Best AI tools for< Run Neural Networks >

Luxonis is a platform that offers robotic vision solutions through high-resolution cameras with depth vision and on-chip machine learning capabilities. Their products include OAK Cameras and Modules, providing features like Stereo Depth Sensing, Computer Vision, Artificial Intelligence, and Cloud Management. Luxonis enables the development of computer vision products and companies by offering performant and affordable hardware solutions. The platform caters to enterprises and hobbyists, empowering them to easily build embedded vision systems.

CALA is a leading fashion platform that unifies design, development, production, and logistics into a single, digital platform. It provides tools and support to automate and optimize the supply chain from start to finish. CALA also offers a network of designers and suppliers, as well as AI-powered design tools to help generate moodboards, fresh ideas, and more.

Functionize is an AI Agentic Automation Platform for Enterprises that offers expert AI agents to handle business processes autonomously. The platform utilizes deep learning neural networks to deliver unparalleled performance across various enterprise applications. Functionize's AI agents run autonomously, self-heal workflows, and redefine efficiency and reliability in automation. The platform provides immediate value with pretrained automation, evolves with operational environments, and ensures seamless adaptability and precision in every task. Functionize helps mitigate risks, unlock gains, and support digital transformation for enterprises.

Cascadeur is a standalone 3D software that lets you create keyframe animation, as well as clean up and edit any imported ones. Thanks to its AI-assisted and physics tools you can dramatically speed up the animation process and get high quality results. It works with .FBX, .DAE and .USD files making it easy to integrate into any animation workflow.

Daily is a platform offering real-time voice, video, and AI solutions for developers. It provides ultra-low latency, open-source SDKs, and enterprise reliability since 2016. Daily collaborates with NVIDIA on Voice Agent Blueprint, offers Pipecat - a vendor-neutral open-source orchestration framework, Daily Bots for Pipecat Cloud deployment, and Daily Infrastructure for running real-time calls on WebRTC global infrastructure. The platform ensures the best video quality on every network, with a global mesh network, low latency, and enterprise-grade security features.

The Run Recommender is a web-based tool that helps runners find the perfect pair of running shoes. It uses a smart algorithm to suggest options based on your input, giving you a starting point in your search for the perfect pair. The Run Recommender is designed to be user-friendly and easy to use. Simply input your shoe width, age, weight, and other details, and the Run Recommender will generate a list of potential shoes that might suit your running style and body. You can also provide information about your running experience, distance, and frequency, and the Run Recommender will use this information to further refine its suggestions. Once you have a list of potential shoes, you can click on each shoe to learn more about it, including its features, benefits, and price. You can also search for the shoe on Amazon to find the best deals.

Practice Run AI is an online platform that offers AI-powered tools for various tasks. Users can utilize the application to practice and run AI algorithms without the need for complex setups or installations. The platform provides a user-friendly interface that allows individuals to experiment with AI models and enhance their understanding of artificial intelligence concepts. Practice Run AI aims to democratize AI education and make it accessible to a wider audience by simplifying the learning process and providing hands-on experience.

Dora is a no-code 3D animated website design platform that allows users to create stunning 3D and animated visuals without writing a single line of code. With Dora, designers, freelancers, and creative professionals can focus on what they do best: designing. The platform is tailored for professionals who prioritize design aesthetics without wanting to dive deep into the backend. Dora offers a variety of features, including a drag-and-connect constraint layout system, advanced animation capabilities, and pixel-perfect usability. With Dora, users can create responsive 3D and animated websites that translate seamlessly across devices.

Reflect is an AI-powered test automation tool that revolutionizes the way end-to-end tests are created, executed, and maintained. By leveraging Generative AI, Reflect eliminates the need for manual coding and provides a seamless testing experience. The tool offers features such as no-code test automation, visual testing, API testing, cross-browser testing, and more. Reflect aims to help companies increase software quality by accelerating testing processes and ensuring test adaptability over time.

The website is a comprehensive resource hub for learning and mastering end-to-end testing using the Playwright automation framework. It offers a blog with in-depth subjects on testing, a platform to ask AI-generated questions about Playwright, a collection of dev tools for QA engineers, job opportunities in QA and Automation, answered questions about Playwright, a Discord forum archive, tutorial videos, a browser extension for generating Playwright locators, a QA wiki with testing term definitions, and a quick access feature using Ctrl + k + 'Tools'.

