comparable behavior across these groups. Fairlearn consists of metrics for assessing model impacts and algorithms for mitigating unfairness in various AI tasks under different fairness definitions.

The AI Fairness 360 toolkit is an open-source library designed to detect and mitigate bias in machine learning models. It provides a comprehensive set of metrics, explanations, and algorithms for bias mitigation in various domains such as finance, healthcare, and education. The toolkit supports multiple bias mitigation algorithms and fairness metrics, and is available in both Python and R. Users can leverage the toolkit to ensure fairness in AI applications and contribute to its development for extensibility.

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.

Upgini is an intelligent data search engine with a Python library that helps users find and add relevant features to their ML pipeline from various public, community, and premium external data sources. It automates the optimization of connected data sources by generating an optimal set of machine learning features using large language models, GraphNNs, and recurrent neural networks. The tool aims to simplify feature search and enrichment for external data to make it a standard approach in machine learning pipelines. It democratizes access to data sources for the data science community.

DataDreamer is an advanced toolkit designed to facilitate the development of edge AI models by enabling synthetic data generation, knowledge extraction from pre-trained models, and creation of efficient and potent models. It eliminates the need for extensive datasets by generating synthetic datasets, leverages latent knowledge from pre-trained models, and focuses on creating compact models suitable for integration into any device and performance for specialized tasks. The toolkit offers features like prompt generation, image generation, dataset annotation, and tools for training small-scale neural networks for edge deployment. It provides hardware requirements, usage instructions, available models, and limitations to consider while using the library.

YuLan-Mini is a lightweight language model with 2.4 billion parameters that achieves performance comparable to industry-leading models despite being pre-trained on only 1.08T tokens. It excels in mathematics and code domains. The repository provides pre-training resources, including data pipeline, optimization methods, and annealing approaches. Users can pre-train their own language models, perform learning rate annealing, fine-tune the model, research training dynamics, and synthesize data. The team behind YuLan-Mini is AI Box at Renmin University of China. The code is released under the MIT License with future updates on model weights usage policies. Users are advised on potential safety concerns and ethical use of the model.

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

Cambrian-1 is a fully open project focused on exploring multimodal Large Language Models (LLMs) with a vision-centric approach. It offers competitive performance across various benchmarks with models at different parameter levels. The project includes training configurations, model weights, instruction tuning data, and evaluation details. Users can interact with Cambrian-1 through a Gradio web interface for inference. The project is inspired by LLaVA and incorporates contributions from Vicuna, LLaMA, and Yi. Cambrian-1 is licensed under Apache 2.0 and utilizes datasets and checkpoints subject to their respective original licenses.

MATLAB-Simulink-Challenge-Project-Hub is a repository aimed at contributing to the progress of engineering and science by providing challenge projects with real industry relevance and societal impact. The repository offers a wide range of projects covering various technology trends such as Artificial Intelligence, Autonomous Vehicles, Big Data, Computer Vision, and Sustainability. Participants can gain practical skills with MATLAB and Simulink while making a significant contribution to science and engineering. The projects are designed to enhance expertise in areas like Sustainability and Renewable Energy, Control, Modeling and Simulation, Machine Learning, and Robotics. By participating in these projects, individuals can receive official recognition for their problem-solving skills from technology leaders at MathWorks and earn rewards upon project completion.

LLM Foundry is a codebase for training, finetuning, evaluating, and deploying LLMs for inference with Composer and the MosaicML platform. It is designed to be easy-to-use, efficient _and_ flexible, enabling rapid experimentation with the latest techniques. You'll find in this repo: * `llmfoundry/` - source code for models, datasets, callbacks, utilities, etc. * `scripts/` - scripts to run LLM workloads * `data_prep/` - convert text data from original sources to StreamingDataset format * `train/` - train or finetune HuggingFace and MPT models from 125M - 70B parameters * `train/benchmarking` - profile training throughput and MFU * `inference/` - convert models to HuggingFace or ONNX format, and generate responses * `inference/benchmarking` - profile inference latency and throughput * `eval/` - evaluate LLMs on academic (or custom) in-context-learning tasks * `mcli/` - launch any of these workloads using MCLI and the MosaicML platform * `TUTORIAL.md` - a deeper dive into the repo, example workflows, and FAQs

The Artificial Intelligence Incident Database (AIID) is a collection of incidents involving the development and use of artificial intelligence (AI). The database is designed to help researchers, policymakers, and the public understand the potential risks and benefits of AI, and to inform the development of policies and practices to mitigate the risks and promote the benefits of AI. The AIID is a collaborative project involving researchers from the University of California, Berkeley, the University of Washington, and the University of Toronto.

The discourse-chatbot is an original AI chatbot for Discourse forums that allows users to converse with the bot in posts or chat channels. Users can customize the character of the bot, enable RAG mode for expert answers, search Wikipedia, news, and Google, provide market data, perform accurate math calculations, and experiment with vision support. The bot uses cutting-edge Open AI API and supports Azure and proxy server connections. It includes a quota system for access management and can be used in RAG mode or basic bot mode. The setup involves creating embeddings to make the bot aware of forum content and setting up bot access permissions based on trust levels. Users must obtain an API token from Open AI and configure group quotas to interact with the bot. The plugin is extensible to support other cloud bots and content search beyond the provided set.

Expert in data disclosure risk analysis, mitigation, and modeling methods.

Guide on AI implementation for secure data, with a focus on best practices and tools.

The pressing environmental issues we face today require novel approaches and technological advancements to effectively mitigate their impacts. GaiaAI offers a range of tools and modes to promote sustainable practices and enhance environmental stewardship.

Guides on mitigating bias and fairness in AI.

Accountable AI represents a step forward in creating a more ethical, transparent, and responsible AI system, tailored to meet the demands of users who prioritize accountability and unbiased information in their AI interactions.

Expert in AI fairness, offering tailored advice and document insights.

Clarity in Risk Management

A helpful guide for understanding the paper "Anatomy of an AI-powered malicious social botnet"

Helps you build logic security into your GPTs custom instructions. Documentation: https://github.com/infotrix/SSLLMs---Semantic-Secuirty-for-LLM-GPTs

Advises on managing technology risks to safeguard organization.

Risk assessment advisor for business challenges

An automated cyber threat intelligence expert configured and trained by Bob Gourley. Pls provide feedback. Find Bob on X at @bobgourley

Assesses project risks to mitigate potential organizational impacts.

Manages and mitigates financial liquidity risks effectively.

Optimizes financial liquidity, mitigates operational risk, and enhances financial performance.

it is a meticulously crafted arsenal of knowledge, insights, and guidelines that is shaped to empower organizations in crafting, enhancing, and refining their cybersecurity defenses

Guides through Prince2 questions and answers, ensuring accuracy and engagement.

Detailed CVE analysis, focusing on chaining and APTs, using a fixed schema.

A cute sheep expert in risk analysis, providing downloadable checklists.

Assists in vendor risk evaluation for security, legal, and privacy.