Best AI tools for< Deploy Virtual Machines >

Microsoft Azure is a cloud computing service that offers a wide range of products and solutions for businesses and developers. It provides services such as virtual machines, AI services, Kubernetes service, DevOps, SQL databases, and more. Azure aims to empower users to build, deploy, and manage applications and services on a global scale, with a focus on innovation, security, and scalability.

3pi.ai is a conversational AI platform that helps businesses build and deploy AI-powered chatbots and virtual assistants. It provides a range of features to help businesses create engaging and informative chatbots, including natural language processing, machine learning, and a drag-and-drop interface. 3pi.ai's chatbots can be used to automate customer service, sales, and marketing tasks, and can be deployed on a variety of platforms, including websites, messaging apps, and social media.

Helix AI is a private GenAI platform that enables users to build AI applications using open source models. The platform offers tools for RAG (Retrieval-Augmented Generation) and fine-tuning, allowing deployment on-premises or in a Virtual Private Cloud (VPC). Users can access curated models, utilize Helix API tools to connect internal and external APIs, embed Helix Assistants into websites/apps for chatbot functionality, write AI application logic in natural language, and benefit from the innovative RAG system for Q&A generation. Additionally, users can fine-tune models for domain-specific needs and deploy securely on Kubernetes or Docker in any cloud environment. Helix Cloud offers free and premium tiers with GPU priority, catering to individuals, students, educators, and companies of varying sizes.

Paperspace is an AI tool designed to develop, train, and deploy AI models of any size and complexity. It offers a cloud GPU platform for accelerated computing, with features such as GPU cloud workflows, machine learning solutions, GPU infrastructure, virtual desktops, gaming, rendering, 3D graphics, and simulation. Paperspace provides a seamless abstraction layer for individuals and organizations to focus on building AI applications, offering low-cost GPUs with per-second billing, infrastructure abstraction, job scheduling, resource provisioning, and collaboration tools.

Dust is a customizable and secure AI assistant platform that helps businesses amplify their team's potential. It allows users to deploy the best Large Language Models to their company, connect Dust to their team's data, and empower their teams with assistants tailored to their specific needs. Dust is exceptionally modular and adaptable, tailoring to unique requirements and continuously evolving to meet changing needs. It supports multiple sources of data and models, including proprietary and open-source models from OpenAI, Anthropic, and Mistral. Dust also helps businesses identify their most creative and driven team members and share their experience with AI throughout the company. It promotes collaboration with shared conversations, @mentions in discussions, and Slackbot integration. Dust prioritizes security and data privacy, ensuring that data remains private and that enterprise-grade security measures are in place to manage data access policies.

InputAI is a conversational AI platform that enables businesses to build and deploy AI-powered chatbots and virtual assistants. It provides a range of features to help businesses create engaging and informative chat experiences, including natural language processing, machine learning, and analytics.

Alltius is a platform that allows users to build and deploy AI assistants for sales and support teams. The platform provides a variety of tools and features to help users create assistants that are accurate, secure, and easy to use. Alltius's assistants can be used to automate a variety of tasks, such as answering customer questions, generating leads, and scheduling appointments. The platform also includes a library of pre-built skills that can be used to add functionality to assistants.

Sierra is a conversational AI platform that enables companies to build AI agents that are personalized to their business and customers. With Sierra, companies can deploy AI agents that are always available, empathetic, and aligned to their brand tone and voice. Sierra's AI agents can help customers with a variety of tasks, such as getting answers to questions, solving problems, and taking action. Sierra is trusted by leading consumer brands with millions of customers across a wide range of industries.

Kindbuds.ai is a platform that allows users to create, train, and deploy custom AI bots. With Kindbuds.ai, users can build bots for a variety of purposes, including customer service, marketing, and sales. Kindbuds.ai also offers an AI Marketplace, where users can buy and sell pre-trained bots.

Poplar Studio is a visualisation technology platform that powers a new generation of shopping experiences through 3D and AR previews of products across e-commerce websites, social commerce, and the metaverse. It offers end-to-end 3D and AR virtual commerce solutions to increase conversions and engage targeted audiences with interactive AR and 3D campaigns. Poplar Studio collaborates with brands to create bespoke AR and 3D experiences tailored to their needs, enhancing brand awareness and customer engagement.

BotGPT is a 24/7 custom AI chatbot assistant for websites. It offers a data-driven ChatGPT that allows users to create virtual assistants from their own data. Users can easily upload files or crawl their website to start asking questions and deploy a custom chatbot on their website within minutes. The platform provides a simple and efficient way to enhance customer engagement through AI-powered chatbots.

