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Cuspera is an AI-powered software recommendation platform that helps businesses find the right software for their marketing and sales needs. It provides personalized software recommendations based on a business's specific needs and has a knowledgebase of over 17,000 software products. Cuspera's AI is trained on insights from peers and experts to guide businesses to the right software and recommends best practices from peer and expert experiences.

Fahim AI is a premier destination for in-depth reviews and analyses of the latest advancements in artificial intelligence and software technology. The website empowers tech enthusiasts, professionals, and casual readers with reliable information to stay ahead in the rapidly evolving digital world. It offers comprehensive evaluations of cutting-edge AI systems, detailed reviews of software solutions, insights on the latest tech gadgets integrated with AI capabilities, side-by-side product comparisons, easy-to-follow tutorials and guides, expert opinions from industry leaders, and a community platform for sharing experiences and connecting with like-minded individuals.

Ai Tool Hunt is a comprehensive directory of free AI tools, software, and websites. It provides users with a curated list of the best AI resources available online, empowering them to enhance their digital experiences and leverage the latest advancements in artificial intelligence. With Ai Tool Hunt, users can discover powerful AI tools for various tasks, including content creation, data analysis, image editing, language learning, and more. The platform offers detailed descriptions, user ratings, and easy access to these tools, making it a valuable resource for individuals and businesses seeking to integrate AI into their workflows.

LLM Price Check is an AI tool designed to compare and calculate the latest prices for Large Language Models (LLM) APIs from leading providers such as OpenAI, Anthropic, Google, and more. Users can use the streamlined tool to optimize their AI budget efficiently by comparing pricing, sorting by various parameters, and searching for specific models. The tool provides a comprehensive overview of pricing information to help users make informed decisions when selecting an LLM API provider.

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.

NavTo.AI is the ultimate AI tools directory that curates exceptional AI solutions from around the globe. It showcases cutting-edge innovations in artificial intelligence, covering a wide range of categories such as AI chatbots, fitness trackers, content generators, video editors, and more. Whether you're a developer, entrepreneur, or AI enthusiast, NavTo.AI helps you discover tools that enhance productivity and spark innovation. The platform offers daily updates on breakthrough AI technologies, making it a valuable resource for staying ahead in the AI landscape.

OSS Insight is an AI tool that provides deep insight into developers and repositories on GitHub, offering information about stars, pull requests, issues, pushes, comments, and reviews. It utilizes artificial intelligence to analyze data and provide valuable insights to users. The tool ranks repositories, tracks trending repositories, and offers real-time information about GitHub events. Additionally, it offers features like data exploration, collections, live blog, API integration, and widgets.

Zoftware is the Middle East's #1 Software Discovery Platform that offers programmed intelligence software buying expertise. It connects users with the best tech solutions for their business needs in the region. With over 3 million reviews and 6000+ software options to compare, Zoftware provides AI assistance to help users make informed decisions. The platform empowers users to discover, compare, and decide on software solutions that align with their requirements, making the process effortless, economical, and efficient.

The website appears to be experiencing technical difficulties as indicated by the error message displayed. It seems that the request could not be satisfied and there was a failure to contact the origin server. The error message includes a timestamp and a request ID. This suggests that the website may be encountering server-side issues or connectivity problems.

Neptune is an MLOps stack component for experiment tracking. It allows users to track, compare, and share their models in one place. Neptune is used by scaling ML teams to skip days of debugging disorganized models, avoid long and messy model handovers, and start logging for free.

Comet ML is a machine learning platform that integrates with your existing infrastructure and tools so you can manage, visualize, and optimize models—from training runs to production monitoring.

Comet ML is a machine learning platform that integrates with your existing infrastructure and tools so you can manage, visualize, and optimize models—from training runs to production monitoring.

Comet ML is an extensible, fully customizable machine learning platform that aims to move ML forward by supporting productivity, reproducibility, and collaboration. It integrates with existing infrastructure and tools to manage, visualize, and optimize models from training runs to production monitoring. Users can track and compare training runs, create a model registry, and monitor models in production all in one platform. Comet's platform can be run on any infrastructure, enabling users to reshape their ML workflow and bring their existing software and data stack.

