Best AI tools for< Defeat Built-in Ai >

Bugasura is an AI-enabled bug management tool designed for fast-moving, modern technology teams. It offers features like issue tracking, bug reporting, performance monitoring, integrations, and API documentation. With intelligent features powered by AI, Bugasura streamlines the bug tracking and resolution process, empowering teams to handle complex challenges efficiently. The tool provides custom workflows, automatic issue assignment, easy exports, and imports, making bug management seamless and productive. Bugasura also includes bug reporters for various use cases, such as website feedback and frontend testing, with features like annotatable screenshots and in-app bug reporting widgets. Additionally, Bugasura offers performance monitoring, advanced filters, and seamless integrations with popular project management tools. The tool is cloud-based with pocket-friendly pricing options for small teams, prioritizing privacy and security with end-to-end encryption and secure authentication protocols.

Google DeepMind is a British artificial intelligence research laboratory owned by Google. The company was founded in 2010 by Demis Hassabis, Shane Legg, and Mustafa Suleyman. DeepMind's mission is to develop safe and beneficial artificial intelligence. The company's research focuses on a variety of topics, including machine learning, reinforcement learning, and computer vision. DeepMind has made significant contributions to the field of artificial intelligence, including the development of AlphaGo, the first computer program to defeat a professional human Go player.

Averroes is the #1 AI Automated Visual Inspection Software designed for various industries such as Oil and Gas, Food and Beverage, Pharma, Semiconductor, and Electronics. It offers an end-to-end AI visual inspection platform that allows users to effortlessly train and deploy custom AI models for defect classification, object detection, and segmentation. Averroes provides advanced solutions for quality assurance, including automated defect classification, submicron defect detection, defect segmentation, defect review, and defect monitoring. The platform ensures labeling consistency, offers flexible deployment options, and has shown remarkable improvements in defect detection and productivity for semiconductor OEMs.

GGPredict.io is an AI-powered platform designed to help Counter-Strike: Global Offensive (CS:GO) players improve their skills through personalized tools and analytics. The platform offers detailed performance analysis, cutting-edge maps for practice, dynamic leaderboards, and challenges. With real-time tracking of skills and AI-led analytics, players can identify strengths, weaknesses, and areas for improvement. GGPredict.io aims to enhance players' gameplay experience and help them reach their full potential in CS:GO.

Sightwise GmbH offers an end-to-end machine vision solution powered by synthetic data. Their modular software platform is designed for manufacturing companies to enhance visual quality assurance. By leveraging synthetic data, they create tailored datasets and applications for various inspection tasks, overcoming the limitations of traditional AI. The platform enables easy data management, dataset generation, application deployment, and continuous improvements, ultimately helping manufacturers achieve top-tier product quality.

aqua is a comprehensive Quality Assurance (QA) management tool designed to streamline testing processes and enhance testing efficiency. It offers a wide range of features such as AI Copilot, bug reporting, test management, requirements management, user acceptance testing, and automation management. aqua caters to various industries including banking, insurance, manufacturing, government, tech companies, and medical sectors, helping organizations improve testing productivity, software quality, and defect detection ratios. The tool integrates with popular platforms like Jira, Jenkins, JMeter, and offers both Cloud and On-Premise deployment options. With AI-enhanced capabilities, aqua aims to make testing faster, more efficient, and error-free.

EthonAI is a Manufacturing Analytics System that offers a suite of software tools to achieve operational excellence at scale in manufacturing industries. The system provides real-time insights to improve product quality and process efficiency by analyzing production data from various sources. EthonAI helps in root cause analysis, defect detection, process monitoring, product tracking, and material flow analysis, ultimately redefining operational excellence in manufacturing.

Large Language Models Play StarCraft II is a project that explores the capabilities of large language models (LLMs) in playing the game StarCraft II. The project introduces TextStarCraft II, a textual environment for the game, and a Chain of Summarization method for analyzing game information and making strategic decisions. Through experiments, the project demonstrates that LLM agents can defeat the built-in AI at a challenging difficulty level. The project provides benchmarks and a summarization approach to enhance strategic planning and interpretability in StarCraft II gameplay.

**Promptulate** is an AI Agent application development framework crafted by **Cogit Lab** , which offers developers an extremely concise and efficient way to build Agent applications through a Pythonic development paradigm. The core philosophy of Promptulate is to borrow and integrate the wisdom of the open-source community, incorporating the highlights of various development frameworks to lower the barrier to entry and unify the consensus among developers. With Promptulate, you can manipulate components like LLM, Agent, Tool, RAG, etc., with the most succinct code, as most tasks can be easily completed with just a few lines of code. 🚀

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

LearnOpenCV is a repository containing code for Computer Vision, Deep learning, and AI research articles shared on the blog LearnOpenCV.com. It serves as a resource for individuals looking to enhance their expertise in AI through various courses offered by OpenCV. The repository includes a wide range of topics such as image inpainting, instance segmentation, robotics, deep learning models, and more, providing practical implementations and code examples for readers to explore and learn from.

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

Chat with your data using OpenAI and AI Search. This solution accelerator uses an Azure OpenAI GPT model and an Azure AI Search index generated from your data, which is integrated into a web application to provide a natural language interface, including speech-to-text functionality, for search queries. Users can drag and drop files, point to storage, and take care of technical setup to transform documents. There is a web app that users can create in their own subscription with security and authentication.

