Best AI tools for< Implement Concepts >

AI Summer is a free educational platform that covers research and applied trends in AI and Deep Learning. It provides accessible and comprehensive content from the entire spectrum of AI to bridge the gap between researchers and the public. The platform simplifies complex concepts and drives scientific research by offering highly-detailed overviews of recent deep learning developments and thorough tutorials on popular frameworks. AI Summer is a community that seeks to demystify the AI landscape and enable new technological innovations.

Dale on AI is a website dedicated to providing insightful articles and guides on various topics related to artificial intelligence, machine learning, and deep learning. The website covers a wide range of subjects, from practical tutorials on building AI-powered applications to in-depth explanations of cutting-edge AI technologies. With a focus on making complex AI concepts accessible to developers and enthusiasts, Dale on AI serves as a valuable resource for anyone interested in exploring the world of artificial intelligence.

FPOV is an AI application that helps businesses transform into digital leaders by providing services in leadership, technology operations, people/culture, and artificial intelligence. The application offers workshops, strategies, analysis, support, and advisory services to help organizations succeed in the digital age. FPOV aims to be world-class thought leaders in navigating the constantly changing digital dynamics that impact organizations and people.

The Robot Code Generator by Pantheon Robotics is a web application that allows users to generate executable robot code from natural language. The tool is designed to simplify the process of creating code for a generic robot based on a physical proof-of-concept, such as a car. By inputting instructions in plain language, users can quickly generate the necessary code for the robot to perform specific tasks. The application is powered by advanced AI technologies, including GPT-4 and Vercel AI SDK, to enhance code generation accuracy and efficiency.

Beebzi.AI is an all-in-one AI content creation platform that offers a wide array of tools for generating various types of content such as articles, blogs, emails, images, voiceovers, and more. The platform utilizes advanced AI technology and behavioral science to empower businesses and individuals in their marketing and sales endeavors. With features like AI Article Wizard, AI Room Designer, AI Landing Page Generator, and AI Code Generation, Beebzi.AI revolutionizes content creation by providing customizable templates, multiple language support, and real-time data insights. The platform also offers various subscription plans tailored for individual entrepreneurs, teams, and businesses, with flexible pricing models based on word count allocations. Beebzi.AI aims to streamline content creation processes, enhance productivity, and drive organic traffic through SEO-optimized content.

STELLARWITS is an AI solutions and software platform that empowers users to explore cutting-edge technology and innovation. The platform offers AI models with versatile capabilities, ranging from content generation to data analysis to problem-solving. Users can engage directly with the technology, experiencing its power in real-time. With a focus on transforming ideas into technology, STELLARWITS provides tailored solutions in software and AI development, delivering intelligent systems and machine learning models for innovative and efficient solutions. The platform also features a download hub with a curated selection of solutions to enhance the digital experience. Through blogs and company information, users can delve deeper into the narrative of STELLARWITS, exploring its mission, vision, and commitment to reshaping the tech landscape.

Ringover is an AI-driven conversation platform designed for staffing and sales teams. It offers features such as transcription and call summaries, mood analysis, cloud telephony, multichannel communications, sales prospecting automations, app marketplace integration, and more. The platform aims to centralize all communication channels within a simple interface, empowering users to enhance productivity and streamline conversations with clients and prospects. Ringover also provides advanced analytics, automation, and coaching to boost the productivity of recruiting and sales teams. With seamless integration with various business tools, Ringover offers a comprehensive solution for businesses looking to optimize their communication strategies.

RankSense is an AI-powered SEO tool designed to help users optimize their website's search engine performance efficiently. Created by Hamlet Batista, RankSense enables users to implement immediate changes to SEO meta tags, structured data, and redirects at scale. By leveraging Cloudflare and Google Sheets, users can make SEO changes on thousands of pages with just a few clicks, without the need for developers. The tool also offers features such as monitoring SEO changes, discovering pages that need optimization, and automatically improving search snippets using artificial intelligence.

