Best AI tools for< Improve Model Transparency >

Copyleaks is an AI-based plagiarism and AI content detection tool that empowers users to create and protect original content. It offers solutions for academic integrity, AI model training, IP and copyright protection, and code governance and compliance. With features like AI Detector, Plagiarism Detector, Writing Assistant, and API integrations, Copyleaks ensures content integrity and transparency. The tool performs over 30 million scans per month across 100+ countries, catering to institutions, enterprises, and individuals. Copyleaks prioritizes data security and compliance, being GDPR-compliant and SOC 2 and SOC 3 certified.

DeepScribe is an AI medical scribe application that leverages advanced speech recognition technology to capture clinical conversations with extreme accuracy. It empowers clinicians and health systems with real-time AI insights, offers customization options to match provider workflows, and ensures trust and safety through features that promote AI transparency. DeepScribe is designed to save time, improve accuracy, drive adoption, and maximize revenue for doctors, hospitals, and health systems. The application is built for enterprise use, allowing users to unlock the power of AI and modernize their patient data strategy.

Defined.ai is a leading provider of high-quality and ethical data for AI applications. Founded in 2015, Defined.ai has a global presence with offices in the US, Europe, and Asia. The company's mission is to make AI more accessible and ethical by providing a marketplace for buying and selling AI data, tools, and models. Defined.ai also offers professional services to help deliver success in complex machine learning projects.

Profit Isle is an AI application that helps enterprises make data-driven decisions to enhance profitability and drive value to the bottom line. The platform integrates and transforms enterprise data to power AI initiatives, providing actionable insights and recommendations grounded in company data. Profit Isle prioritizes transparency, data governance, and privacy to ensure customers can confidently run AI models and make informed decisions.

Flow AI is an advanced AI tool designed for evaluating and improving Large Language Model (LLM) applications. It offers a unique system for creating custom evaluators, deploying them with an API, and developing specialized LMs tailored to specific use cases. The tool aims to revolutionize AI evaluation and model development by providing transparent, cost-effective, and controllable solutions for AI teams across various domains.

Zest AI is an AI-driven credit underwriting software that offers a complete solution for AI-driven lending. It enables users to build custom machine learning risk models, adopt model assessment and regulatory compliance, and operate performance management and model monitoring. Zest AI helps increase approvals, manage risk, control loss, drive operational efficiency, automate credit decisioning, and improve borrower experience while ensuring fair lending practices. The software is designed to provide fair and transparent credit for everyone, making lending more accessible and inclusive.

Segwise is an AI tool designed to help game developers increase their game's Lifetime Value (LTV) by providing insights into player behavior and metrics. The tool uses AI agents to detect causal LTV drivers, root causes of LTV drops, and opportunities for growth. Segwise offers features such as running causal inference models on player data, hyper-segmenting player data, and providing instant answers to questions about LTV metrics. It also promises seamless integrations with gaming data sources and warehouses, ensuring data ownership and transparent pricing. The tool aims to simplify the process of improving LTV for game developers.

Gardian is an AI tool designed to streamline content analysis processes by leveraging advanced AI technology. It allows users to create custom AI Agents with specific labels to detect and manage content that violates company policies. Gardian offers pre-configured models, custom analysis labels, a simple API for integration, multilanguage support, transparent pricing, and privacy protection. It serves various use cases such as content moderation, live chat moderation, and customer sentiment analysis, providing valuable insights and enhancing user experience.

Censius is an AI Observability Platform for Enterprise ML Teams. It provides end-to-end visibility of structured and unstructured production models, enabling proactive model management and continuous delivery of reliable ML. Key features include model monitoring, explainability, and analytics.

Appen is a leading provider of high-quality data for training AI models. The company's end-to-end platform, flexible services, and deep expertise ensure the delivery of high-quality, diverse data that is crucial for building foundation models and enterprise-ready AI applications. Appen has been providing high-quality datasets that power the world's leading AI models for decades. The company's services enable it to prepare data at scale, meeting the demands of even the most ambitious AI projects. Appen also provides enterprises with software to collect, curate, fine-tune, and monitor traditionally human-driven tasks, creating massive efficiencies through a trustworthy, traceable process.

