Open Source Artificial Intelligence

Open Source Artificial Intelligence
Open Source Artificial Intelligence Image link: https://commons.wikimedia.org/wiki/File:Artificial_intelligence_(33661764490).jpg
C O N T E N T S:

KEY TOPICS

  • Today in this article we are going to show some variety of useful open source artificial intelligence software that helps in building your AI projects.(More...)
  • Here is a list of 8 best open source AI technologies you can use to take your machine learning projects to the next level.(More...)
  • Apache SystemML is open-source artificial intelligence platform for machine learning ideal for big data.(More...)
  • CNTK or Microsoft Cognitive Toolkit, an open source toolkit for building artificial neural networks.(More...)
  • The recent rise in artificial intelligence (AI) and machine learning (ML), as Mark Russinovich, Microsoft Azure chief technology officer, recently said, is due to open-source AI and machine learning software.(More...)
  • This ML tool has been designed by the Apache Software Foundation and is built on a platform called Mahout Hadoop. Data analysts use this open source machine learning tool to carry out a critical and detailed analysis of Big Data.(More...)
  • "The progression of artificial intelligence and machine learning technologies calls for a shift in how we design and implement networks and services," said Adan Pope Chief Information Technology Officer at Ciena.(More...)
  • Open source software has largely been able to avoid or route around most patent problems, but with IoT and AI in the mix, we should expect a whole new round of patent "land grabs? that are both expensive and difficult to defend against.(More...)
  • On Thursday the two companies rolled out new tools that will make it easier for developers to use open-source artificial intelligence software.(More...)
  • Enterprises are accelerating their investment in areas such as Artificial Intelligence (AI) and Deep Learning (DL), as they look to turn data into competitive advantage.(More...)
  • Another advantage open source IoT creates is the ability to take advantage of publicly available AI tools like TensorFlow, Google?s deep learning AI framework.(More...)

POSSIBLY USEFUL

  • OpenNN (Open Neural Networks Library) was formerly known as Flood is based on the Ph.D. thesis of R. Lopez, "Neural Networks for Variational Problems in Engineering," at Technical University of Catalonia, 2008.(More...)
  • Open-source programs such as Core ML, Google TensorFlow, and ONNX are driving AI and ML. Now, The Linux Foundation has announced a new group at the Open Networking Summit in Los Angeles: LF Deep Learning Foundation, to further promote open-source AI and ML. (More...)
  • Amazon yesterday announced its ONNX-MXNet package to import Open Neural Network Exchange ( ONNX ) deep learning models into Apache MXNet, signifying the company is on-board with Facebook and Microsoft in efforts to open-source AI. (More...)
  • The term "open source" refers to a philosophy of sharing code, ideas, and innovations, enabling the knowledge base of an entire industry to grow more quickly than if that knowledge remained proprietary.(More...)

RANKED SELECTED SOURCES

KEY TOPICS

Today in this article we are going to show some variety of useful open source artificial intelligence software that helps in building your AI projects. [1] It also an Open Source Artificial Intelligence project that uses Raspberry Pi. [1] NuPIC is an open source artificial intelligence project based on a theory called Hierarchical Temporal Memory. [1]

Open Assistant, an evolving open source artificial intelligence agent able to interact in basic conversation and automate an increasing number of tasks. [2] Open source is also helping companies to keep pace with artificial intelligence (AI) as it evolves at a breakneck pace. [3] The open source tool comes as academic medical centers, hospitals, insurance companies and other healthcare organizations are gearing up for if not already embarking on artificial intelligence, cognitive computing and machine learning as well as precision medicine and the genomic sequencing that entails. [4] Google announced Monday an open source version of DeepVariant, the artificial intelligence tool that last year earned the highest accuracy rating at the precisionFDA's Truth Challenge. [4]