RIOS is an AI-powered automation tool that revolutionizes American manufacturing by leveraging robotics and AI technology. It offers flexible, reliable, and efficient robotic automation solutions that integrate seamlessly into existing production lines, helping businesses improve productivity, reduce operating expenses, and minimize risks. RIOS provides intelligent agents, machine tending, food handling, and end-of-line packout services, powered by AI and robotics. The tool aims to simplify complex manual processes, ensure total control of operations, and cut costs for businesses facing production inefficiencies and challenges in labor productivity.

Cue AI is an AI research lab dedicated to enhancing the capabilities of cutting-edge models. The lab is committed to pushing the boundaries of AI technology and innovation. While the website currently has limited information, it serves as a platform for sharing updates and developments in the field of artificial intelligence. For inquiries or collaborations, users can reach out via email at [email protected].

Faculty AI is a leading applied AI consultancy and technology provider, specializing in helping customers transform their businesses through bespoke AI consultancy and Frontier, the world's first AI operating system. They offer services such as AI consultancy, generative AI solutions, and AI services tailored to various industries. Faculty AI is known for its expertise in AI governance and safety, as well as its partnerships with top AI platforms like OpenAI, AWS, and Microsoft.

Modulos is a Responsible AI Platform that integrates risk management, data science, legal compliance, and governance principles to ensure responsible innovation and adherence to industry standards. It offers a comprehensive solution for organizations to effectively manage AI risks and regulations, streamline AI governance, and achieve relevant certifications faster. With a focus on compliance by design, Modulos helps organizations implement robust AI governance frameworks, execute real use cases, and integrate essential governance and compliance checks throughout the AI life cycle.

Papers With Code is an AI tool that provides access to the latest research papers in the field of Machine Learning, along with corresponding code implementations. It offers a platform for researchers and enthusiasts to stay updated on state-of-the-art datasets, methods, and trends in the ML domain. Users can explore a wide range of topics such as language modeling, image generation, virtual try-on, and more through the collection of papers and code available on the website.

SentiSight.ai is a machine learning platform for image recognition solutions, offering services such as object detection, image segmentation, image classification, image similarity search, image annotation, computer vision consulting, and intelligent automation consulting. Users can access pre-trained models, background removal, NSFW detection, text recognition, and image recognition API. The platform provides tools for image labeling, project management, and training tutorials for various image recognition models. SentiSight.ai aims to streamline the image annotation process, empower users to build and train their own models, and deploy them for online or offline use.

Notice is an AI-powered platform that allows users to create blogs, documents, portfolios, and more with ease. It offers collaborative editing, auto-translation in over 100 languages, and an AI writing assistant. Users can embed their content anywhere on the web using ready-to-use templates that are SEO-friendly. Notice simplifies content creation and publishing, making it accessible to users of all skill levels.

Rebecca Bultsma is a trusted and experienced AI educator who aims to make AI simple and ethical for everyday use. She provides resources, speaking engagements, and consulting services to help individuals and organizations understand and integrate AI into their workflows. Rebecca empowers people to work in harmony with AI, leveraging its capabilities to tackle challenges, spark creative ideas, and make a lasting impact. She focuses on making AI easy to understand and promoting ethical adoption strategies.

My Cheeky Bot is an AI tool that allows users to create advanced AI bots in minutes to add custom lead gen chat assistants to their business websites. It offers a solution for effortless customer engagement by providing personalized customer service assistants. The tool aims to help small businesses and freelance developers manage customer queries and provide instant assistance without the need for any coding skills. With innovative chatbot technology, My Cheeky Bot enables users to enhance their website's customer engagement experience and stay connected with their audience in today's fast-paced digital landscape.

Velocity Explorations is an AI tool that empowers warfighters with cutting-edge technology by enhancing existing software systems with advanced AI capabilities. The team uses data to develop impactful solutions, focusing on prototyping, iterative development, and user-centered design. Their services include AI integration, spaceport integration, and business optimization to streamline processes and improve operational efficiency. The technology offered includes secure, hosted Mattermost for DoD teams, flexible AI integration, and AI-driven content based on live audio recordings.