Symphony is a platform that allows users to write programs using natural language. It enables users to interact with the system by talking to it, making programming more accessible and intuitive. Symphony aims to simplify the process of coding by bridging the gap between human language and programming languages.

aify is an AI-native application framework and runtime that allows users to build AI-native applications quickly and easily. With aify, users can create applications by simply writing a YAML file. The platform also offers a ready-to-use AI chatbot UI for seamless integration. Additionally, aify provides features such as Emoji express for searching emojis by semantics. The framework is open source under the MIT license, making it accessible to developers of all levels.

Lumora is an AI tool designed to help users efficiently manage, optimize, and test prompts for various AI platforms. It offers features such as prompt organization, enhancement, testing, and development. Lumora aims to improve prompt outcomes and streamline prompt management for teams, providing a user-friendly interface and a playground for experimentation. The tool also integrates with various AI models for text, image, and video generation, allowing users to optimize prompts for better results.

Dora is an AI-powered platform that enables users to create 3D animated websites without the need for coding. It caters to designers, freelancers, and creative professionals who seek to design visually captivating websites effortlessly. With Dora, users can craft mesmerizing 3D and animated visuals that are responsive and seamlessly translate across devices. The platform is designed for professionals who prioritize design aesthetics and offers a no-code experience for those transitioning from other design tools. Dora leverages advanced AI algorithms to generate, customize, and deploy stunning landing pages, revolutionizing the web design process.

Magnet is an AI coding assistant that helps product teams fix issues, share AI threads, and organize projects. It integrates with Linear, GitHub, and Notion, and provides auto-suggested files and code files for personalized and accurate AI recommendations. Magnet also offers prompt templates to help users get started and suggests quick fixes for bugs or enhancements.

Devath is the world's first AI-powered SmartHome platform that revolutionizes the way users interact with their smart devices. It eliminates the need for writing extensive lines of code by allowing users to simply give instructions to the AI for seamless device control. With features like splash resistance and responsive design, Devath offers a user-friendly experience for managing smart home functionalities. The platform also enables developers to preview and test their apps before submission, providing a 99% faster publishing process. Devath is continuously evolving with user feedback and aims to enhance the SmartHome experience through AI copilots and customizable features. With Devath, users can control their devices from the web and enjoy free unlimited access to the AI era of SmartHome.

One-Commerce is an AI-powered application designed to streamline the e-commerce listing process. It utilizes gemini technology to automatically generate detailed product descriptions, specifications, and SEO keywords from a single image. With its innovative approach, One-Commerce aims to simplify and enhance the online selling experience for e-commerce businesses.

Sessions is a cloud-based video conferencing and webinar platform that offers a range of features to help businesses run successful online meetings and events. With Sessions, users can create interactive agendas, share screens, record meetings, and host webinars with up to 1000 participants. Sessions also integrates with a variety of third-party tools, including Google Drive, Dropbox, and Slack, making it easy to collaborate with colleagues and share files. Additionally, Sessions offers a number of AI-powered features, such as automatic transcription and translation, to help users get the most out of their meetings.

Effy AI is a free performance management software for teams. It is AI-powered and backed by Run your first 360 review in 60 sec. Fast, and stress-free 360 feedback and performance review software build for teams. With Effy AI, you can collect reviews from different sources such as self, peer, manager, and subordinate evaluations. The platform goes even further by allowing employees to suggest particular peers and seek approval from their manager, giving them a voice in their reviews. Effy AI uses cutting-edge artificial intelligence to carefully process reviewers' answers and generate comprehensive reports for each employee based on the review responses.

Tely is an autonomous AI agent that helps businesses run B2B content marketing. It uses machine learning to understand your product, build domain expertise, run SEO optimization, and create a content plan. Tely can also personalize your content with infographics, code snippets, experts' quotes, and call to actions. With Tely, you can drive sales with expert-level content on autopilot, reduce customer acquisition cost, increase conversion rate, and save money on marketing expenses.

AI-resources is a repository containing links to various resources for learning Artificial Intelligence. It includes video lectures, courses, tutorials, and open-source libraries related to deep learning, reinforcement learning, machine learning, and more. The repository categorizes resources for beginners, average users, and advanced users/researchers, providing a comprehensive collection of materials to enhance knowledge and skills in AI.

Netsaur is a powerful machine learning library for Deno, offering a lightweight and easy-to-use neural network solution. It is blazingly fast and efficient, providing a simple API for creating and training neural networks. Netsaur can run on both CPU and GPU, making it suitable for serverless environments. With Netsaur, users can quickly build and deploy machine learning models for various applications with minimal dependencies. This library is perfect for both beginners and experienced machine learning practitioners.