Image In Words is a generative model designed for scenarios that require generating ultra-detailed text from images. It leverages cutting-edge image recognition technology to provide high-quality and natural image descriptions. The framework ensures detailed and accurate descriptions, improves model performance, reduces fictional content, enhances visual-language reasoning capabilities, and has wide applications across various fields. Image In Words supports English and has been trained using approximately 100,000 hours of English data. It has demonstrated high quality and naturalness in various tests.

Fine-Tune AI is a tool that allows users to generate fine-tune data sets using prompts. This can be useful for a variety of tasks, such as improving the accuracy of machine learning models or creating new training data for AI applications.

Gretel.ai is a synthetic data platform designed for Generative AI applications. It allows users to generate artificial datasets with the same characteristics as real data, enabling the improvement of AI models without compromising privacy. The platform offers various features such as building synthetic data pipelines, rule-based data transformation, measuring data quality, and customizing language models. Gretel.ai is suitable for industries like finance, healthcare, and the public sector, providing a secure and efficient solution for data generation and model enhancement.

Voxel51 is an AI tool that provides open-source computer vision tools for machine learning. It offers solutions for various industries such as agriculture, aviation, driving, healthcare, manufacturing, retail, robotics, and security. Voxel51's main product, FiftyOne, helps users explore, visualize, and curate visual data to improve model performance and accelerate the development of visual AI applications. The platform is trusted by thousands of users and companies, offering both open-source and enterprise-ready solutions to manage and refine data and models for visual AI.

Bifrost AI is a data generation engine designed for AI and robotics applications. It enables users to train and validate AI models faster by generating physically accurate synthetic datasets in 3D simulations, eliminating the need for real-world data. The platform offers pixel-perfect labels, scenario metadata, and a simulated 3D world to enhance AI understanding. Bifrost AI empowers users to create new scenarios and datasets rapidly, stress test AI perception, and improve model performance. It is built for teams at every stage of AI development, offering features like automated labeling, class imbalance correction, and performance enhancement.

Cradle is a protein engineering platform that uses machine learning to design improved protein sequences. It allows users to import assay data, generate new sequences, test them in the lab, and import the results to improve the model. Cradle can be used to optimize multiple properties of a protein simultaneously, and it has been used by leading biotech teams to accelerate new and ongoing projects.

Langtrace AI is an open-source observability tool powered by Scale3 Labs that helps monitor, evaluate, and improve LLM (Large Language Model) applications. It collects and analyzes traces and metrics to provide insights into the ML pipeline, ensuring security through SOC 2 Type II certification. Langtrace supports popular LLMs, frameworks, and vector databases, offering end-to-end observability and the ability to build and deploy AI applications with confidence.

Sapling is a language model copilot and API for businesses. It provides real-time suggestions to help sales, support, and success teams more efficiently compose personalized responses. Sapling also offers a variety of features to help businesses improve their customer service, including: * Autocomplete Everywhere: Provides deep learning-powered autocomplete suggestions across all messaging platforms, allowing agents to compose replies more quickly. * Sapling Suggest: Retrieves relevant responses from a team response bank and allows agents to respond more quickly to customer inquiries by simply clicking on suggested responses in real time. * Snippet macros: Allow for quick insertion of common responses. * Grammar and language quality improvements: Sapling catches 60% more language quality issues than other spelling and grammar checkers using a machine learning system trained on millions of English sentences. * Enterprise teams can define custom settings for compliance and content governance. * Distribute knowledge: Ensure team knowledge is shared in a snippet library accessible on all your web applications. * Perform blazing fast search on your knowledge library for compliance, upselling, training, and onboarding.

