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Messari is an AI-powered platform that provides comprehensive crypto research, reports, AI news, live prices, token unlocks, and fundraising data. It offers a wide range of tools for users to explore and analyze the cryptocurrency market. With features like AI summaries, personalized watchlists, comparative charts, and AI recaps, Messari aims to organize and contextualize all crypto information at a global scale.

Keplar is an AI-powered platform that provides unlimited customer access by delivering interactive models of target customers using influencer audiences and 1st-party data. It helps marketing teams iterate on creative assets, discover new markets, compare audiences, and save resources for bigger impact. Keplar offers a new way to unlock creative and audience insights faster, enabling teams to maintain velocity at scale.

InsureSmart is an AI-powered platform that empowers users to take control of their insurance needs. By leveraging artificial intelligence technology, InsureSmart offers personalized insurance solutions tailored to individual requirements. The platform provides a seamless and user-friendly experience for users to manage and optimize their insurance policies efficiently. With InsureSmart, users can access smart recommendations, compare insurance plans, and make informed decisions to secure their financial well-being.

Lex Machina is a Legal Analytics platform that provides comprehensive insights into litigation track records of parties across the United States. It offers accurate and transparent analytic data, exclusive outcome analytics, and valuable insights to help law firms and companies craft successful strategies, assess cases, and set litigation strategies. The platform uses a unique combination of machine learning and in-house legal experts to compile, clean, and enhance data, providing unmatched insights on courts, judges, lawyers, law firms, and parties.

GaitAnalyzer.health is a web application designed to analyze and assess human gait patterns for healthcare professionals and researchers. The platform utilizes advanced algorithms to process gait data captured through various sensors and devices, providing valuable insights into gait abnormalities and biomechanical characteristics. Users can upload gait data, visualize results, and generate detailed reports to aid in diagnosis and treatment planning. GaitAnalyzer.health aims to improve the understanding of human movement patterns and enhance the quality of care in the field of biomechanics and rehabilitation.

AI Copilot for bank ALCOs is an AI application designed to empower Asset-Liability Committees (ALCOs) in banks to test funding and liquidity strategies in a risk-free environment, ensuring optimal balance sheet decisions before real-world implementation. The application provides proactive intelligence for day-to-day decisions, allowing users to test multiple strategies, compare funding options, and make forward-looking decisions. It offers features such as stakeholder feedback, optimal funding mix, forward-looking decisions, comparison of funding strategies, domain-specific models, maximizing returns, staying compliant, and built-in security measures. MaverickFi, the AI Copilot, is deployed on Microsoft Azure and offers deployment options based on user preferences.

Lilac is an AI tool designed to enhance data quality and exploration for AI applications. It offers features such as data search, quantification, editing, clustering, semantic search, field comparison, and fuzzy-concept search. Lilac enables users to accelerate dataset computations and transformations, making it a valuable asset for data scientists and AI practitioners. The tool is trusted by Alignment Lab and is recommended for working with LLM datasets.

This AI-powered age detection tool analyzes your photo to estimate how old you look. It utilizes advanced artificial intelligence technology to assess facial characteristics such as wrinkles, skin texture, and facial features, comparing them against a vast dataset to provide an approximation of your age. The tool is free to use and ensures privacy by automatically deleting uploaded photos after analysis.

Spellbook is a comprehensive AI tool designed for commercial lawyers to streamline contract review and drafting processes. It offers features such as redlining contracts, drafting from scratch or libraries, providing quick answers to complex questions, comparing contracts to industry standards, and enabling multi-document workflows. Spellbook leverages AI technology to enhance legal work efficiency and accuracy, making it a valuable asset for legal professionals worldwide.

Legalysis is a powerful tool for analyzing and summarizing legal documents. It is designed to save time and reduce complexity in legal processes. The tool uses advanced AI technology to examine contracts and other legal documents in depth, detecting potential risks and issues with impressive accuracy. It also converts dense, lengthy legal documents into brief, one-page summaries, making them easier to understand. Legalysis is a valuable tool for law firms, corporate legal departments, and individuals dealing with legal documents.

