AI Software is computer programs that possess and mimic near-human behaviour with the help of learning various data patterns and similar insights. It comes tagged with features like machine learning, speech and voice recognition, virtual assistant, deep learning capabilities and likewise.
It can set reminders, switch lights, controls AC, lock doors, place an order online etc. It is a free AI software for answering questions, developed by IBM for answering questions posed in natural language.
It can integrate artificial intelligence into an important business process. It helps declutter and arrange the unstructured data to extract meaningful information out of it.
It can be connected to multiple devices like cameras, music systems, and lights. Caffe is a deep learning framework released under open source license and made with expression, speed, and modularity in mind. The software is available as an open-source system. Caffe2 can be used for neural networks and also works with smartphones. The software can be a valuable asset to those working on AR and social network. Combining AR and the artificial world will yield new types of programs that can interact with the real world.
You can also take a demo of it using the link given below. Website Link: caffe. Tensorflow is an open-source software library for numerical computation Intelligence.
It performs the computation using the data flow graphs. Website Link : www. It is designed to run with enterprise application such as Hadoop and Apache Spark. Website Link: Deeplearning4j. H20 is an open-source deep learning platform. It is an artificial intelligence tool which is business-oriented and help them to make a decision from data and enables the user to draw insights.
There are two open-source versions of it: one is standard H2O and other is paid version Sparkling Water. It can be used for predictive modelling, risk and fraud analysis, insurance analytics, advertising technology, healthcare and customer intelligence. It can communicate with Hadoop via Java, but Python, R and Scala can also be used, including all supported packages. It easily integrates with Hadoop and includes a host of machine learning algorithms for classification, regression, decision trees, recommendation, clustering, topic modelling, feature transformations, model evaluation, ML pipeline construction, ML persistence and survival analysis.
Website Link : Spark. It is an open-source artificial intelligence tool from Microsoft. This toolkit is designed to use in big data applications.
It designed to run train AI systems faster. Numenta is tackling one of the most important scientific challenges of all time: reverse-engineering the neocortex. Scikit-learn is available under BSD license and can be used commercially free of charge. In , it was taken over by a non-profit foundation, which now runs the community, user support, and developer assistance.
Key features : Some of the key features of OpenCV include:. Editorial comments : Companies looking to leverage AI-based computer vision to develop facial recognition systems, augmented reality apps, and the like should consider OpenCV.
Its rich library of algorithms, coupled with learning support and complementary hardware, makes for a degree solution. Its primary use cases include customer intelligence and industry-specific analytics, including their predictive applications. The company developing and maintaining OpenNN is called Artelnics, known for its pathbreaking AI and big data research. Importantly, OpenNN does not specialize in computer vision or natural language processing, unlike some of the other open source software on this list.
You can leverage this open source AI software to build apps for customer segmentation, early healthcare diagnosis, predictive maintenance for equipment, and many more. Editorial comments : Companies, teams, and independent developers looking for a pure-play open source AI software library without any commercial bells and whistles should definitely consider OpenNN — particularly for predictive analytics use cases.
You can gain from its rich set of documentation , which also acts as a helpful tutorial to get started. Overview : PyTorch improves upon the foundational torch framework for ML that uses the Lua programming language.
Today, PyTorch has developed into a rich ecosystem that gives you all the tools necessary for accelerating AI development from research to production. Key features : Some of the key features of PyTorch include:. This lets you quickly download the software library from the relevant app marketplace and get started without leaving your current cloud-based development environment.
Editorial comments : PyTorch has the most expansive range of use cases among top open source AI software. Not only can you use it for computer vision, but you can also apply PyTorch for audio processing, NLP, language translation, and more. Overview : Rasa is among the most popular open source AI software used to build conversational interfaces. While the company mainly drives monetization from its enterprise product, it also has a powerful open source edition and a separate toolset for enhancing AI assistance.
You can use Rasa to build custom ML models or leverage its pre-built library of models written in TensorFlow. Rasa Enterprise bolts on to the open source platform, bringing SSO-based security, service level agreements, and dedicated support. Key features : Some of the key features of Rasa include:. Editorial comments : Mid-sized to large enterprises looking to build custom chatbots or ISVs eager to incorporate a conversational capability into their software offerings should definitely consider Rasa.
It started as an internal project by the Google Brain Team in , based on deep learning neural networks. As the company began using the technology in various ways, it decided to take TensorFlow in the open source direction from Today, several of the popular open source AI frameworks in the market are built on TensorFlow, which enjoys an active global community and widespread learning resources.
Key features : Some key features of TensorFlow include:. Another advantage is its sheer flexibility, as you can use TensorFlow in any language or production environment. Editorial comments : While TensorFlow is meant for more mature, expert-backed applications, it supports an impressive variety of use cases and can be used in a wide range of business scenarios. Overview : Tesseract is an optical character recognition OCR engine originally developed by Hewlett Packard as a proprietary technology in the s.
It is commonly known as one of the most accurate OCR engines available and was launched as an open source AI software with sponsorship from Google in Its primary implementation is meant for unstructured data processing and text from image extraction, executed entirely from a common line interface.
Its core purpose is to detect text in an unstructured visual environment and convert it into a human-readable language. Editorial comments : If you are looking for a sophisticated OCR engine that can work in challenging conditions and recognize languages such as Arabic or Hebrew, which follow right to left text, you cannot go wrong with Tesseract.
It is considered the de facto solution for text detection and language analysis. Users can opt for a GUI overlay if the command-line interface is not in sync with your requirements.
Ultimately, your choice of open source AI technology will come down to your unique software development need. Which use cases are you looking to solve using AI?
Would you require a GUI, or is a command-line interface sufficient? What is the underlying language for your code? The top ten technologies we listed promise a large developer community for support, regular enhancements and iterations, and are battle-tested in real-world scenarios. They are well suited for strengthening the foundations of your next AI project, bringing the collective intelligence of the global dev community and some of the most cutting-edge research labs in the world.
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