OpenAI Strawberry Model is a cutting-edge AI initiative that represents a significant leap in AI capabilities, focusing on enhancing reasoning, problem-solving, and complex task execution. It aims to improve AI's ability to handle mathematical problems, programming tasks, and deep research, including long-term planning and action. The project showcases advancements in AI safety and aims to reduce errors in AI responses by generating high-quality synthetic data for training future models. Strawberry is designed to achieve human-like reasoning and is expected to play a crucial role in the development of OpenAI's next major model, codenamed 'Orion.'

QOVES is a website that provides tools and advice to help people improve their looks. The website offers a variety of services, including facial analysis, hairline design, style advice, and Photoshop retouching. QOVES also has a blog with articles on a variety of topics related to beauty and aesthetics.

This repository is a collection of resources focused on interpretability in large language models (LLMs). It aims to help beginners get started in the area and keep researchers updated on the latest progress. It includes libraries, blogs, tutorials, forums, tools, programs, papers, and more related to interpretability in LLMs.

This is the official repository for 'Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing'. Magpie is a tool designed to synthesize high-quality instruction data at scale by extracting it directly from an aligned Large Language Models (LLMs). It aims to democratize AI by generating large-scale alignment data and enhancing the transparency of model alignment processes. Magpie has been tested on various model families and can be used to fine-tune models for improved performance on alignment benchmarks such as AlpacaEval, ArenaHard, and WildBench.

Awesome-Attention-Heads is a platform providing the latest research on Attention Heads, focusing on enhancing understanding of Transformer structure for model interpretability. It explores attention mechanisms for behavior, inference, and analysis, alongside feed-forward networks for knowledge storage. The repository aims to support researchers studying LLM interpretability and hallucination by offering cutting-edge information on Attention Head Mining.

Awesome MLSecOps is a curated list of open-source tools, resources, and tutorials for MLSecOps (Machine Learning Security Operations). It includes a wide range of security tools and libraries for protecting machine learning models against adversarial attacks, as well as resources for AI security, data anonymization, model security, and more. The repository aims to provide a comprehensive collection of tools and information to help users secure their machine learning systems and infrastructure.

Awesome Responsible AI is a curated list of academic research, books, code of ethics, courses, data sets, frameworks, institutes, newsletters, principles, podcasts, reports, tools, regulations, and standards related to Responsible, Trustworthy, and Human-Centered AI. It covers various concepts such as Responsible AI, Trustworthy AI, Human-Centered AI, Responsible AI frameworks, AI Governance, and more. The repository provides a comprehensive collection of resources for individuals interested in ethical, transparent, and accountable AI development and deployment.

AIDE is a machine learning code generation agent that can generate solutions for machine learning tasks from natural language descriptions. It has the following features: 1. **Instruct with Natural Language**: Describe your problem or additional requirements and expert insights, all in natural language. 2. **Deliver Solution in Source Code**: AIDE will generate Python scripts for the **tested** machine learning pipeline. Enjoy full transparency, reproducibility, and the freedom to further improve the source code! 3. **Iterative Optimization**: AIDE iteratively runs, debugs, evaluates, and improves the ML code, all by itself. 4. **Visualization**: We also provide tools to visualize the solution tree produced by AIDE for a better understanding of its experimentation process. This gives you insights not only about what works but also what doesn't. AIDE has been benchmarked on over 60 Kaggle data science competitions and has demonstrated impressive performance, surpassing 50% of Kaggle participants on average. It is particularly well-suited for tasks that require complex data preprocessing, feature engineering, and model selection.

ClearML is a suite of tools designed to streamline the machine learning workflow. It includes an experiment manager, MLOps/LLMOps, data management, and model serving capabilities. ClearML is open-source and offers a free tier hosting option. It supports various ML/DL frameworks and integrates with Jupyter Notebook and PyCharm. ClearML provides extensive logging capabilities, including source control info, execution environment, hyper-parameters, and experiment outputs. It also offers automation features, such as remote job execution and pipeline creation. ClearML is designed to be easy to integrate, requiring only two lines of code to add to existing scripts. It aims to improve collaboration, visibility, and data transparency within ML teams.

