Best AI tools for< Interpret Models >

Enterprise AI provides comprehensive information, news, and tips on artificial intelligence (AI) for businesses. It covers various aspects of AI, including AI business strategies, AI infrastructure, AI technologies, AI platforms, careers in AI, and enterprise applications of AI. The website offers insights into the latest AI trends, best practices, and industry news. It also provides resources such as e-books, webinars, and podcasts to help businesses understand and implement AI solutions.

U-xer is an innovative automation tool developed by Quality Museum Software Testing Services. It is designed to meet a broad range of needs, including Robotic Process Automation (RPA), test automation, and bot development. Crafted with user flexibility in mind, U-xer aims to be a user-friendly solution for your automation requirements! U-xer's unique screen recognition models interpret screens in the same way that humans do. This enables non-technical users to automate simple tasks, while allowing advanced users to tackle more complex tasks with ease. With U-xer, you can automate anything, anywhere, whether it's Web or Desktop. U-xer works seamlessly across all platforms with just a screenshot. Unlike other tools, U-xer interprets screens just like a human does, enabling more natural and accurate automation of a wide range of tasks.

CrayEye is a multimodal multitool that allows users to craft and share vision prompts infused with real-world context from device sensors and APIs. It is a free, open-source tool written by AI, enabling users to experiment with visual multimodal models and interpret their environment in new ways. Users can analyze their surroundings using their smartphone's camera, customize prompts augmented by sensors and APIs, and share their creations with friends. CrayEye is a product of AI-driven development, offering a range of features to enhance user experience.

xAI Grok is a visual analytics platform that helps users understand and interpret machine learning models. It provides a variety of tools for visualizing and exploring model data, including interactive charts, graphs, and tables. xAI Grok also includes a library of pre-built visualizations that can be used to quickly get started with model analysis.

Kombai is an AI tool designed to code email and web designs like humans. It uses deep learning and heuristics models to interpret UI designs and generate high-quality HTML, CSS, or React code with human-like names for classes and components. Kombai aims to help developers save time by automating the process of writing UI code based on design files without the need for tagging, naming, or grouping elements. The tool is currently in 'public research preview' and is free for individual developers to use.

FairPlay is a Fairness-as-a-Service solution designed for financial institutions, offering AI-powered tools to assess automated decisioning models quickly. It helps in increasing fairness and profits by optimizing marketing, underwriting, and pricing strategies. The application provides features such as Fairness Optimizer, Second Look, Customer Composition, Redline Status, and Proxy Detection. FairPlay enables users to identify and overcome tradeoffs between performance and disparity, assess geographic fairness, de-bias proxies for protected classes, and tune models to reduce disparities without increasing risk. It offers advantages like increased compliance, speed, and readiness through automation, higher approval rates with no increase in risk, and rigorous Fair Lending analysis for sponsor banks and regulators. However, some disadvantages include the need for data integration, potential bias in AI algorithms, and the requirement for technical expertise to interpret results.

The Human-Centred Artificial Intelligence Lab (Holzinger Group) is a research group focused on developing AI solutions that are explainable, trustworthy, and aligned with human values, ethical principles, and legal requirements. The lab works on projects related to machine learning, digital pathology, interactive machine learning, and more. Their mission is to combine human and computer intelligence to address pressing problems in various domains such as forestry, health informatics, and cyber-physical systems. The lab emphasizes the importance of explainable AI, human-in-the-loop interactions, and the synergy between human and machine intelligence.

Tredence is a data science and AI services company that provides end-to-end solutions for businesses across various industries. The company's services include data engineering, data analytics, AI consulting, and machine learning operations (MLOps). Tredence has a team of experienced data scientists and engineers who use their expertise to help businesses solve complex data challenges and achieve their business goals.

Tecnotree is a full-stack digital BSS provider with over 40 years of deep domain knowledge, proven delivery and transformation capability across the globe.

IndieFeel is a website that provides interpretations of songs, movies, and poems. It uses large language models to generate these interpretations, which can be helpful for understanding the meaning of a work of art or getting a different perspective on it. The website is still in beta, but it already has a number of interpretations available, and the quality of the interpretations is generally good.

Cuckoo is an AI interpreter designed for global teams, offering seamless multilingual conversation support for sales, marketing, and customer support interactions. It enables users to effortlessly communicate in multiple languages during meetings and events, adapting to conversations of any size and topic. Cuckoo is powered by large language models, speaks 20+ languages, and can be integrated with popular communication platforms like Zoom, Google Meet, Slack, and Microsoft Teams. The application is user-friendly, requires no prior arrangements or rehearsals, and provides real-time interpretation on the fly.