Relyance AI is a platform that offers 360 Data Governance and Trust solutions. It helps businesses safeguard against fines and reputation damage while enhancing customer trust to drive business growth. The platform provides visibility into enterprise-wide data processing, ensuring compliance with regulatory and customer obligations. Relyance AI uses AI-powered risk insights to proactively identify and address risks, offering a unified trust and governance infrastructure. It offers features such as data inventory and mapping, automated assessments, security posture management, and vendor risk management. The platform is designed to streamline data governance processes, reduce costs, and improve operational efficiency.

TitleCorp.AI is a dynamic company specializing in the research and development of title insurance and real estate services that leverage advanced technologies like artificial intelligence and blockchain to enhance the transactional experience for clients. By simplifying complex title workflows, TitleCorp aims to reduce the time it takes to complete real estate transactions while minimizing risks associated with title claims. The company is committed to innovation and aims to provide more efficient, accurate, and secure title insurance services compared to traditional methods.

Tube Transcripts is an AI-powered tool designed to provide fast, accurate, and cost-effective transcription services for YouTube videos. It offers human-quality transcripts at a fraction of the cost and time compared to traditional methods. By leveraging AI technology, users can easily transcribe their videos with high accuracy and efficiency. The tool also helps improve SEO, accessibility, and viewer engagement by generating subtitles that are easy to read and SEO-friendly. Tube Transcripts is a user-friendly solution that caters to YouTubers of all sizes, making it a valuable asset for content creators looking to enhance their video content.

ChartChatAI is a free AI-based technical analysis and prediction tool designed to help traders analyze charts, discover trades, predict prices, and spot risks on autopilot. It offers features such as one-click chart analysis, forecasting, price prediction, technical and fundamental analysis, trend forecasting, ticker comparison, risk assessment, scenario simulation, and strategy builder. ChartChatAI provides instant, precise, and actionable insights with automated chart analysis, auto prompt generation, trade idea generation, a trained chatbot, and hotkey commands for stock, crypto, and forex trading. It is a smarter, faster, and easier-to-use trading assistant compared to ChatGPT, offering unlimited chart analysis without any signup or credit card requirements.

KAYAK is a comprehensive travel search engine that allows users to search for flights, hotels, and rental cars from hundreds of travel sites. The platform offers a wide range of features to help users plan their trips efficiently and find the best travel deals. With KAYAK, users can explore flight options, track flights, access travel tips, and plan their travel itineraries. The website compares prices from various sources to provide users with a convenient way to book their travel arrangements.

Contentable.ai is a platform for comparing multiple AI models, rapidly moving from prototyping to production, and management of your custom AI solutions across multiple vendors. It allows users to test multiple AI models in seconds, compare models side-by-side across top AI providers, collaborate on AI models with their team seamlessly, design complex AI workflows without coding, and pay as they go.

Sofon is a knowledge aggregation and curation platform that provides users with personalized insights on topics they care about. It aggregates and curates knowledge shared across 1,000+ articles, podcasts, and books, delivering a personalized stream of ideas to users. Sofon uses AI to compare ideas across hundreds of people on any question, saving users thousands of hours of curation. Users can indicate the people they want to learn from, and Sofon will curate insights across all their knowledge. Users can receive an idealetter, which is a unique combination of ideas across all the people they've selected around a common theme, delivered at an interval of their choice.

LLM Clash is a web-based application that allows users to compare the outputs of different large language models (LLMs) on a given task. Users can input a prompt and select which LLMs they want to compare. The application will then display the outputs of the LLMs side-by-side, allowing users to compare their strengths and weaknesses.

Prompt Octopus is a free tool that allows you to compare multiple prompts side-by-side. You can add as many prompts as you need and view the responses in real-time. This can be helpful for fine-tuning your prompts and getting the best possible results from your AI model.

Gemini is a multi-modal AI model, developed by Google. It is designed to understand and generate human language, and can be used for a variety of tasks, including question answering, translation, and dialogue generation. ChatGPT is a large language model, developed by OpenAI. It is also designed to understand and generate human language, and can be used for a variety of tasks, including question answering, translation, and dialogue generation.