AI Marketplace is a platform that allows users to discover and access a variety of AI agents for different purposes. Users can explore a wide range of AI solutions and find the best agents to meet their specific needs. The platform provides a convenient way to connect with AI technology and leverage its capabilities for various applications.

HireMatch is an AI-powered resume screening tool designed for recruiters. It automates the process of screening and analyzing resumes to identify top candidates for job positions. By leveraging Neural Language Processing algorithms, HireMatch saves time by extracting and interpreting relevant information from resumes. The tool caters to various industries and positions, offering a data-rich dashboard for easy comparison of skills and experience. Whether you are an HR manager in a small team or a freelance recruiter handling numerous resumes, HireMatch streamlines the candidate selection process and enhances recruitment efficiency.

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Weights & Biases is an AI tool that offers documentation, guides, tutorials, and support for using AI models in applications. The platform provides two main products: W&B Weave for integrating AI models into code and W&B Models for building custom AI models. Users can access features such as tracing, output evaluation, cost estimates, hyperparameter sweeps, model registry, and more. Weights & Biases aims to simplify the process of working with AI models and improving model reproducibility.

Oncely.ai is the #1 Lifetime Deal Platform for AI Business Software, offering exclusive one-time payment deals for top-tier software without recurring fees. The platform features a curated selection of AI tools and applications, rigorously tested for quality and reliability. Users can access lifetime deals on a variety of AI solutions, from chatbots to automation databases, at minimal cost with maximum benefits. With a focus on providing reliable support and a money-back guarantee, Oncely.ai aims to help businesses stay ahead with the hottest lifetime deals.

Buzz4AI is a platform that provides a curated list of AI tools, software, and research to help businesses enhance strategies, optimize workflow, and stay ahead in the rapidly evolving field of artificial intelligence. The platform offers a wide range of AI solutions for various business needs, including cold email software, DDoS protection software, learning management systems, payroll software, biometric attendance software, and more. Buzz4AI aims to empower users with up-to-date and secure information, interactive tool comparison, community-driven reviews, and the latest AI tools to revolutionize industries with cutting-edge capabilities and advancements.

OpenRouter is an AI tool that provides a unified interface for Large Language Models (LLMs). Users can find the best models and prices for various prompts related to roleplay, programming, marketing, technology, science, translation, legal, finance, health, trivia, and academia. The platform offers transformer-based models with multilingual capabilities, coding, mathematics, and reasoning. It features SwiGLU activation, attention QKV bias, and group query attention. OpenRouter allows users to interact with trending models, simulate the web, chat with multiple LLMs simultaneously, and engage in AI character chat and roleplay.

DevQualityEval is an evaluation benchmark and framework designed to compare and improve the quality of code generation of Language Model Models (LLMs). It provides developers with a standardized benchmark to enhance real-world usage in software development and offers users metrics and comparisons to assess the usefulness of LLMs for their tasks. The tool evaluates LLMs' performance in solving software development tasks and measures the quality of their results through a point-based system. Users can run specific tasks, such as test generation, across different programming languages to evaluate LLMs' language understanding and code generation capabilities.

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.

Nous is an open-source TypeScript platform for autonomous AI agents and LLM based workflows. It aims to automate processes, support requests, review code, assist with refactorings, and more. The platform supports various integrations, multiple LLMs/services, CLI and web interface, human-in-the-loop interactions, flexible deployment options, observability with OpenTelemetry tracing, and specific agents for code editing, software engineering, and code review. It offers advanced features like reasoning/planning, memory and function call history, hierarchical task decomposition, and control-loop function calling options. Nous is designed to be a flexible platform for the TypeScript community to expand and support different use cases and integrations.

Sophia is an open-source TypeScript platform designed for autonomous AI agents and LLM based workflows. It aims to automate processes, review code, assist with refactorings, and support various integrations. The platform offers features like advanced autonomous agents, reasoning/planning inspired by Google's Self-Discover paper, memory and function call history, adaptive iterative planning, and more. Sophia supports multiple LLMs/services, CLI and web interface, human-in-the-loop interactions, flexible deployment options, observability with OpenTelemetry tracing, and specific agents for code editing, software engineering, and code review. It provides a flexible platform for the TypeScript community to expand and support various use cases and integrations.