PIXIU is a project designed to support the development, fine-tuning, and evaluation of Large Language Models (LLMs) in the financial domain. It includes components like FinBen, a Financial Language Understanding and Prediction Evaluation Benchmark, FIT, a Financial Instruction Dataset, and FinMA, a Financial Large Language Model. The project provides open resources, multi-task and multi-modal financial data, and diverse financial tasks for training and evaluation. It aims to encourage open research and transparency in the financial NLP field.

Instructor for PHP is a library designed for structured data extraction in PHP, powered by Large Language Models (LLMs). It simplifies the process of extracting structured, validated data from unstructured text or chat sequences. Instructor enhances workflow by providing a response model, validation capabilities, and max retries for requests. It supports classes as response models and provides features like partial results, string input, extracting scalar and enum values, and specifying data models using PHP type hints or DocBlock comments. The library allows customization of validation and provides detailed event notifications during request processing. Instructor is compatible with PHP 8.2+ and leverages PHP reflection, Symfony components, and SaloonPHP for communication with LLM API providers.

UpTrain is an open-source unified platform to evaluate and improve Generative AI applications. We provide grades for 20+ preconfigured evaluations (covering language, code, embedding use cases), perform root cause analysis on failure cases and give insights on how to resolve them.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

MInference is a tool designed to accelerate pre-filling for long-context Language Models (LLMs) by leveraging dynamic sparse attention. It achieves up to a 10x speedup for pre-filling on an A100 while maintaining accuracy. The tool supports various decoding LLMs, including LLaMA-style models and Phi models, and provides custom kernels for attention computation. MInference is useful for researchers and developers working with large-scale language models who aim to improve efficiency without compromising accuracy.

The Bee Agent Framework is an open-source tool for building, deploying, and serving powerful agentic workflows at scale. It provides AI agents, tools for creating workflows in Javascript/Python, a code interpreter, memory optimization strategies, serialization for pausing/resuming workflows, traceability features, production-level control, and upcoming features like model-agnostic support and a chat UI. The framework offers various modules for agents, llms, memory, tools, caching, errors, adapters, logging, serialization, and more, with a roadmap including MLFlow integration, JSON support, structured outputs, chat client, base agent improvements, guardrails, and evaluation.

Moved to https://chat.openai.com/g/g-KFnF7qssT-palm-reader . Interprets palm readings from user-uploaded hand images. Turned off setting to use data for OpenAi to improve model.

Moved to https://chat.openai.com/g/g-q6GNcOkYx-face-reader. Reads faces to tell fortunes based on Chinese face reading. Turned off setting to use data for OpenAi to improve model.

I'm Back Propagation, here to help you understand and apply back propagation techniques to your AI models.

An assistant to help you understand transfer learning better

Business model expert, create detailed reports based on business ideas.

Rate AI-created model portraits on a 1-10 scale.

CUDA and Triton expert with concise, accurate answers.

I'm a ML engineer who formats code.

A software architect for C4 Model generation.

Let's get started by telling me about your business: What do you offer? Who do you serve? ------------------------------------------------------- Need help Prompt Engineering? Reach out on LinkedIn: StephenHnilica

Un aiuto a costruire il Business Model Canvas della tua iniziativa

Guía paso a paso para la creación y mejora de modelos de negocio usando la metodología Business Model Canvas.

Educational feedback using RISE Model

Expert in refining custom GPT model instructions.

This GPT generates the best possible LLM-agents for your system prompts. You can also specify the model size, like 3B, 33B, 70B, etc.

Professionally finds top custom GPT models for specific topics

Evaluates faces and rates them out of 10 ⭐ Provides valuable feedback to improving your attractiveness!

あなたの顔写真を送付するだけで顔面偏差値を出力してくれます。各項目別に点数付けしてくれて、顔の強みや特徴まで分析してくれるツール。

I provide consistent age guesses and reasons from photos.