Here is a list of 8 best open source AI technologies you can use to take your machine learning projects to the next level. [5] Initially released in 2015, TensorFlow is an open source machine learning framework that is easy to use and deploy across a variety of platforms. [5] Mahout is an open source machine learning framework and offers three major features: programming environment and framework for building scalable algorithms, wide variety of premade algorithms for Scala + Apache Spark, H2O, Apache Flink and Samsara, a vector math experimentation environment with R-like syntax which works at scale. [1] Microsoft says that the open source framework is capable of "training deep learning algorithms to function like the human brain." [5] Initially released in 2015, Keras is an open source software library designed to simplify the creation of deep learning models. [5] Deeplearning4j means Deep Learning for Java is an open source deep learning library for Java virtual Machine (JVM). [1] Initially released in 2007, Theano is an open source Python library that allows you to easily fashion various machine learning models. [5] Initially released in 2007, scikit-learn is an open source library developed for machine learning. [5] The open source framework provides you with optimized flexibility and speed when handling machine learning projects--without causing unnecessary complexities in the process. [5] Caffe is a deep learning framework released under open source license and made with expression, speed, and modularity in mind. [1] The open source framework is written in C++ and comes with a Python interface. [5] The open source framework is suitable for production-grade scientific computing. [5] It comes under Facebook open source project and supported by Microsoft and Aws. [1] Facebook has released a set of extension modules as open source software. [6] OpenNN is an open source class library written in C++ programming language. [1] Scikit-learn is designed on three other open source projects--Matplotlib, NumPy, and SciPy--and it focuses on data mining and data analysis. [5] It has been released as open source under the Apache 2.0 license. [6]

Apache SystemML is open-source artificial intelligence platform for machine learning ideal for big data. [1] It is an open-source artificial intelligence tool from Microsoft. [1] It is artificial intelligence tool which is business oriented and help them to make a decision from data and enables the user to draw insights. [1] Artificial Intelligence (AI) is now in trend because people are looking for some sought of technology that makes their lives more easy and valuable. [1] The meteoric rise of artificial intelligence in the last decade has spurred a huge demand for AI and ML skills in today?s job market. [7] Artificial intelligence (AI) technologies are quickly transforming almost every sphere of our lives. [5]

To that end, we?re collaborating with Tech Mahindra to build an open source artificial intelligence (AI) platform, Acumos, hosted by The Linux Foundation that makes it easy to build, share and deploy AI applications. [8] "The Deep Learning Foundation is a significant achievement by the open source community to drive harmonization among tools and platforms in deep learning and artificial intelligence," said Mazin Gilbert, Vice President of Advanced Technology and Systems at AT&T. "This effort will enable an open marketplace of analytics and machine learning capabilities to help expedite adoption and deployments of DL solutions worldwide." [9] The LF Deep Learning Foundation, a Linux Foundation project, accelerates and sustains the growth of artificial intelligence, machine learning and deep learning open source projects. [9] SAN FRANCISCO, Aug. 8, 2018 /PRNewswire/ -- The LF Deep Learning Foundation, an umbrella organization of The Linux Foundation that supports and sustains open source innovation in artificial intelligence, machine learning, and deep learning, today announced five new members: Ciena, DiDi, Intel, Orange and Red Hat. [9]

All of these intelligent recommendations would not have been possible had Netflix not adopted an open source approach towards Artificial Intelligence and Machine Learning. [10]

CNTK or Microsoft Cognitive Toolkit, an open source toolkit for building artificial neural networks. [2] In 2015, Google gave its deep learning framework, TensorFlow, to the open source community, and it has since become a common tool for people creating deep learning training models for AI applications. [3] That's why Google is proposing an alternative: an open source reinforcement framework based on TensorFlow, its machine learning library. [11]

In 2016, it released the AI framework behind its Cortana digital assistant as open source software called the Microsoft Cognitive Toolkit. [3] Open source software also complicates the calls for ethics in AI development. [12] Companies have another incentive to open source their AI work: so outsiders can improve it. [13] Moving AI away from open source isn?t an ideal solution, either. [12] The ideal scenario is one in which open source, AI, and IoT create a cohesive whole that is more than the sum of its parts. [3] Stockfish AI, an open source chess engine currently ranked the highest in many computer chess rankings. [2] Theano, developed at the University of Montreal, is an open source project for machine learning using Python. [3] Torch, a framework that Facebook developed with others including Twitter, is an open source project that spawned a Python version called PyTorch. [3] Here we update the information and examine the trends since our previous post Top 20 Python Machine Learning Open Source Projects (Nov 2016). [14] The change in number of contributors is versus 2016 KDnuggets Post on Top 20 Python Machine Learning Open Source Projects. [14]

Orange3 is open source machine learning and data visualization for novice and expert. [14] It can also train models using custom data or public benchmark datasets with popular open source frameworks like Google's TensorFlow or Facebook's PyTorch. [15] Chainer is a Python-based, standalone open source framework for deep learning models. [14]