Nebius AI is an AI-centric cloud platform designed to handle intensive workloads efficiently. It offers a range of advanced features to support various AI applications and projects. The platform ensures high performance and security for users, enabling them to leverage AI technology effectively in their work. With Nebius AI, users can access cutting-edge AI tools and resources to enhance their projects and streamline their workflows.

Zenus AI is a behavioral analytics tool for events and retail, offering facial analysis and custom solutions for event organizers, retail brands, and exhibitors. The tool provides insights such as demographics, sentiment analysis, and behavioral tracking with 95% accuracy without collecting personal data. It helps businesses understand consumers, attract more exhibitors, and improve visitor experience through AI-powered solutions.

This repository provides a comprehensive guide to understanding and applying artificial intelligence (AI) theory, including basic knowledge, machine learning, deep learning, and natural language processing (BERT). It features detailed explanations, annotated code, and datasets to help users grasp the concepts and implement them in practice. The repository is continuously updated to ensure the latest information and best practices are covered.

The 100 Days in AI repository provides a comprehensive roadmap for individuals to learn Artificial Intelligence over a period of 100 days. It covers topics ranging from basic programming in Python to advanced concepts in AI, including machine learning, deep learning, and specialized AI topics. The repository includes daily tasks, resources, and exercises to ensure a structured learning experience. By following this roadmap, users can gain a solid understanding of AI and be prepared to work on real-world AI projects.

Generative AI Indepth Basic to Advance is a repository focused on providing tutorials and resources related to generative artificial intelligence. The repository covers a wide range of topics from basic concepts to advanced techniques in the field of generative AI. Users can find detailed explanations, code examples, and practical demonstrations to help them understand and implement generative AI algorithms. The goal of this repository is to help beginners get started with generative AI and to provide valuable insights for more experienced practitioners.

This project is a tutorial on developing large model applications for novice developers. It aims to provide a comprehensive introduction to large model development, focusing on Alibaba Cloud servers and integrating personal knowledge assistant projects. The tutorial covers the following topics: 1. **Introduction to Large Models**: A simplified introduction for novice developers on what large models are, their characteristics, what LangChain is, and how to develop an LLM application. 2. **How to Call Large Model APIs**: This section introduces various methods for calling APIs of well-known domestic and foreign large model products, including calling native APIs, encapsulating them as LangChain LLMs, and encapsulating them as Fastapi calls. It also provides a unified encapsulation for various large model APIs, such as Baidu Wenxin, Xunfei Xinghuo, and Zh譜AI. 3. **Knowledge Base Construction**: Loading, processing, and vector database construction of different types of knowledge base documents. 4. **Building RAG Applications**: Integrating LLM into LangChain to build a retrieval question and answer chain, and deploying applications using Streamlit. 5. **Verification and Iteration**: How to implement verification and iteration in large model development, and common evaluation methods. The project consists of three main parts: 1. **Introduction to LLM Development**: A simplified version of V1 aims to help beginners get started with LLM development quickly and conveniently, understand the general process of LLM development, and build a simple demo. 2. **LLM Development Techniques**: More advanced LLM development techniques, including but not limited to: Prompt Engineering, processing of multiple types of source data, optimizing retrieval, recall ranking, Agent framework, etc. 3. **LLM Application Examples**: Introduce some successful open source cases, analyze the ideas, core concepts, and implementation frameworks of these application examples from the perspective of this course, and help beginners understand what kind of applications they can develop through LLM. Currently, the first part has been completed, and everyone is welcome to read and learn; the second and third parts are under creation. **Directory Structure Description**: requirements.txt: Installation dependencies in the official environment notebook: Notebook source code file docs: Markdown documentation file figures: Pictures data_base: Knowledge base source file used

Pipecat is an open-source framework designed for building generative AI voice bots and multimodal assistants. It provides code building blocks for interacting with AI services, creating low-latency data pipelines, and transporting audio, video, and events over the Internet. Pipecat supports various AI services like speech-to-text, text-to-speech, image generation, and vision models. Users can implement new services and contribute to the framework. Pipecat aims to simplify the development of applications like personal coaches, meeting assistants, customer support bots, and more by providing a complete framework for integrating AI services.