MagikKraft is an AI-powered platform that simplifies complex controls by enabling users to create personalized sequences and actions for programmable devices like drones, automated appliances, and self-driving vehicles. Users can craft, simulate, and deploy customized recipes through the AI-powered tool, enhancing the potential of technology while prioritizing privacy, user control, and creative freedom.

Picovoice is an on-device Voice AI and local LLM platform designed for enterprises. It offers a range of voice AI and LLM solutions, including speech-to-text, noise suppression, speaker recognition, speech-to-index, wake word detection, and more. Picovoice empowers developers to build virtual assistants and AI-powered products with compliance, reliability, and scalability in mind. The platform allows enterprises to process data locally without relying on third-party remote servers, ensuring data privacy and security. With a focus on cutting-edge AI technology, Picovoice enables users to stay ahead of the curve and adapt quickly to changing customer needs.

LuckyRobots is an AI tool designed to make robotics accessible to software engineers by providing a simulation platform for deploying end-to-end AI models. The platform allows users to interact with robots using natural language commands, explore virtual environments, test robot models in realistic scenarios, and receive camera feeds for monitoring. LuckyRobots aims to train AI models on real-world simulations and respond to natural language inputs, offering a user-friendly and innovative approach to robotics development.

Quidget is a no-code AI Agent platform designed to build, train, and deploy AI assistants for websites, apps, or as standalone chatbots. It offers features such as answering customer support questions, engaging leads for sales, automating bookings, orders, and inquiries, as well as assisting with HR, finance, and operations. Quidget AI Agents are trained virtual assistants that go beyond basic chatbots by understanding, learning, and intelligently assisting customers. The platform allows customization of AI behavior, deployment on multiple channels, and integration with various tools. Quidget supports 45+ languages and ensures data security with end-to-end encryption and GDPR compliance.

Chatbase is an AI tool that provides custom ChatGPT models tailored to your data. It allows users to create conversational AI models that are specific to their needs, enabling more engaging and personalized interactions with customers. With Chatbase, users can easily train, deploy, and manage chatbots for various applications such as customer support, virtual assistants, and more. The platform offers advanced natural language processing capabilities to understand and respond to user queries effectively.

Millis AI is an advanced AI tool that enables users to effortlessly create next-gen voice agents with ultra-low latency, providing a seamless and natural conversational experience. It offers affordable pricing, integration with various services through webhooks, and the ability to connect phone numbers to AI voice agents for inbound/outbound calls in over 100 countries. With Millis AI, users can build and deploy voice agents in minutes, from no-code to low-code developers, and transform voice interactions across industries.

VEGA AI is an AI-powered virtual entity designed for guidance and assistance in the field of education. It offers an AI-first learning platform that allows users to effortlessly create personalized courses, gain learning insights, and support students with the help of an AI avatar. Trusted by leading institutions worldwide, VEGA AI helps educators deploy adaptive learning environments, build personalized learning paths, and provide 24/7 AI avatar support. The platform aims to transform teaching by automating workflows, reducing workload, and boosting student outcomes through AI automation and personalized learning journeys.

OmniAI is an AI tool that allows teams to deploy AI applications on their existing infrastructure. It provides a unified API experience for building AI applications and offers a wide selection of industry-leading models. With tools like Llama 3, Claude 3, Mistral Large, and AWS Titan, OmniAI excels in tasks such as natural language understanding, generation, safety, ethical behavior, and context retention. It also enables users to deploy and query the latest AI models quickly and easily within their virtual private cloud environment.

Mentals.ai is an operating system for AI agents that enables users to design and deploy complex AI agents using natural language instructions. It focuses on creativity and logic rather than programming, allowing for multi-agent collaboration, advanced features like memory and code execution, and various use cases such as business automation, personal automation, and marketing automation. The platform also supports the creation of intelligent chatbots, virtual employees, and multi-agent systems, revolutionizing productivity and problem-solving in various domains.

Tau is a framework for building low maintenance & highly scalable cloud computing platforms that software developers will love. It aims to solve the high cost and time required to build, deploy, and scale software by providing a developer-friendly platform that offers autonomy and flexibility. Tau simplifies the process of building and maintaining a cloud computing platform, enabling developers to achieve 'Local Coding Equals Global Production' effortlessly. With features like auto-discovery, content-addressing, and support for WebAssembly, Tau empowers users to create serverless computing environments, host frontends, manage databases, and more. The platform also supports E2E testing and can be extended using a plugin system called orbit.