Molmo AI is a powerful, open-source multimodal AI model revolutionizing visual understanding. It helps developers easily build tools that can understand images and interact with the world in useful ways. Molmo AI offers exceptional image understanding, efficient data usage, open and accessible features, on-device compatibility, and a new era in multimodal AI development. It closes the gap between open and closed AI models, empowers the AI community with open access, and efficiently utilizes data for superior performance.

LLMMM is an AI tool designed to monitor how AI models perceive and present brands. It offers real-time monitoring and cross-model insights to help brands understand their digital presence across various leading AI platforms. With automated analysis and lightning-fast results, LLMMM provides immediate visibility into how AI chatbots interpret brands. The tool focuses on brand intelligence, brand safety monitoring, misalignment detection, and cross-model brand intelligence. Users can create an account in minutes and access a range of features to track and analyze their brand's performance in the AI landscape.

ChatTab is a desktop application for macOS that serves as a ChatGPT API client, offering a seamless experience for users to interact with various GPT models. It provides a native Mac app with features like Markdown support, multiple tabs for conversations, shortcut keys, iCloud sync, and GPT4-Vision for image-related queries. ChatTab prioritizes security and privacy by not storing user data or logs, and encrypting the API Key. It supports multiple languages and offers different pricing plans to cater to various user needs.

Grok-1.5 Vision (Grok-1.5V) is a groundbreaking multimodal AI model developed by Elon Musk's research lab, x.AI. This advanced model has the potential to revolutionize the field of artificial intelligence and shape the future of various industries. Grok-1.5V combines the capabilities of computer vision, natural language processing, and other AI techniques to provide a comprehensive understanding of the world around us. With its ability to analyze and interpret visual data, Grok-1.5V can assist in tasks such as object recognition, image classification, and scene understanding. Additionally, its natural language processing capabilities enable it to comprehend and generate human language, making it a powerful tool for communication and information retrieval. Grok-1.5V's multimodal nature sets it apart from traditional AI models, allowing it to handle complex tasks that require a combination of visual and linguistic understanding. This makes it a valuable asset for applications in fields such as healthcare, manufacturing, and customer service.

Ogma is an interpretable symbolic general problem-solving model that utilizes a symbolic sequence modeling paradigm to address tasks requiring reliability, complex decomposition, and without hallucinations. It offers solutions in areas such as math problem-solving, natural language understanding, and resolution of uncertainty. The technology is designed to provide a structured approach to problem-solving by breaking down tasks into manageable components while ensuring interpretability and self-interpretability. Ogma aims to set benchmarks in problem-solving applications by offering a reliable and transparent methodology.

Eigen Technologies is an AI-powered data extraction platform designed for business users to automate the extraction of data from various documents. The platform offers solutions for intelligent document processing and automation, enabling users to streamline business processes, make informed decisions, and achieve significant efficiency gains. Eigen's platform is purpose-built to deliver real ROI by reducing manual processes, improving data accuracy, and accelerating decision-making across industries such as corporates, banks, financial services, insurance, law, and manufacturing. With features like generative insights, table extraction, pre-processing hub, and model governance, Eigen empowers users to automate data extraction workflows efficiently. The platform is known for its unmatched accuracy, speed, and capability, providing customers with a flexible and scalable solution that integrates seamlessly with existing systems.

JADBio is an automated machine learning (AutoML) platform designed to accelerate biomarker discovery and drug development processes. It offers a no-code solution that automates the discovery of biomarkers and interprets their role based on research needs. JADBio can parse multi-omics data, including genomics, transcriptome, metagenome, proteome, metabolome, phenotype/clinical data, and images, enabling users to efficiently discover insights for various conditions such as cancer, immune system disorders, chronic diseases, infectious diseases, and mental health. The platform is trusted by partners in precision health and medicine and is continuously evolving to disrupt drug discovery times and costs at all stages.

IXICO is a precision analytics company specializing in intelligent insights in neuroscience. They offer a range of services for drug development analytics, imaging operations, and post-marketing consultancy. With a focus on technology and innovation, IXICO provides expertise in imaging biomarkers, radiological reads, volumetric MRI, PET & SPECT, and advanced MRI. Their TrialTracker platform and Assessa tool utilize innovation and AI for disease modeling and analysis. IXICO supports biopharmaceutical companies in CNS clinical research with cutting-edge neuroimaging techniques and AI technology.