The Machine Learning Road Map is a comprehensive guide designed to take individuals from various levels of machine learning knowledge to a basic understanding of machine learning principles using high-quality, free resources. It aims to simplify the complex and rapidly growing field of machine learning by providing a structured roadmap for learning. The guide emphasizes the importance of understanding AI for everyone, the need for patience in learning machine learning due to its complexity, and the value of learning from experts in the field. It covers five different paths to learning about machine learning, catering to consumers, aspiring AI researchers, ML engineers, developers interested in building ML applications, and companies looking to implement AI solutions.

**deep** doctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated framework for fine-tuning, evaluating and running models. For more specific text processing tasks use one of the many other great NLP libraries. **deep** doctection focuses on applications and is made for those who want to solve real world problems related to document extraction from PDFs or scans in various image formats. **deep** doctection provides model wrappers of supported libraries for various tasks to be integrated into pipelines. Its core function does not depend on any specific deep learning library. Selected models for the following tasks are currently supported: * Document layout analysis including table recognition in Tensorflow with **Tensorpack**, or PyTorch with **Detectron2**, * OCR with support of **Tesseract**, **DocTr** (Tensorflow and PyTorch implementations available) and a wrapper to an API for a commercial solution, * Text mining for native PDFs with **pdfplumber**, * Language detection with **fastText**, * Deskewing and rotating images with **jdeskew**. * Document and token classification with all LayoutLM models provided by the **Transformer library**. (Yes, you can use any LayoutLM-model with any of the provided OCR-or pdfplumber tools straight away!). * Table detection and table structure recognition with **table-transformer**. * There is a small dataset for token classification available and a lot of new tutorials to show, how to train and evaluate this dataset using LayoutLMv1, LayoutLMv2, LayoutXLM and LayoutLMv3. * Comprehensive configuration of **analyzer** like choosing different models, output parsing, OCR selection. Check this notebook or the docs for more infos. * Document layout analysis and table recognition now runs with **Torchscript** (CPU) as well and **Detectron2** is not required anymore for basic inference. * [**new**] More angle predictors for determining the rotation of a document based on **Tesseract** and **DocTr** (not contained in the built-in Analyzer). * [**new**] Token classification with **LiLT** via **transformers**. We have added a model wrapper for token classification with LiLT and added a some LiLT models to the model catalog that seem to look promising, especially if you want to train a model on non-english data. The training script for LayoutLM can be used for LiLT as well and we will be providing a notebook on how to train a model on a custom dataset soon. **deep** doctection provides on top of that methods for pre-processing inputs to models like cropping or resizing and to post-process results, like validating duplicate outputs, relating words to detected layout segments or ordering words into contiguous text. You will get an output in JSON format that you can customize even further by yourself. Have a look at the **introduction notebook** in the notebook repo for an easy start. Check the **release notes** for recent updates. **deep** doctection or its support libraries provide pre-trained models that are in most of the cases available at the **Hugging Face Model Hub** or that will be automatically downloaded once requested. For instance, you can find pre-trained object detection models from the Tensorpack or Detectron2 framework for coarse layout analysis, table cell detection and table recognition. Training is a substantial part to get pipelines ready on some specific domain, let it be document layout analysis, document classification or NER. **deep** doctection provides training scripts for models that are based on trainers developed from the library that hosts the model code. Moreover, **deep** doctection hosts code to some well established datasets like **Publaynet** that makes it easy to experiment. It also contains mappings from widely used data formats like COCO and it has a dataset framework (akin to **datasets** so that setting up training on a custom dataset becomes very easy. **This notebook** shows you how to do this. **deep** doctection comes equipped with a framework that allows you to evaluate predictions of a single or multiple models in a pipeline against some ground truth. Check again **here** how it is done. Having set up a pipeline it takes you a few lines of code to instantiate the pipeline and after a for loop all pages will be processed through the pipeline.