NuPIC, an open source implementation by Numenta of its cortical learning algorithm. [2] By relying on open source code bases, organizations like Apache and their associated communities, can accelerate the development of analytics tools on scale-out hardware architectures, enabling them to map and reduce the IoT's large data sets. [3] Scikit-learn is simple and efficient tools for data mining and data analysis, accessible to everybody, and reusable in various context, built on NumPy, SciPy, and matplotlib, open source, commercially usable - BSD license. [14] In this massively fragmented landscape, open source software can create a cohesive mechanism for data exchange. [3] TensorFlow? is an open source software library for high performance numerical computation. [16] Today, open source software lies at the heart of the most exciting technology developments. [3] Open source is a key factor in the development of this software. [3] "What open source did was reduce the barrier to entry, so that it?s no longer the IBMs and the Googles and the Facebooks, who have the deep pockets." [12] Governance frameworks such as this program make open source tools stronger and more shareable. [3] NuPIC is an open source project based on a theory of neocortex called Hierarchical Temporal Memory (HTM). [14] While much good has come from TensorFlow being open source, like potential cancer detection algorithms, FakeApp represents the dark side of open source. [12] The open source protocol and secure flow management provide the foundation for different vendors' equipment to exchange information in industrial IoT environments, speeding up the deployment of interoperable IoT infrastructures for customers. [3] Microsoft, once a harsh critic of the open source movement, has since warmed up to the concept. [3] Commonly accepted open source code bases make that more likely. [3] Learn more about how open source is changing the technology landscape. [3]

The recent rise in artificial intelligence (AI) and machine learning (ML), as Mark Russinovich, Microsoft Azure chief technology officer, recently said, is due to open-source AI and machine learning software. [17] Reinforcement learning an artificial intelligence (AI) technique that uses rewards (or punishments) to drive agents in the direction of specific goals trained the systems that defeated Alpha Go world champions and mastered Valve's Dota 2. [11] BrainR, an RPA solution that use artificial intelligence for learning how people are resolving task using their computers. [2]

An executive guide to artificial intelligence, from machine learning and general AI to neural networks. [17] CALO, a DARPA-funded, 25-institution effort to integrate many artificial intelligence approaches (natural language processing, speech recognition, machine vision, probabilistic logic, planning, reasoning, many forms of machine learning ) into an AI assistant that learns to help manage your office environment. [2] Microsoft, for its part, launched a new U.K-based unit focusing on AI for healthcare in September of 2017 after aligning with UPMC in a strategic partnership to advance artificial intelligence and released new products including HealthVault Insights, Microsoft Genomics, a chatbot and Project InnerEye for radiotherapy. [4] The Linux Foundation has launched the LF Deep Learning Foundation, an umbrella organization for open-source innovation in artificial intelligence, machine learning, and deep learning. [17] By closing the software, we?d lose a rare view into how these otherwise opaque tech companies develop their artificial intelligence algorithms. [12] OpenCog, a GPL-licensed framework for artificial intelligence written in C++, Python and Scheme. [2] Big technology companies want to make it easier to use artificial intelligence to attack real-world problems. [13] The following is a list of current and past, nonclassified notable artificial intelligence projects. [2] From Google Lens to the the company's new artificial intelligence chip here are the big announcements from Google I/O 2017's first day. [13] AIXI, Universal Artificial Intelligence developed by Marcus Hutter at IDSIA and ANU. [2] Cog, a robot developed by MIT to study theories of cognitive science and artificial intelligence, now discontinued. [2]

DALLAS - AT&T and Tech Mahindra are developing an open source artificial intelligence (AI) and machine learning platform that will be hosted within the Linux Foundation. [18] Development of a Laparoscopic Box Trainer Based on Open Source Hardware and Artificial Intelligence for Objective Assessment of Surgical Psychomoto. - PubMed - NCBI Warning: The NCBI web site requires JavaScript to function. more. [19]

This ML tool has been designed by the Apache Software Foundation and is built on a platform called Mahout Hadoop. Data analysts use this open source machine learning tool to carry out a critical and detailed analysis of Big Data. [20] Distributed Machine Learning Toolkit (DMTK): This is an open source ML tool that simplifies various tasks on Big Data. [20]