FastTrackML is an experiment tracking server focused on speed and scalability, fully compatible with MLFlow. It provides a user-friendly interface to track and visualize your machine learning experiments, making it easy to compare different models and identify the best performing ones. FastTrackML is open source and can be easily installed and run with pip or Docker. It is also compatible with the MLFlow Python package, making it easy to integrate with your existing MLFlow workflows.

Minic is a chess engine developed for learning about chess programming and modern C++. It is compatible with CECP and UCI protocols, making it usable in various software. Minic has evolved from a one-file code to a more classic C++ style, incorporating features like evaluation tuning, perft, tests, and more. It has integrated NNUE frameworks from Stockfish and Seer implementations to enhance its strength. Minic is currently ranked among the top engines with an Elo rating around 3400 at CCRL scale.

SheetCopilot is an assistant agent that manipulates spreadsheets by following user commands. It leverages Large Language Models (LLMs) to interact with spreadsheets like a human expert, enabling non-expert users to complete tasks on complex software such as Google Sheets and Excel via a language interface. The tool observes spreadsheet states, polishes generated solutions based on external action documents and error feedback, and aims to improve success rate and efficiency. SheetCopilot offers a dataset with diverse task categories and operations, supporting operations like entry & manipulation, management, formatting, charts, and pivot tables. Users can interact with SheetCopilot in Excel or Google Sheets, executing tasks like calculating revenue, creating pivot tables, and plotting charts. The tool's evaluation includes performance comparisons with leading LLMs and VBA-based methods on specific datasets, showcasing its capabilities in controlling various aspects of a spreadsheet.

APS Toolkit is a powerful tool for developers, software engineers, and AI engineers to explore Autodesk Platform Services (APS). It allows users to read, download, and write data from APS, as well as export data to various formats like CSV, Excel, JSON, and XML. The toolkit is built on top of Autodesk.Forge and Newtonsoft.Json, offering features such as reading SVF models, querying properties database, exporting data, and more.

This repository provides a collection of tools and techniques for defending against injection attacks in software applications. It includes code samples, best practices, and guidelines for implementing secure coding practices to prevent common injection vulnerabilities such as SQL injection, XSS, and command injection. The tools and resources in this repository aim to help developers build more secure and resilient applications by addressing one of the most common and critical security threats in modern software development.

TypedAI is a TypeScript-first AI platform designed for developers to create and run autonomous AI agents, LLM based workflows, and chatbots. It offers advanced autonomous agents, software developer agents, pull request code review agent, AI chat interface, Slack chatbot, and supports various LLM services. The platform features configurable Human-in-the-loop settings, functional callable tools/integrations, CLI and Web UI interface, and can be run locally or deployed on the cloud with multi-user/SSO support. It leverages the Python AI ecosystem through executing Python scripts/packages and provides flexible run/deploy options like single user mode, Firestore & Cloud Run deployment, and multi-user SSO enterprise deployment. TypedAI also includes UI examples, code examples, and automated LLM function schemas for seamless development and execution of AI workflows.

Language Models is a Python package that provides building blocks to explore large language models with as little as 512MB of RAM. It simplifies the usage of large language models from Python, ensuring all inference is performed locally to keep data private. The package includes features such as text completions, chat capabilities, code completions, external text retrieval, semantic search, and more. It outperforms Hugging Face transformers for CPU inference and offers sensible default models with varying parameters based on memory constraints. The package is suitable for learners and educators exploring the intersection of large language models with modern software development.

DVC, or Data Version Control, is a command-line tool and VS Code extension that helps you develop reproducible machine learning projects. With DVC, you can version your data and models, iterate fast with lightweight pipelines, track experiments in your local Git repo, compare any data, code, parameters, model, or performance plots, and share experiments and automatically reproduce anyone's experiment.

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.

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.