The 'create-million-parameter-llm-from-scratch' repository provides a detailed guide on creating a Large Language Model (LLM) with 2.3 million parameters from scratch. The blog replicates the LLaMA approach, incorporating concepts like RMSNorm for pre-normalization, SwiGLU activation function, and Rotary Embeddings. The model is trained on a basic dataset to demonstrate the ease of creating a million-parameter LLM without the need for a high-end GPU.

Azure OpenAI Service is a central capability with Azure API Management, providing guidance and tools for organizations to implement Azure OpenAI in a production environment with an emphasis on cost control, secure access, and usage monitoring. It includes infrastructure-as-code templates, CI/CD pipelines, secure access management, usage monitoring, load balancing, streaming requests, and end-to-end samples like ChatApp and Azure Dashboards.

MSCCL++ is a GPU-driven communication stack for scalable AI applications. It provides a highly efficient and customizable communication stack for distributed GPU applications. MSCCL++ redefines inter-GPU communication interfaces, delivering a highly efficient and customizable communication stack for distributed GPU applications. Its design is specifically tailored to accommodate diverse performance optimization scenarios often encountered in state-of-the-art AI applications. MSCCL++ provides communication abstractions at the lowest level close to hardware and at the highest level close to application API. The lowest level of abstraction is ultra light weight which enables a user to implement logics of data movement for a collective operation such as AllReduce inside a GPU kernel extremely efficiently without worrying about memory ordering of different ops. The modularity of MSCCL++ enables a user to construct the building blocks of MSCCL++ in a high level abstraction in Python and feed them to a CUDA kernel in order to facilitate the user's productivity. MSCCL++ provides fine-grained synchronous and asynchronous 0-copy 1-sided abstracts for communication primitives such as `put()`, `get()`, `signal()`, `flush()`, and `wait()`. The 1-sided abstractions allows a user to asynchronously `put()` their data on the remote GPU as soon as it is ready without requiring the remote side to issue any receive instruction. This enables users to easily implement flexible communication logics, such as overlapping communication with computation, or implementing customized collective communication algorithms without worrying about potential deadlocks. Additionally, the 0-copy capability enables MSCCL++ to directly transfer data between user's buffers without using intermediate internal buffers which saves GPU bandwidth and memory capacity. MSCCL++ provides consistent abstractions regardless of the location of the remote GPU (either on the local node or on a remote node) or the underlying link (either NVLink/xGMI or InfiniBand). This simplifies the code for inter-GPU communication, which is often complex due to memory ordering of GPU/CPU read/writes and therefore, is error-prone.

Mentals AI is a tool designed for creating and operating agents that feature loops, memory, and various tools, all through straightforward markdown syntax. This tool enables you to concentrate solely on the agent’s logic, eliminating the necessity to compose underlying code in Python or any other language. It redefines the foundational frameworks for future AI applications by allowing the creation of agents with recursive decision-making processes, integration of reasoning frameworks, and control flow expressed in natural language. Key concepts include instructions with prompts and references, working memory for context, short-term memory for storing intermediate results, and control flow from strings to algorithms. The tool provides a set of native tools for message output, user input, file handling, Python interpreter, Bash commands, and short-term memory. The roadmap includes features like a web UI, vector database tools, agent's experience, and tools for image generation and browsing. The idea behind Mentals AI originated from studies on psychoanalysis executive functions and aims to integrate 'System 1' (cognitive executor) with 'System 2' (central executive) to create more sophisticated agents.

mlcourse.ai is an open Machine Learning course by OpenDataScience (ods.ai), led by Yury Kashnitsky (yorko). The course offers a perfect balance between theory and practice, with math formulae in lectures and practical assignments including Kaggle Inclass competitions. It is currently in a self-paced mode, guiding users through 10 weeks of content covering topics from Pandas to Gradient Boosting. The course provides articles, lectures, and assignments to enhance understanding and application of machine learning concepts.