Caffe: This is an open source AI tool developed by the Berkeley Vision and Learning Center. [20] The initiative's Acumos AI Project is a platform and open source framework that makes it easy to build, share and deploy AI models. [9] The support of these new members will provide additional resources to the community to develop and expand open source AI, ML and DL projects, such as the Acumos AI Project, the foundation's comprehensive platform for AI model discovery, development and sharing. [9]

LF Deep Learning will also host a half day workshop at the upcoming Open Source Summit, August 28 in Vancouver, BC, which will provide a scope review of Acumos AI project, an AI full stack overview, overview of new projects and details of how to get involved. [9] "We believe that the LF Deep Learning Foundation and the Acumos project will accelerate the development of telecom use cases, in an open source environment for communication services, networks, security, and customer care," said Jamil Chawki, Director IT of Cloud Standards and Open Source at Orange. [9] "DiDi is excited to support the LF Deep Learning Foundation, which is helping fill an important gap in the AI space by providing a space for the open source community to innovate," said Wensong Zhang, Senior Vice President at DiDi. [9] Deeplearning4j: As the name suggests, Deeplearning4j is an open source Java AI tool specially designed for deep learning. [20] The Acumos platform is built on open source technologies and can federate across the various AI tools available today, enabling easy access for developers and businesses. [8] Apache SystemML: This is a flexible open source AI platform that focuses on Big Data and has been designed for complex mathematical problems. [20] Not only are many of the core elements of modern AI systems - such as Hadoop and SPARK open source software but vendors including Microsoft, Google and Amazon have open sourced their AI solutions. [21] It is primarily a Facebook open source project but is also endorsed by Microsoft and AWS. This open source ecosystem for deep learning was developed in 2017 when both the tech giants, Facebook and Microsoft, came together to create a system for switching ML frameworks. [20] There is vast potential to use these open source AI tools in healthcare, robotics, food and financial trading. [20] This open source AI tool is also being used for numerical computations by programmers. [20] This bird?s eye view of the top open source AI tools serves as a reminder of how AI has already impacted our lives. [20] OpenText?s AI enhanced analytics solution - OpenText? Magellan is an open source AI enhanced cognitive analytics platform based around SPARK. [21] It has been integrated with other open source AI platforms like Keta and TensorFlow. [20] Open source AI - especially when enhanced with advanced analytics - provides a platform for the development of new and innovative products that offer quality and accountability for AI-derived insight and decision-making with the sector. [21] In this AI based Science article, we explore How Netflix adopted an Open Source Model to improve their Entertainment Recommender Systems. [10] To summarize, we began by introducing Machine Learning to you, how Netflix evolved as an entertainment recommender, a hands-on comparison to Netflix's recommendation model and about Netflix Open Connect, followed by their Open Source Software Initiative. [10] PyTorch is an open source machine learning library for Python, used for applications such as natural language processing. [22] Apache Mahout: This is an open source machine learning tool under the Apache licence. [20] Founded in 2000, The Linux Foundation today provides tools, training and events to scale any open source project, which together deliver an economic impact not achievable by any one company. [9] Many of these challenges stem from the fact that open source projects entail large volumes of structured and unstructured data that are difficult to find, manage and analyze. [23] To train a machine, you essentially need to provide a relevant and sufficient amount of data to your algorithms so that they can continue to learn from the evolving data as new open source solutions become available and new vulnerabilities are discovered. [23] This open source deep learning platform helps in decision making after the deep analysis of data so that the user can draw useful insights. [20] At Synopsys, we are fortunate to have the world's largest database of open source software, supplemented by important pieces of meta data such as publicly known vulnerabilities, licenses, vendor information, and so on. [23] "We look forward to collaborating with the foundation and global open source and AI communities to develop useful solutions now and into the future." [9] We need to embrace an open source approach where communities of Life Science and technology experts can collaborate to develop, adapt and test new and existing AI solutions. [21] Open source is proving to be particularly attractive within the AI community. [21] Open source AI helps enormously here as the openness and transparency is inherent in the process - as is the necessity to document and audit the work. [21] Essentially, AI cannot fully automate the process of open source security or open source risk management. [23] I believe the reason that so many take the open source route is that the implementation of AI is only limited by imagination. [21] TensorFlow: This open source ML library was launched by Google Brain. [20] Open Neural Networks (OpenNN): This is an open source library written in the C++ language. [20] This open source library is used in the logistics and marketing verticals. [20] It contains a well-designed, open source Java library with a small number of basic classes that correspond to basic NN concepts. [22] Although open source is no more or less secure than other software, given the availability of source codes, detection and exploitation of security vulnerabilities in open source presents an easier target. [23] Automatically find relationships between various Open Source projects that are detected within your code. [23] Automatically map publicly known vulnerabilities to open source projects (which could be known differently within various open source and security communities). [23] All of the predictive results that we just saw hands-on, are powered by these unique open source projects listed on GitHub. [10] Launched in February 2003 (as Linux For You), the magazine aims to help techies avail the benefits of open source software and solutions. [22] Today, Netflix's Open Source Software initiative speaks of their commitment towards open source. [10] They have their very own Open Source Software Center ! Netflix's GitHub page clearly shows off their 139 repositories managed by 52 developers. [10] The concept of open source has been around in the software industry for many years. [21] Having two open source versions, this tool has found widespread application in predictive modelling, healthcare and fraud analysis. [20] The recent exploitation of vulnerability ( CVE -2017-5638 ) in Apache Struts reminds us of severe consequences that enterprises (as well individuals) face when they don't secure and manage the open source in their applications. [23] Oryx 2: This is an open source framework built on Spark and Apache Kafka. [20] TensorFlow was launched under the Apache 2.0 open source licence in 2015. [20] Our data scientists and security experts are utilizing these data to build the next generation of open source security solutions. [23] In that case, though, we spent years developing our own internal platform, called ECOMP, before releasing it into open source via The Linux Foundation. [8] Both the concept of open source and the Life Sciences communities using it are mature enough to be able to use the approach to gain the best results. [21] We?re getting the initial framework into open source as quickly as possible. [8] Netflix's very own content delivery network (CDN) is powered by open source. [10] Together with the worldwide open source community, it is solving the hardest technology problems by creating the largest shared technology investment in history. [9]