WeatherGFT is a physics-AI hybrid model designed to generalize weather forecasts to finer-grained temporal scales beyond the training dataset. It incorporates physical partial differential equations (PDEs) into neural networks to simulate fine-grained physical evolution and correct biases. The model achieves state-of-the-art performance in forecasting tasks at different time scales, from nowcasting to medium-range forecasts, by utilizing a lead time-aware training framework and a carefully designed PDE kernel. WeatherGFT bridges the gap between nowcast and medium-range forecast by extending forecasting abilities to predict accurately at a 30-minute time scale.

TokenPacker is a novel visual projector that compresses visual tokens by 75%∼89% with high efficiency. It adopts a 'coarse-to-fine' scheme to generate condensed visual tokens, achieving comparable or better performance across diverse benchmarks. The tool includes TokenPacker for general use and TokenPacker-HD for high-resolution image understanding. It provides training scripts, checkpoints, and supports various compression ratios and patch numbers.

MiniCPM-V is a series of end-side multimodal LLMs designed for vision-language understanding. The models take image and text inputs to provide high-quality text outputs. The series includes models like MiniCPM-Llama3-V 2.5 with 8B parameters surpassing proprietary models, and MiniCPM-V 2.0, a lighter model with 2B parameters. The models support over 30 languages, efficient deployment on end-side devices, and have strong OCR capabilities. They achieve state-of-the-art performance on various benchmarks and prevent hallucinations in text generation. The models can process high-resolution images efficiently and support multilingual capabilities.

OpenModelDB is a community-driven database of AI upscaling models, providing a centralized platform for users to access and compare various models. The repository contains a collection of models and model metadata, facilitating easy exploration and evaluation of different AI upscaling solutions. With a focus on enhancing the accessibility and usability of AI models, OpenModelDB aims to streamline the process of finding and selecting the most suitable models for specific tasks or projects.

The Korean SAT LLM Leaderboard is a benchmarking project that allows users to test their fine-tuned Korean language models on a 10-year dataset of the Korean College Scholastic Ability Test (CSAT). The project provides a platform to compare human academic ability with the performance of large language models (LLMs) on various question types to assess reading comprehension, critical thinking, and sentence interpretation skills. It aims to share benchmark data, utilize a reliable evaluation dataset curated by the Korea Institute for Curriculum and Evaluation, provide annual updates to prevent data leakage, and promote open-source LLM advancement for achieving top-tier performance on the Korean CSAT.

Neptune is a scalable experiment tracker for teams training foundation models. Log millions of runs, effortlessly monitor and visualize model training, and deploy on your infrastructure. Track 100% of metadata to accelerate AI breakthroughs. Log and display any framework and metadata type from any ML pipeline. Organize experiments with nested structures and custom dashboards. Compare results, visualize training, and optimize models quicker. Version models, review stages, and access production-ready models. Share results, manage users, and projects. Integrate with 25+ frameworks. Trusted by great companies to improve workflow.

Weights & Biases (W&B) is a platform that helps users build better machine learning models faster by tracking and visualizing all components of the machine learning pipeline, from datasets to production models. It offers tools for tracking, debugging, evaluating, and monitoring machine learning applications. W&B provides integrations with popular frameworks like PyTorch, TensorFlow/Keras, Hugging Face Transformers, PyTorch Lightning, XGBoost, and Sci-Kit Learn. Users can easily log metrics, visualize performance, and compare experiments using W&B. The platform also supports hosting options in the cloud or on private infrastructure, making it versatile for various deployment needs.

Raga LLM Hub is a comprehensive evaluation toolkit for Language and Learning Models (LLMs) with over 100 meticulously designed metrics. It allows developers and organizations to evaluate and compare LLMs effectively, establishing guardrails for LLMs and Retrieval Augmented Generation (RAG) applications. The platform assesses aspects like Relevance & Understanding, Content Quality, Hallucination, Safety & Bias, Context Relevance, Guardrails, and Vulnerability scanning, along with Metric-Based Tests for quantitative analysis. It helps teams identify and fix issues throughout the LLM lifecycle, revolutionizing reliability and trustworthiness.