Blobfish AI is an innovative artificial intelligence tool that leverages advanced algorithms to analyze and interpret complex data sets. It offers a user-friendly interface for users to input data and receive valuable insights and predictions. The tool is designed to assist businesses in making informed decisions, optimizing processes, and gaining a competitive edge in their respective industries. With Blobfish AI, users can harness the power of AI technology without the need for extensive technical knowledge, making it accessible to a wide range of users.

FiftyOne is an open-source tool designed for building high-quality datasets and computer vision models. It supercharges machine learning workflows by enabling users to visualize datasets, interpret models faster, and improve efficiency. With FiftyOne, users can explore scenarios, identify failure modes, visualize complex labels, evaluate models, find annotation mistakes, and much more. The tool aims to streamline the process of improving machine learning models by providing a comprehensive set of features for data analysis and model interpretation.

paperless-gpt is a tool designed to generate accurate and meaningful document titles and tags for paperless-ngx using Large Language Models (LLMs). It supports multiple LLM providers, including OpenAI and Ollama. With paperless-gpt, you can streamline your document management by automatically suggesting appropriate titles and tags based on the content of your scanned documents. The tool offers features like multiple LLM support, customizable prompts, easy integration with paperless-ngx, user-friendly interface for reviewing and applying suggestions, dockerized deployment, automatic document processing, and an experimental OCR feature.

Algernon is a web server with built-in support for QUIC, HTTP/2, Lua, Teal, Markdown, Pongo2, HyperApp, Amber, Sass(SCSS), GCSS, JSX, Ollama (LLMs), BoltDB, Redis, PostgreSQL, MariaDB/MySQL, MSSQL, rate limiting, graceful shutdown, plugins, users, and permissions. It is a small self-contained executable that supports various technologies and features for web development.

ProLLM is a framework that leverages Large Language Models to interpret and analyze protein sequences and interactions through natural language processing. It introduces the Protein Chain of Thought (ProCoT) method to transform complex protein interaction data into intuitive prompts, enhancing predictive accuracy by incorporating protein-specific embeddings and fine-tuning on domain-specific datasets.

The repository 'Awesome-LLM4Cybersecurity' provides a comprehensive overview of the applications of Large Language Models (LLMs) in cybersecurity. It includes a systematic literature review covering topics such as constructing cybersecurity-oriented domain LLMs, potential applications of LLMs in cybersecurity, and research directions in the field. The repository analyzes various benchmarks, datasets, and applications of LLMs in cybersecurity tasks like threat intelligence, fuzzing, vulnerabilities detection, insecure code generation, program repair, anomaly detection, and LLM-assisted attacks.

This repository contains frontier research on explainable AI (XAI), a hot topic in the field of artificial intelligence. It includes trends, use cases, survey papers, books, open courses, papers, and Python libraries related to XAI. The repository aims to organize and categorize publications on XAI, provide evaluation methods, and list various Python libraries for explainable AI.

PSAI is a PowerShell module that empowers scripts with the intelligence of OpenAI, bridging the gap between PowerShell and AI. It enables seamless integration for tasks like file searches and data analysis, revolutionizing automation possibilities with just a few lines of code. The module supports the latest OpenAI API changes, offering features like improved file search, vector store objects, token usage control, message limits, tool choice parameter, custom conversation histories, and model configuration parameters.

InterpretML is an open-source package that incorporates state-of-the-art machine learning interpretability techniques under one roof. With this package, you can train interpretable glassbox models and explain blackbox systems. InterpretML helps you understand your model's global behavior, or understand the reasons behind individual predictions. Interpretability is essential for: - Model debugging - Why did my model make this mistake? - Feature Engineering - How can I improve my model? - Detecting fairness issues - Does my model discriminate? - Human-AI cooperation - How can I understand and trust the model's decisions? - Regulatory compliance - Does my model satisfy legal requirements? - High-risk applications - Healthcare, finance, judicial, ...

LLMonFHIR is an iOS application that utilizes large language models (LLMs) to interpret and provide context around patient data in the Fast Healthcare Interoperability Resources (FHIR) format. It connects to the OpenAI GPT API to analyze FHIR resources, supports multiple languages, and allows users to interact with their health data stored in the Apple Health app. The app aims to simplify complex health records, provide insights, and facilitate deeper understanding through a conversational interface. However, it is an experimental app for informational purposes only and should not be used as a substitute for professional medical advice. Users are advised to verify information provided by AI models and consult healthcare professionals for personalized advice.

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.

ROSGPT_Vision is a new robotic framework designed to command robots using only two prompts: a Visual Prompt for visual semantic features and an LLM Prompt to regulate robotic reactions. It is based on the Prompting Robotic Modalities (PRM) design pattern and is used to develop CarMate, a robotic application for monitoring driver distractions and providing real-time vocal notifications. The framework leverages state-of-the-art language models to facilitate advanced reasoning about image data and offers a unified platform for robots to perceive, interpret, and interact with visual data through natural language. LangChain is used for easy customization of prompts, and the implementation includes the CarMate application for driver monitoring and assistance.