"The progression of artificial intelligence and machine learning technologies calls for a shift in how we design and implement networks and services," said Adan Pope Chief Information Technology Officer at Ciena. [9] Artificial Intelligence (AI) is revolutionizing the way we live, work and think. [23] Artificial Intelligence (AI) has the power to change everything. [21] Artificial intelligence or AI has now penetrated many aspects of our lives. [20] This article highlights ten tools and frameworks that feature on the "hot list? for artificial intelligence. [22] Machine learning is a branch of artificial intelligence that deals with the self-learning of computers. [20]

There is also a big open source community that supports machine learning and artificial intelligence (AI). [24] The Linux Foundation this week announced an agreement with AT&T and Tech Mahindra to launch the Acumos Project, a new platform for open source development of artificial intelligence. [25]

Open source software has largely been able to avoid or route around most patent problems, but with IoT and AI in the mix, we should expect a whole new round of patent "land grabs? that are both expensive and difficult to defend against. [26] Christopher Shallue, the lead Google engineer behind the exoplanet AI, announced in a blog post that the company was making the algorithm open source. [27] "We?re building a grass-roots movement in open source that brings the best compilers, technologists, and grand masters in data science together to build a software stack that rivals the likes of Google and giving it to enterprises and businesses that cannot attract that kind of talent," said Sri Ambati, H20.ai's chief executive. [28] Hunt for exoplanets with Kepler data and Google?s open source machine learning algorithm. [27] What is to be done about it all? While efforts to provide "open" code, algorithms and training data are laudable, the computation, competition, and accountability/audit concerns are unlikely to be answered with standard open source approaches. [26] As we have learned with Android OS phones, simply having access to the source code often doesn?t provide the necessary level of transparency, security, or accountability we demand from open source software, especially when so much of it happens on the server side of the equation. [26]

On Thursday the two companies rolled out new tools that will make it easier for developers to use open-source artificial intelligence software. [29] The new Gluon code will make it easier for developers to use open-source artificial intelligence frameworks, including those that Amazon and Microsoft support. [29] Artificial intelligence (AI) has become the center of today's biggest tech companies, including Google, Microsoft and Amazon, as well as social-networking giant Facebook, and even Apple. [30] K ansas City-based artificial intelligence startup Mycroft AI revealed Wednesday its newest product during Techcrunch Disrupt?s Product Showcase in San Francisco. [31] The system uses computer vision, augmented reality, and artificial intelligence algorithms, implemented into a Raspberry Pi board with Python programming language. [19] We constructed and evaluated an affordable laparoscopic trainer system using computer vision, augmented reality, and an artificial intelligence algorithm. [19] IBM is partnering with a firm specializing in machine learning in an effort to speed up artificial intelligence programs. [28] For the second time in recent months, Amazon and Microsoft are teaming up in artificial intelligence, with Google on the sidelines for now. [29]