ChainForge is a visual programming environment for battle-testing prompts to LLMs. It is geared towards early-stage, quick-and-dirty exploration of prompts, chat responses, and response quality that goes beyond ad-hoc chatting with individual LLMs. With ChainForge, you can: * Query multiple LLMs at once to test prompt ideas and variations quickly and effectively. * Compare response quality across prompt permutations, across models, and across model settings to choose the best prompt and model for your use case. * Setup evaluation metrics (scoring function) and immediately visualize results across prompts, prompt parameters, models, and model settings. * Hold multiple conversations at once across template parameters and chat models. Template not just prompts, but follow-up chat messages, and inspect and evaluate outputs at each turn of a chat conversation. ChainForge comes with a number of example evaluation flows to give you a sense of what's possible, including 188 example flows generated from benchmarks in OpenAI evals. This is an open beta of Chainforge. We support model providers OpenAI, HuggingFace, Anthropic, Google PaLM2, Azure OpenAI endpoints, and Dalai-hosted models Alpaca and Llama. You can change the exact model and individual model settings. Visualization nodes support numeric and boolean evaluation metrics. ChainForge is built on ReactFlow and Flask.

Litlyx is a single-line code analytics solution that integrates with every JavaScript/TypeScript framework. It allows you to track 10+ KPIs and custom events for your website or web app. The tool comes with an AI Data Analyst Assistant that can analyze your data, compare data, query metadata, visualize charts, and more. Litlyx is open-source, allowing users to self-host it and create their own version of the dashboard. The tool is user-friendly and supports various JavaScript/TypeScript frameworks, making it versatile for different projects.

A curated repository of code recipes, demos, and resources for basic and advanced Redis use cases in the AI ecosystem. It includes demos for ArxivChatGuru, Redis VSS, Vertex AI & Redis, Agentic RAG, ArXiv Search, and Product Search. Recipes cover topics like Getting started with RAG, Semantic Cache, Advanced RAG, and Recommendation systems. The repository also provides integrations/tools like RedisVL, AWS Bedrock, LangChain Python, LangChain JS, LlamaIndex, Semantic Kernel, RelevanceAI, and DocArray. Additional content includes blog posts, talks, reviews, and documentation related to Vector Similarity Search, AI-Powered Document Search, Vector Databases, Real-Time Product Recommendations, and more. Benchmarks compare Redis against other Vector Databases and ANN benchmarks. Documentation includes QuickStart guides, official literature for Vector Similarity Search, Redis-py client library docs, Redis Stack documentation, and Redis client list.

LLM AutoEval is a tool that simplifies the process of evaluating Large Language Models (LLMs) using a convenient Colab notebook. It automates the setup and execution of evaluations using RunPod, allowing users to customize evaluation parameters and generate summaries that can be uploaded to GitHub Gist for easy sharing and reference. LLM AutoEval supports various benchmark suites, including Nous, Lighteval, and Open LLM, enabling users to compare their results with existing models and leaderboards.

Log10 is a one-line Python integration to manage your LLM data. It helps you log both closed and open-source LLM calls, compare and identify the best models and prompts, store feedback for fine-tuning, collect performance metrics such as latency and usage, and perform analytics and monitor compliance for LLM powered applications. Log10 offers various integration methods, including a python LLM library wrapper, the Log10 LLM abstraction, and callbacks, to facilitate its use in both existing production environments and new projects. Pick the one that works best for you. Log10 also provides a copilot that can help you with suggestions on how to optimize your prompt, and a feedback feature that allows you to add feedback to your completions. Additionally, Log10 provides prompt provenance, session tracking and call stack functionality to help debug prompt chains. With Log10, you can use your data and feedback from users to fine-tune custom models with RLHF, and build and deploy more reliable, accurate and efficient self-hosted models. Log10 also supports collaboration, allowing you to create flexible groups to share and collaborate over all of the above features.