LLMWare is a framework for quickly developing LLM-based applications including Retrieval Augmented Generation (RAG) and Multi-Step Orchestration of Agent Workflows. This project provides a comprehensive set of tools that anyone can use - from a beginner to the most sophisticated AI developer - to rapidly build industrial-grade, knowledge-based enterprise LLM applications. Our specific focus is on making it easy to integrate open source small specialized models and connecting enterprise knowledge safely and securely.

This solution accelerator is built on Azure Cognitive Search Service and Azure OpenAI Service to synthesize post-contact center transcripts for intelligent contact center scenarios. It converts raw transcripts into customer call summaries to extract insights around product and service performance. Key features include conversation summarization, key phrase extraction, speech-to-text transcription, sensitive information extraction, sentiment analysis, and opinion mining. The tool enables data professionals to quickly analyze call logs for improvement in contact center operations.

LLM-Pruner is a tool for structural pruning of large language models, allowing task-agnostic compression while retaining multi-task solving ability. It supports automatic structural pruning of various LLMs with minimal human effort. The tool is efficient, requiring only 3 minutes for pruning and 3 hours for post-training. Supported LLMs include Llama-3.1, Llama-3, Llama-2, LLaMA, BLOOM, Vicuna, and Baichuan. Updates include support for new LLMs like GQA and BLOOM, as well as fine-tuning results achieving high accuracy. The tool provides step-by-step instructions for pruning, post-training, and evaluation, along with a Gradio interface for text generation. Limitations include issues with generating repetitive or nonsensical tokens in compressed models and manual operations for certain models.

This repository contains a sophisticated deterministic graph-based solution for answering complex questions using a controllable autonomous agent. The solution is designed to ensure that answers are solely based on the provided data, avoiding hallucinations. It involves various steps such as PDF loading, text preprocessing, summarization, database creation, encoding, and utilizing large language models. The algorithm follows a detailed workflow involving planning, retrieval, answering, replanning, content distillation, and performance evaluation. Heuristics and techniques implemented focus on content encoding, anonymizing questions, task breakdown, content distillation, chain of thought answering, verification, and model performance evaluation.

Build-your-own-AI-Assistant-Solution-Accelerator is a pre-release and preview solution that helps users create their own AI assistants. It leverages Azure Open AI Service, Azure AI Search, and Microsoft Fabric to identify, summarize, and categorize unstructured information. Users can easily find relevant articles and grants, generate grant applications, and export them as PDF or Word documents. The solution accelerator provides reusable architecture and code snippets for building AI assistants with enterprise data. It is designed for researchers looking to explore flu vaccine studies and grants to accelerate grant proposal submissions.

IOPaint is a free and open-source inpainting & outpainting tool powered by SOTA AI model. It supports various AI models to perform erase, inpainting, or outpainting tasks. Users can remove unwanted objects, defects, watermarks, or people from images using erase models. Additionally, diffusion models can replace objects or perform outpainting. The tool also offers plugins for interactive object segmentation, background removal, anime segmentation, super resolution, face restoration, and file management. IOPaint provides a web UI for easy access to the latest AI models and supports batch processing of images through the command line. Developers can contribute to the project by installing front-end dependencies, setting up the backend, and starting the development environment for both front-end and back-end components.

Bugbug is a tool developed by Mozilla that leverages machine learning techniques to assist with bug and quality management, as well as other software engineering tasks like test selection and defect prediction. It provides various classifiers to suggest assignees, detect patches likely to be backed-out, classify bugs, assign product/components, distinguish between bugs and feature requests, detect bugs needing documentation, identify invalid issues, verify bugs needing QA, detect regressions, select relevant tests, track bugs, and more. Bugbug can be trained and tested using Python scripts, and it offers the ability to run model training tasks on Taskcluster. The project structure includes modules for data mining, bug/commit feature extraction, model implementations, NLP utilities, label handling, bug history playback, and GitHub issue retrieval.

NNStreamer is a set of Gstreamer plugins that allow Gstreamer developers to adopt neural network models easily and efficiently and neural network developers to manage neural network pipelines and their filters easily and efficiently.

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

Bagatur chess engine is a powerful Java chess engine that can run on Android devices and desktop computers. It supports the UCI protocol and can be easily integrated into chess programs with user interfaces. The engine is available for download on various platforms and has advanced features like SMP (multicore) support and NNUE evaluation function. Bagatur also includes syzygy endgame tablebases and offers various UCI options for customization. The project started as a personal challenge to create a chess program that could defeat a friend, leading to years of development and improvements.

Gigax is a tool for creating and controlling Non-Player Characters (NPCs) powered by Large Language Models (LLMs). It allows users to define actions for NPCs such as speaking, jumping, and attacking, with quick GPU inference times. The tool provides access to open-weights models fine-tuned from Llama-3, Phi-3, Mistral, and more. Users can generate structured content with outlines, ensuring the output format is always respected. Gigax is continuously evolving with upcoming features like local server mode and API support for runtime quest generation and memory management. It offers various models on the Huggingface hub for instantiating NPCs and provides classes for handling locations, characters, items, and events.

Ah, Perry the Platypus, behold my new -inator!

A knowledgeable guide for improving your Minecraft Java skills.

Stuck at progressing in a game? Need details about a specific item?

Your expert guide for all things Isaac, now with more features!

Mysterious and just, as Batman.

The mustachioed plumber who leaps into adventure!

Your expert guide for Pokémon adventures, based on Bulbapedia's strategies and walkthroughs.

Designed for excellence in Quality Assurance, fine-tuning custom GPT configurations through continuous refinement.

Enhanced QA/QC expertise with user-driven improvements, powered by OpenAI

Expert in Software Testing, Test Automation, And AI. Modeled after Jason Arbon.