Collective Mind (CM) is a collection of portable, extensible, technology-agnostic and ready-to-use automation recipes with a human-friendly interface (aka CM scripts) to unify and automate all the manual steps required to compose, run, benchmark and optimize complex ML/AI applications on any platform with any software and hardware: see online catalog and source code. CM scripts require Python 3.7+ with minimal dependencies and are continuously extended by the community and MLCommons members to run natively on Ubuntu, MacOS, Windows, RHEL, Debian, Amazon Linux and any other operating system, in a cloud or inside automatically generated containers while keeping backward compatibility - please don't hesitate to report encountered issues here and contact us via public Discord Server to help this collaborative engineering effort! CM scripts were originally developed based on the following requirements from the MLCommons members to help them automatically compose and optimize complex MLPerf benchmarks, applications and systems across diverse and continuously changing models, data sets, software and hardware from Nvidia, Intel, AMD, Google, Qualcomm, Amazon and other vendors: * must work out of the box with the default options and without the need to edit some paths, environment variables and configuration files; * must be non-intrusive, easy to debug and must reuse existing user scripts and automation tools (such as cmake, make, ML workflows, python poetry and containers) rather than substituting them; * must have a very simple and human-friendly command line with a Python API and minimal dependencies; * must require minimal or zero learning curve by using plain Python, native scripts, environment variables and simple JSON/YAML descriptions instead of inventing new workflow languages; * must have the same interface to run all automations natively, in a cloud or inside containers. CM scripts were successfully validated by MLCommons to modularize MLPerf inference benchmarks and help the community automate more than 95% of all performance and power submissions in the v3.1 round across more than 120 system configurations (models, frameworks, hardware) while reducing development and maintenance costs.

ChatSim is a tool designed for editable scene simulation for autonomous driving via LLM-Agent collaboration. It provides functionalities for setting up the environment, installing necessary dependencies like McNeRF and Inpainting tools, and preparing data for simulation. Users can train models, simulate scenes, and track trajectories for smoother and more realistic results. The tool integrates with Blender software and offers options for training McNeRF models and McLight's skydome estimation network. It also includes a trajectory tracking module for improved trajectory tracking. ChatSim aims to facilitate the simulation of autonomous driving scenarios with collaborative LLM-Agents.

Recognize is a smart media tagging tool for Nextcloud that automatically categorizes photos and music by recognizing faces, animals, landscapes, food, vehicles, buildings, landmarks, monuments, music genres, and human actions in videos. It uses pre-trained models for object detection, landmark recognition, face comparison, music genre classification, and video classification. The tool ensures privacy by processing images locally without sending data to cloud providers. However, it cannot process end-to-end encrypted files. Recognize is rated positively for ethical AI practices in terms of open-source software, freely available models, and training data transparency, except for music genre recognition due to limited access to training data.

The NVIDIA AI Blueprint for Vulnerability Analysis for Container Security showcases accelerated analysis on common vulnerabilities and exposures (CVE) at an enterprise scale, reducing mitigation time from days to seconds. It enables security analysts to determine software package vulnerabilities using large language models (LLMs) and retrieval-augmented generation (RAG). The blueprint is designed for security analysts, IT engineers, and AI practitioners in cybersecurity. It requires NVAIE developer license and API keys for vulnerability databases, search engines, and LLM model services. Hardware requirements include L40 GPU for pipeline operation and optional LLM NIM and Embedding NIM. The workflow involves LLM pipeline for CVE impact analysis, utilizing LLM planner, agent, and summarization nodes. The blueprint uses NVIDIA NIM microservices and Morpheus Cybersecurity AI SDK for vulnerability analysis.

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.

AirspeedVelocity.jl is a tool designed to simplify benchmarking of Julia packages over their lifetime. It provides a CLI to generate benchmarks, compare commits/tags/branches, plot benchmarks, and run benchmark comparisons for every submitted PR as a GitHub action. The tool freezes the benchmark script at a specific revision to prevent old history from affecting benchmarks. Users can configure options using CLI flags and visualize benchmark results. AirspeedVelocity.jl can be used to benchmark any Julia package and offers features like generating tables and plots of benchmark results. It also supports custom benchmarks and can be integrated into GitHub actions for automated benchmarking of PRs.

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Find the perfect online course in tech, business, marketing, programming, and more. Compare options from top platforms like Udemy, Coursera, and EDX.

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