Dwata is a desktop application that allows users to chat with any AI model and gain insights from their data. Chats are organized into threads, similar to Discord, with each thread connecting to a different AI model. Dwata can connect to databases, APIs (such as Stripe), or CSV files and send structured data as prompts when needed. The AI's response will often include SQL or Python code, which can be used to extract the desired insights. Dwata can validate AI-generated SQL to ensure that the tables and columns referenced are correct and can execute queries against the database from within the application. Python code (typically using Pandas) can also be executed from within Dwata, although this feature is still in development. Dwata supports a range of AI models, including OpenAI's GPT-4, GPT-4 Turbo, and GPT-3.5 Turbo; Groq's LLaMA2-70b and Mixtral-8x7b; Phind's Phind-34B and Phind-70B; Anthropic's Claude; and Ollama's Llama 2, Mistral, and Phi-2 Gemma. Dwata can compare chats from different models, allowing users to see the responses of multiple models to the same prompts. Dwata can connect to various data sources, including databases (PostgreSQL, MySQL, MongoDB), SaaS products (Stripe, Shopify), CSV files/folders, and email (IMAP). The desktop application does not collect any private or business data without the user's explicit consent.

RouteLLM is a framework for serving and evaluating LLM routers. It allows users to launch an OpenAI-compatible API that routes requests to the best model based on cost thresholds. Trained routers are provided to reduce costs while maintaining performance. Users can easily extend the framework, compare router performance, and calibrate cost thresholds. RouteLLM supports multiple routing strategies and benchmarks, offering a lightweight server and evaluation framework. It enables users to evaluate routers on benchmarks, calibrate thresholds, and modify model pairs. Contributions for adding new routers and benchmarks are welcome.

PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

Empirical is a tool that allows you to test different LLMs, prompts, and other model configurations across all the scenarios that matter for your application. With Empirical, you can run your test datasets locally against off-the-shelf models, test your own custom models and RAG applications, view, compare, and analyze outputs on a web UI, score your outputs with scoring functions, and run tests on CI/CD.

H2O LLM Studio is a framework and no-code GUI designed for fine-tuning state-of-the-art large language models (LLMs). With H2O LLM Studio, you can easily and effectively fine-tune LLMs without the need for any coding experience. The GUI is specially designed for large language models, and you can finetune any LLM using a large variety of hyperparameters. You can also use recent finetuning techniques such as Low-Rank Adaptation (LoRA) and 8-bit model training with a low memory footprint. Additionally, you can use Reinforcement Learning (RL) to finetune your model (experimental), use advanced evaluation metrics to judge generated answers by the model, track and compare your model performance visually, and easily export your model to the Hugging Face Hub and share it with the community.

The Generative AI Application Builder on AWS (GAAB) is a solution that provides a web-based management dashboard for deploying customizable Generative AI (Gen AI) use cases. Users can experiment with and compare different combinations of Large Language Model (LLM) use cases, configure and optimize their use cases, and integrate them into their applications for production. The solution is targeted at novice to experienced users who want to experiment and productionize different Gen AI use cases. It uses LangChain open-source software to configure connections to Large Language Models (LLMs) for various use cases, with the ability to deploy chat use cases that allow querying over users' enterprise data in a chatbot-style User Interface (UI) and support custom end-user implementations through an API.

The RAG Experiment Accelerator is a versatile tool that helps you conduct experiments and evaluations using Azure AI Search and RAG pattern. It offers a rich set of features, including experiment setup, integration with Azure AI Search, Azure Machine Learning, MLFlow, and Azure OpenAI, multiple document chunking strategies, query generation, multiple search types, sub-querying, re-ranking, metrics and evaluation, report generation, and multi-lingual support. The tool is designed to make it easier and faster to run experiments and evaluations of search queries and quality of response from OpenAI, and is useful for researchers, data scientists, and developers who want to test the performance of different search and OpenAI related hyperparameters, compare the effectiveness of various search strategies, fine-tune and optimize parameters, find the best combination of hyperparameters, and generate detailed reports and visualizations from experiment results.

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Compare similar GPTs outputs quality on the same question, identify the most valuable one.

Compare TV Devices Uncover the pros and cons of different latest TV models.

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