STOCKHOLM, May 24, 2018 /PRNewswire/ -- FOSSID, the world's largest database for scanning open source code and snippets, today announced it is being awarded a grant of 2 Million SEK (US $250,000 ) to integrate Artificial Intelligence (AI) technologies into its database and code-scanning tools. [32] The project "will enable a community of AI-interested contributors to collaboratively work on an AI platform together under a proven governance structure for distributed open source software development," said Mike Dolan, vice president, strategic programs, at The Linux Foundation. [25] We are a top contributor to Apache Spark, which has emerged as the leading platform for big data/machine learning analytics and also the largest open source project in data processing. [33]

It's also a technology particularly suited for the open source development model when using permissive licensing, as companies can work together to build the basic AI or ML engines or frameworks and then add their own secret sauces in front of proprietary releases. [34] The official goal is to promote open source innovation in AI, machine learning, and deep learning. [34] At the heart of machine learning technology lies algorithms developed by the open source community that help analysts uncover patterns and insights from historical data. [24] TensorFlow is an open source software library that makes the use of data flow graphs for the purpose of numerical computation. [35] The open source model infrastructure is an essential underpinning of the DataRobot platform, which uses open-source algorithms for most of its models because they are some of the best available. [24] "There remains a concern regarding compromising the code in an AI, making it dangerous, which works against open source at the moment." [25] "Still, we are in the early years of AI, and right now, training -- not whether the code is open source -- is the limiting factor for rollouts," Enderle pointed out. [25] Intel is committed to delivering open source technology that drives analytics and AI momentum. [33] Two of the most popular open source frameworks are the Python scikit-learn and a number of R machine learning packages. [24] In the Concept to Clinic challenge, hundreds of data scientists and engineers from around the world came together to build open source tools to fight the world?s deadliest cancer. [36] The plan calls for the participants to build out the community of interested contributors over the next few months, Dolan said, and they expect to announce the availability of the open source code by early 2018. [25] Baidu will be contributing a version of its fault tolerable open source deep learning platform PaddlePaddle that integrates its Elastic Deep Learning feature for enhanced Kubernetes elastic scheduling. [34] The open source organization announced the launch of the Deep Learning Foundation. [34] It's often thought to be primarily linked to software, but there are open source communities for hardware, robotics, manufacturing, services, economics -- even an open source eyewear brand. [24] Opensource.com or Mybridge for Professionals for open source projects. [37] As an open source project, the impact from the contributions made during this challenge should extend well beyond the boundaries of one prototype or repository. [36] In an open source model infrastructure, some or all of a business or technology is built upon open source principles. [24] Imad Sousou is a corporate vice president and general manager of the Open Source Technology Center at Intel. [33]

Enterprises are accelerating their investment in areas such as Artificial Intelligence (AI) and Deep Learning (DL), as they look to turn data into competitive advantage. [33] The evolution of artificial intelligence from science fiction to reality needs a platform that can help make AI apps reusable and accessible to those beyond the companies that originally make them and lower the barrier to entry, according to AT&T. [25] AI2-THOR is an open-source project backed by the Allen Institute for Artificial Intelligence (AI2). [38] The Linux Foundation is throwing its hat into the artificial intelligence ring. [34]

These learning algorithms can be embedded within applications to provide automated, artificial intelligence (AI) features or be used in an AI platform to build brand new applications. [39] Artificial intelligence (AI) platforms provide users a tool kit to build intelligent applications. [39]

Artificial intelligence software is a very general space, with a number of different subcategories, including AI platforms, chatbots, deep learning, and machine learning. [39] Artificial intelligence (AI) is becoming a staple of all business software, whether users are aware of it or not. [39] Cyc is an artificial intelligence project that attempts to assemble a comprehensive ontology and knowledge base of everyday common sense knowledge, with the goal of enabling AI applications to perform human-like reasoning. [40] To solve these challenges, we are combining state-of-the-art artificial intelligence (AI) techniques with the rich expertise of data scientists, engineers, and other users. [41]