Nesa is a tool that allows users to run on-prem AI for a fraction of the cost through a blind API. It provides blind privacy, zero latency on protected inference, wide model coverage, cost savings compared to cloud and on-prem AI, RAG support, and ChatGPT compatibility. Nesa achieves blind AI through Equivariant Encryption (EE), a new security technology that provides complete inference encryption with no additional latency. EE allows users to perform inference on neural networks without exposing the underlying data, preserving data privacy and security.

XLang™ is a cutting-edge language designed for AI and IoT applications, offering exceptional dynamic and high-performance capabilities. It excels in distributed computing and seamless integration with popular languages like C++, Python, and JavaScript. Notably efficient, running 3 to 5 times faster than Python in AI and deep learning contexts. Features optimized tensor computing architecture for constructing neural networks through tensor expressions. Automates tensor data flow graph generation and compilation for specific targets, enhancing GPU performance by 6 to 10 times in CUDA environments.

CIFAR-10 Airbench is a project offering fast and stable training baselines for CIFAR-10 dataset, facilitating machine learning research. It provides easily runnable PyTorch scripts for training neural networks with high accuracy levels. The methods used in this project aim to accelerate research on fundamental properties of deep learning. The project includes GPU-accelerated dataloader for custom experiments and trainings, and can be used for data selection and active learning experiments. The training methods provided are faster than standard ResNet training, offering improved performance for research projects.

NNtrainer is a software framework for training neural network models on devices with limited resources. It enables on-device fine-tuning of neural networks using user data for personalization. NNtrainer supports various machine learning algorithms and provides examples for tasks such as few-shot learning, ResNet, VGG, and product rating. It is optimized for embedded devices and utilizes CBLAS and CUBLAS for accelerated calculations. NNtrainer is open source and released under the Apache License version 2.0.

TokenFormer is a fully attention-based neural network architecture that leverages tokenized model parameters to enhance architectural flexibility. It aims to maximize the flexibility of neural networks by unifying token-token and token-parameter interactions through the attention mechanism. The architecture allows for incremental model scaling and has shown promising results in language modeling and visual modeling tasks. The codebase is clean, concise, easily readable, state-of-the-art, and relies on minimal dependencies.

The UvA Deep Learning Tutorials repository contains a series of Jupyter notebooks designed to help understand theoretical concepts from lectures by providing corresponding implementations. The notebooks cover topics such as optimization techniques, transformers, graph neural networks, and more. They aim to teach details of the PyTorch framework, including PyTorch Lightning, with alternative translations to JAX+Flax. The tutorials are integrated as official tutorials of PyTorch Lightning and are relevant for graded assignments and exams.

Neural Network Compression Framework (NNCF) provides a suite of post-training and training-time algorithms for optimizing inference of neural networks in OpenVINO™ with a minimal accuracy drop. It is designed to work with models from PyTorch, TorchFX, TensorFlow, ONNX, and OpenVINO™. NNCF offers samples demonstrating compression algorithms for various use cases and models, with the ability to add different compression algorithms easily. It supports GPU-accelerated layers, distributed training, and seamless combination of pruning, sparsity, and quantization algorithms. NNCF allows exporting compressed models to ONNX or TensorFlow formats for use with OpenVINO™ toolkit, and supports Accuracy-Aware model training pipelines via Adaptive Compression Level Training and Early Exit Training.

The Cheat-Sheet Collection for DevOps, Engineers, IT professionals, and more is a curated list of cheat sheets for various tools and technologies commonly used in the software development and IT industry. It includes cheat sheets for Nginx, Docker, Ansible, Python, Go (Golang), Git, Regular Expressions (Regex), PowerShell, VIM, Jenkins, CI/CD, Kubernetes, Linux, Redis, Slack, Puppet, Google Cloud Developer, AI, Neural Networks, Machine Learning, Deep Learning & Data Science, PostgreSQL, Ajax, AWS, Infrastructure as Code (IaC), System Design, and Cyber Security.