This repository showcases how to deploy generative AI models from Amazon SageMaker JumpStart using the AWS CDK. Generative AI is a type of AI that can create new content and ideas, such as conversations, stories, images, videos, and music. The repository provides a detailed guide on deploying image and text generative AI models, utilizing pre-trained models from SageMaker JumpStart. The web application is built on Streamlit and hosted on Amazon ECS with Fargate. It interacts with the SageMaker model endpoints through Lambda functions and Amazon API Gateway. The repository also includes instructions on setting up the AWS CDK application, deploying the stacks, using the models, and viewing the deployed resources on the AWS Management Console.

AMD-AI is a repository containing detailed instructions for installing, setting up, and configuring ROCm on Ubuntu systems with AMD GPUs. The repository includes information on installing various tools like Stable Diffusion, ComfyUI, and Oobabooga for tasks like text generation and performance tuning. It provides guidance on adding AMD GPU package sources, installing ROCm-related packages, updating system packages, and finding graphics devices. The instructions are aimed at users with AMD hardware looking to set up their Linux systems for AI-related tasks.

This repository contains scripts for installing HPC and AI libraries and tools to build Azure HPC/AI images. It streamlines the process of provisioning compute-intensive workloads and crafting advanced AI models in the cloud, ensuring efficiency and reliability in deployments.

AIlice is a fully autonomous, general-purpose AI agent that aims to create a standalone artificial intelligence assistant, similar to JARVIS, based on the open-source LLM. AIlice achieves this goal by building a "text computer" that uses a Large Language Model (LLM) as its core processor. Currently, AIlice demonstrates proficiency in a range of tasks, including thematic research, coding, system management, literature reviews, and complex hybrid tasks that go beyond these basic capabilities. AIlice has reached near-perfect performance in everyday tasks using GPT-4 and is making strides towards practical application with the latest open-source models. We will ultimately achieve self-evolution of AI agents. That is, AI agents will autonomously build their own feature expansions and new types of agents, unleashing LLM's knowledge and reasoning capabilities into the real world seamlessly.

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.

The Data Scientist Roadmap2024 provides a comprehensive guide to mastering essential tools for data science success. It includes programming languages, machine learning libraries, cloud platforms, and concepts categorized by difficulty. The roadmap covers a wide range of topics from programming languages to machine learning techniques, data visualization tools, and DevOps/MLOps tools. It also includes web development frameworks and specific concepts like supervised and unsupervised learning, NLP, deep learning, reinforcement learning, and statistics. Additionally, it delves into DevOps tools like Airflow and MLFlow, data visualization tools like Tableau and Matplotlib, and other topics such as ETL processes, optimization algorithms, and financial modeling.

Kalavai is an open-source platform that transforms everyday devices into an AI supercomputer by aggregating resources from multiple machines. It facilitates matchmaking of resources for large AI projects, making AI hardware accessible and affordable. Users can create local and public pools, connect with the community's resources, and share computing power. The platform aims to be a management layer for research groups and organizations, enabling users to unlock the power of existing hardware without needing a devops team. Kalavai CLI tool helps manage both versions of the platform.

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.

AITreasureBox is a comprehensive collection of AI tools and resources designed to simplify and accelerate the development of AI projects. It provides a wide range of pre-trained models, datasets, and utilities that can be easily integrated into various AI applications. With AITreasureBox, developers can quickly prototype, test, and deploy AI solutions without having to build everything from scratch. Whether you are working on computer vision, natural language processing, or reinforcement learning projects, AITreasureBox has something to offer for everyone. The repository is regularly updated with new tools and resources to keep up with the latest advancements in the field of artificial intelligence.

Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.

The STM32 AI model zoo is a collection of reference machine learning models optimized to run on STM32 microcontrollers. It provides a large collection of application-oriented models ready for re-training, scripts for easy retraining from user datasets, pre-trained models on reference datasets, and application code examples generated from user AI models. The project offers training scripts for transfer learning or training custom models from scratch. It includes performances on reference STM32 MCU and MPU for float and quantized models. The project is organized by application, providing step-by-step guides for training and deploying models.

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.

AIStore is a lightweight object storage system designed for AI applications. It is highly scalable, reliable, and easy to use. AIStore can be deployed on any commodity hardware, and it can be used to store and manage large datasets for deep learning and other AI applications.

Dataflow-oriented robotic application (dora-rs) is a framework that makes creation of robotic applications fast and simple. Building a robotic application can be summed up as bringing together hardwares, algorithms, and AI models, and make them communicate with each others. At dora-rs, we try to: make integration of hardware and software easy by supporting Python, C, C++, and also ROS2. make communication low latency by using zero-copy Arrow messages. dora-rs is still experimental and you might experience bugs, but we're working very hard to make it stable as possible.

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