AI Gallery is a showcase site built using React and Nextjs for static site generation, featuring interactive visualizations of classic algorithms, classic games implementation, and various interesting widgets. The project utilizes AI assistance from Claude 3.5 and GPT-4 to create components and enhance the development process. It aims to continually add more components with AI assistance, providing a platform for contributors to leverage AI in frontend development.

This repository contains sample code demonstrating various use cases leveraging Amazon Bedrock and Generative AI. Each sample is a separate project with its own directory, and includes a basic Streamlit frontend to help users quickly set up a proof of concept.

Awesome-Embedded is a curated list of resources for embedded systems enthusiasts. It covers a wide range of topics including MCU programming, RTOS, Linux kernel development, assembly programming, machine learning & AI on MCU, utilities, tips & tricks, and more. The repository provides valuable information, tutorials, and tools for individuals interested in embedded systems development.

This repository focuses on utilizing generative AI to bridge the gap between natural language questions and SQL queries, aiming to improve data consumption in enterprise data warehouses. It addresses challenges in SQL query generation, such as foreign key relationships and table joins, and highlights the importance of accuracy metrics like Execution Accuracy (EX) and Exact Set Match Accuracy (EM). The workshop content covers advanced prompt engineering, Retrieval Augmented Generation (RAG), fine-tuning models, and security measures against prompt and SQL injections.

uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

The 'awesome-mobile-robotics' repository is a curated list of important content related to Mobile Robotics and AI. It includes resources such as courses, books, datasets, software and libraries, podcasts, conferences, journals, companies and jobs, laboratories and research groups, and miscellaneous resources. The repository covers a wide range of topics in the field of Mobile Robotics and AI, providing valuable information for enthusiasts, researchers, and professionals in the domain.

This practical free hands-on course focuses on Large Language models and their applications, providing a hands-on experience using models from OpenAI and the Hugging Face library. The course is divided into three major sections: Techniques and Libraries, Projects, and Enterprise Solutions. It covers topics such as Chatbots, Code Generation, Vector databases, LangChain, Fine Tuning, PEFT Fine Tuning, Soft Prompt tuning, LoRA, QLoRA, Evaluate Models, Knowledge Distillation, and more. Each section contains chapters with lessons supported by notebooks and articles. The course aims to help users build projects and explore enterprise solutions using Large Language Models.

AIKA (Artificial Intelligence for Knowledge Acquisition) is a new type of artificial neural network designed to mimic the behavior of a biological brain more closely and bridge the gap to classical AI. The network conceptually separates activations from neurons, creating two separate graphs to represent acquired knowledge and inferred information. It uses different types of neurons and synapses to propagate activation values, binding signals, causal relations, and training gradients. The network structure allows for flexible topology and supports the gradual population of neurons and synapses during training.

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Assists with Qiskit code and quantum computing concepts.

Improves product quality through innovative research and development.

A bot for fast, direct coding help, skipping basic steps.

Implement specific web applications based on sketches submitted by users

Provides concise GC troubleshooting and method development advice that is easy to implement.

Your proactive virtual CTO, ready to implement requests

Assists in enhancing e-commerce sites for better conversions with tailored, easy-to-implement advice.

Insurance providers collect and process personal health, financial, and property information, making it crucial to implement comprehensive data protection strategies.

Agente de IA especializado em Proteção de Dados

Guides users on Oracle EPM Cloud services and tasks.

Expert in Your ERP software, specializing in White Label contracts and implementation advice.

ISO27001およびISO/IEC 27002のベストプラクティスに精通したアドバイザー　Expert in ISO27001 and ISO/IEC 27002 best practices.

Japanese-first, young GCP expert with AI diagrams.

Consultor especializado em SAP ECC 6

Demystifying ISO 26262: Your Simple Guide to Automotive Functional Safety

Mon expert en protection des données

Spécialiste ISO 15189 et documents COFRAC pour les conseils en qualité des laboratoires médicaux.

Guides organization in telecommunications systems implementation and optimization.

Guides in designing, implementing, and maintaining technical architecture.