This repository serves as an educational resource for pharmaceutical and chemistry students to learn the basics of Deep Learning through a collection of Jupyter Notebooks. The content covers various topics such as Introduction to Jupyter, Python, Cheminformatics & RDKit, Linear Regression, Data Science, Linear Algebra, Neural Networks, PyTorch, Convolutional Neural Networks, Transfer Learning, Recurrent Neural Networks, Autoencoders, Graph Neural Networks, and Summary. The notebooks aim to provide theoretical concepts to understand neural networks through code completion, but instructors are encouraged to supplement with their own lectures. The work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

AI-For-Beginners is a comprehensive 12-week, 24-lesson curriculum designed by experts at Microsoft to introduce beginners to the world of Artificial Intelligence (AI). The curriculum covers various topics such as Symbolic AI, Neural Networks, Computer Vision, Natural Language Processing, Genetic Algorithms, and Multi-Agent Systems. It includes hands-on lessons, quizzes, and labs using popular frameworks like TensorFlow and PyTorch. The focus is on providing a foundational understanding of AI concepts and principles, making it an ideal starting point for individuals interested in AI.

PyTorch Forecasting is a PyTorch-based package for time series forecasting with state-of-the-art network architectures. It offers a high-level API for training networks on pandas data frames and utilizes PyTorch Lightning for scalable training on GPUs and CPUs. The package aims to simplify time series forecasting with neural networks by providing a flexible API for professionals and default settings for beginners. It includes a timeseries dataset class, base model class, multiple neural network architectures, multi-horizon timeseries metrics, and hyperparameter tuning with optuna. PyTorch Forecasting is built on pytorch-lightning for easy training on various hardware configurations.

At Nesa, privacy is a critical objective. Equivariant Encryption (EE) is a solution developed to perform inference on neural networks without exposing input and output data. EE integrates specialized transformations for neural networks, maintaining data privacy while ensuring inference operates correctly on encrypted inputs. It provides the same latency as plaintext inference with no slowdowns and offers strong security guarantees. EE avoids the computational costs of traditional Homomorphic Encryption (HE) by preserving non-linear neural functions. The tool is designed for modern neural architectures, ensuring accuracy, scalability, and compatibility with existing pipelines.

Deej-A.I. is an advanced machine learning project that aims to revolutionize music recommendation systems by using artificial intelligence to analyze and recommend songs based on their content and characteristics. The project involves scraping playlists from Spotify, creating embeddings of songs, training neural networks to analyze spectrograms, and generating recommendations based on similarities in music features. Deej-A.I. offers a unique approach to music curation, focusing on the 'what' rather than the 'how' of DJing, and providing users with personalized and creative music suggestions.

AIMET is a library that provides advanced model quantization and compression techniques for trained neural network models. It provides features that have been proven to improve run-time performance of deep learning neural network models with lower compute and memory requirements and minimal impact to task accuracy. AIMET is designed to work with PyTorch, TensorFlow and ONNX models. We also host the AIMET Model Zoo - a collection of popular neural network models optimized for 8-bit inference. We also provide recipes for users to quantize floating point models using AIMET.

This repository contains a student training series focusing on AI-driven science on supercomputers. It covers topics such as ALCF systems overview, AI on supercomputers, neural networks, LLMs, and parallel training techniques. The content is organized into subdirectories with prefixed indexes for easy navigation. The series aims to provide hands-on experience and knowledge in utilizing AI on supercomputers for scientific research.

The W3C Cognitive AI Community Group focuses on advancing Cognitive AI through collaboration on defining use cases, open source implementations, and application areas. The group aims to demonstrate the potential of Cognitive AI in various domains such as customer services, healthcare, cybersecurity, online learning, autonomous vehicles, manufacturing, and web search. They work on formal specifications for chunk data and rules, plausible knowledge notation, and neural networks for human-like AI. The group positions Cognitive AI as a combination of symbolic and statistical approaches inspired by human thought processes. They address research challenges including mimicry, emotional intelligence, natural language processing, and common sense reasoning. The long-term goal is to develop cognitive agents that are knowledgeable, creative, collaborative, empathic, and multilingual, capable of continual learning and self-awareness.

Trace is a new AutoDiff-like tool for training AI systems end-to-end with general feedback. It generalizes the back-propagation algorithm by capturing and propagating an AI system's execution trace. Implemented as a PyTorch-like Python library, users can write Python code directly and use Trace primitives to optimize certain parts, similar to training neural networks.

SciMLBenchmarks.jl holds webpages, pdfs, and notebooks showing the benchmarks for the SciML Scientific Machine Learning Software ecosystem, including: * Benchmarks of equation solver implementations * Speed and robustness comparisons of methods for parameter estimation / inverse problems * Training universal differential equations (and subsets like neural ODEs) * Training of physics-informed neural networks (PINNs) * Surrogate comparisons, including radial basis functions, neural operators (DeepONets, Fourier Neural Operators), and more The SciML Bench suite is made to be a comprehensive open source benchmark from the ground up, covering the methods of computational science and scientific computing all the way to AI for science.

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