Markdown Translation BOT is a GitHub action that translates markdown files into multiple languages using various AI models. It supports markdown, markdown-jsx, and json files only. The action can be executed by individuals with write permissions to the repository, preventing API abuse by non-trusted parties. Users can set up the action by providing their API key and configuring the workflow settings. The tool allows users to create comments with specific commands to trigger translations and automatically generate pull requests or add translated files to existing pull requests. It supports multiple file translations and can interpret any language supported by GPT-4 or GPT-3.5.

A high-performance TensorFlow Lite library for React Native that utilizes JSI for power, zero-copy ArrayBuffers for efficiency, and low-level C/C++ TensorFlow Lite core API for direct memory access. It supports swapping out TensorFlow Models at runtime and GPU-accelerated delegates like CoreML/Metal/OpenGL. Easy VisionCamera integration allows for seamless usage. Users can load TensorFlow Lite models, interpret input and output data, and utilize GPU Delegates for faster computation. The library is suitable for real-time object detection, image classification, and other machine learning tasks in React Native applications.

This repository provides advanced AI explainability for PyTorch, offering state-of-the-art methods for Explainable AI in computer vision. It includes a comprehensive collection of Pixel Attribution methods for various tasks like Classification, Object Detection, Semantic Segmentation, and more. The package supports high performance with full batch image support and includes metrics for evaluating and tuning explanations. Users can visualize and interpret model predictions, making it suitable for both production and model development scenarios.

Awesome-LLM-Interpretability is a curated list of materials related to LLM (Large Language Models) interpretability, covering tutorials, code libraries, surveys, videos, papers, and blogs. It includes resources on transformer mechanistic interpretability, visualization, interventions, probing, fine-tuning, feature representation, learning dynamics, knowledge editing, hallucination detection, and redundancy analysis. The repository aims to provide a comprehensive overview of tools, techniques, and methods for understanding and interpreting the inner workings of large language models.

The Ollama R library provides an easy way to integrate R with Ollama for running language models locally on your machine. It supports working with standard data structures for different LLMs, offers various output formats, and enables integration with other libraries/tools. The library uses the Ollama REST API and requires the Ollama app to be installed, with GPU support for accelerating LLM inference. It is inspired by Ollama Python and JavaScript libraries, making it familiar for users of those languages. The installation process involves downloading the Ollama app, installing the 'ollamar' package, and starting the local server. Example usage includes testing connection, downloading models, generating responses, and listing available models.

The Octopus-v4 project aims to build the world's largest graph of language models, integrating specialized models and training Octopus models to connect nodes efficiently. The project focuses on identifying, training, and connecting specialized models. The repository includes scripts for running the Octopus v4 model, methods for managing the graph, training code for specialized models, and inference code. Environment setup instructions are provided for Linux with NVIDIA GPU. The Octopus v4 model helps users find suitable models for tasks and reformats queries for effective processing. The project leverages Language Large Models for various domains and provides benchmark results. Users are encouraged to train and add specialized models following recommended procedures.

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.

Help Beginners Get Started With AI

I assist with statistical analysis for molecular biology

医学统计领域的专家，提供详细分析性回应。

Evolves with user interactions in data science.

X線CTと画像Viewer開発に特化した技術的アドバイザー

Es un modelo IA especializado en compras públicas, ofreciendo interpretaciones legales y asesoramiento en licitaciones. Actualizado y preciso, es ideal para funcionarios y empresas.

Expert in epidemiology, modeling disease spread and analyzing public health data.

Physical Geology expert

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.

Automates DCF Analysis with internet-sourced data and summary table.

I am a constitutional lawyer here to interpret legal texts.

I help interpret medical reports and clarify symptoms.

I interpret coffee cup images for fun, creative fortunes.

Upload an image of a statistical analysis and we'll interpret the results: linear regression, logistic regression, ANOVA, cluster analysis, MDS, factor analysis, and many more

Expert in ads incrementality and campaign will help you interpret data, forecasting and share you testing frameworks using advanced Python libraries

I read and interpret Lithuanian construction norms.

Interpret AI and technology news trough blend of fantasy and modern tech mixed with wit, join a game to sit on AI-ron Throne, checkout Medium publication V.03 2023-11-26

I create and interpret dream visuals.

Interpret your dreams

I interpret text and respond with witty, humorous emojis.