Another advantage open source IoT creates is the ability to take advantage of publicly available AI tools like TensorFlow, Google?s deep learning AI framework. [42] As part of this initiative, Uber AI Labs is excited to announce the open source release of our Pyro probabilistic programming language ! Pyro is a tool for deep probabilistic modeling, unifying the best of modern deep learning and Bayesian modeling. [41]

Since 2015 (when Google handed over TensorFlow to the open source software community), global IoT initiatives have relied on tools like these to create training models that prepare enterprise technologies for a virtually unlimited number of business applications and use cases. [42] By introducing an open source IoT software product, organizations give themselves an always-updated tool that helps accelerate internal data analysis efforts and more accurately maps a mobile technology program?s most serious information needs. This not only eliminates the time-consuming, non-essential tasks IoT management often creates, but refocuses enterprise IT resources to capturing only the most relevant, desirable data insights possible. [42] "We believe that FOSSID was chosen because of its vast data- and knowledge-base and the technology it already possesses to create the first open source scanner to automatically audit and identify code without human intervention," said Jon Aldama, VP Products at FOSSID. "FOSSID is poised to lead the integration of AI technologies for advancing open source software auditing and compliance." [32] The FOSSID AI For Open Source Auditing Project will combine the largest and highest performing knowledge base of open source on the market to dramatically cut costs in the software auditing process, reduce risks for tech companies and accelerate overall innovation. [32] While enterprise IoT software still has a long way to go before it can guarantee data security and privacy, open source development projects like Numberjack could very well be the path to a successfully managed future. [42] Since few organizations can ensure integration and operability with other mobile technologies currently, global IoT initiatives are increasingly using open source software to create more efficient connectivity and data communication paths. [42] Some companies are even using open source IoT to streamline data processing tasks, whether it works with one or 100 different cloud storage structures. [42] Parts of the project are released as OpenCyc, which provides an API, RDF endpoint, and data dump under an open source license. [40] While a lack of proprietary IoT software does pose risks that can be concerning to IoT asset management efforts, organizations are often willing to overlook those dangers for the promise of a continuously updated code base only open source software can deliver. [42] About FOSSID FOSSID is the world's largest database for scanning open source software licences and vulnerabilities. [32] Open source software has never been more valuable than it is today. [42] MOBI, the company I work for, has also hopped on the open source bandwagon to create technology-driven tools. [42] FOSSID's database management system and source code harvest techniques can store petabytes of code without any human interaction, allowing the company to build the biggest open source knowledge base in the industry and perform scans real time. [32]

POSSIBLY USEFUL

OpenNN (Open Neural Networks Library) was formerly known as Flood is based on the Ph.D. thesis of R. Lopez, "Neural Networks for Variational Problems in Engineering," at Technical University of Catalonia, 2008. [6] Developed by Google, TensorFlow is an open-source software library built for deep learning or artificial neural networks. [7] Neuroph's core classes correspond to basic neural network concepts like artificial neuron, neuron layer, neuron connections, weight, transfer function, input function, learning rule, etc. Neuroph supports common neural network architectures such as Multilayer perceptron with Backpropagation, Kohonen and Hopfield networks. [6] With its extensive range of libraries, you can build various applications in artificial neural networks, statistical data processing, image processing, and many others. [5] The tool can be used for numerical optimization, artificial neural networks, and visualization. [7]

OpenCog was originally based on the release in 2008 of the source code of the proprietary "Novamente Cognition Engine" (NCE) of Novamente LLC. The original NCE code is discussed in the PLN book (ref below). [6] Tensorflow is an open-source software library for numerical computation Intelligence. [1] It can be used for predictive modeling, risk and fraud analysis, insurance analytics, advertising technology, healthcare and customer intelligence. [1]

Open-source programs such as Core ML, Google TensorFlow, and ONNX are driving AI and ML. Now, The Linux Foundation has announced a new group at the Open Networking Summit in Los Angeles: LF Deep Learning Foundation, to further promote open-source AI and ML. [17] According to AT&T, "Our goal with open sourcing the Acumos platform is to make building and deploying AI applications as easy as creating a website." [17] In March, AT&T went beyond merely using open-source software: it released the code for its Open Network Automation Platform (ONAP) project, allowing other telecom companies to use it to manage their own network operations. [13] Open Mind Common Sense, a project based at the MIT Media Lab to build a large common sense knowledge base from online contributions. [2]

Google Brain Team members Mark DePristo and Ryan Poplin explained that by open sourcing DeepVariant, which was created with Google's Verily company, they hope to encourage its use and collaboration. [4]

The movement rapidly gathered force with the success of the World Wide Web and now drives a significant portion of the economy.Open source software has touched everything from word processing applications to databases and has recently enjoyed success in a major growth area: the Internet of Things (IoT). [3] Donovan says that when he started working for AT&T in 2008, employees were prohibited from even using open-source software, let alone releasing source code to the public. [13]

Google Brain A deep learning project part of Google X attempting to have intelligence similar or equal to human-level. [2] Veloxiti, formerly known as Applied Systems Intelligence Inc., now called Veloxiti Inc. developed under Dr. Norman D. Geddes post-DARPA Pilots Associate program. [2]

Artificial Linguistic Internet Computer Entity (A.L.I.C.E.), an award-winning natural language processing chatterbot. [2]

Amazon yesterday announced its ONNX-MXNet package to import Open Neural Network Exchange ( ONNX ) deep learning models into Apache MXNet, signifying the company is on-board with Facebook and Microsoft in efforts to open-source AI. [43] Earlier this year, Amazon, Facebook, and Microsoft partnered to help advance AI by creating ONNX (the Open Neural Network Exchange)--an open format to represent deep learning models. [44]

This specification and set of tools, supported by a community of partners, is the first step toward an open ecosystem that empowers AI developers to choose the right tools as their project evolves. [44]

The source code of a particular technology or solution is open for everyone to add to and improve. [21] "Our goal with open sourcing the Acumos platform is to make building and deploying AI applications as easy as creating a website," said Mazin Gilbert, vice president of Advanced Technology at AT&T Labs. [8] The Linux Foundation is the organization of choice for the world's top developers and companies to build ecosystems that accelerate open technology development and industry adoption. [9]

OpenNN (Open Neural Networks Library) was formerly known as Flood and is based on the Ph.D thesis of R. Lopez, called "Neural Networks for Variational Problems in Engineering?, at the Technical University of Catalonia, 2008. [22]

Skymind is its commercial support arm, bundling Deeplearning4j and other libraries such as TensorFlow and Keras in the Skymind Intelligence Layer (SKIL, Community Edition), which is a deep learning environment that gives developers an easy, fast way to train and deploy AI models. [22] The intelligence work of creating and testing hypotheses, developing algorithms and models, and taking informed decisions are all done by humans - and that?s not changing any time soon. [21]

OpenCog Prime is the architecture for robot and virtual embodied cognition, which defines a set of interacting components designed to give rise to human-equivalent artificial general intelligence (AGI) as an emergent phenomenon of the whole system. [22] Supporting ONNX could only benefit consumers, startups, and the quest for useful artificial general intelligence. [43]

Neuroph?s core classes correspond to basic neural network concepts like the artificial neuron, neuron layer, neuron connections, weight, transfer function, input function, learning rule, etc. Neuroph supports common neural network architectures such as multi-layer perceptron with Backpropagation, Kohonen and Hopfield networks. [22] Relating to a subject widely known as Artificial Neural Networks, there is also " Deep Learning ", which is a technique to perform Machine Learning that is inspired by Our Brain's Own Network of Neurons. [10]

OpenCog was originally based on the 2008 release of the source code of the proprietary Novamente Cognition Engine (NCE) of Novamente LLC. The original NCE code is discussed in the PLN book (reference given below). [22] Microsoft and Amazon are building their business, like Google, on AI. The task is daunting, to say the least, which is why they've teamed up under Gluon; to open it to other interested partners. [30]

Or consider the impact of open vs. closed Internet of Things ("IoT") on AI. As autonomous network agents proliferate within our phones, refrigerators, health care devices, cars, clothes, mattresses, and even children?s toys, these objects are quickly becoming one of the most powerful vectors for data used in AI systems. [26] Unlike most software and web technologies, where specific proprietary layers can be replaced when open versions are available, AI technologies are intensely integrated and complex and generally lack the discernible or distinct components necessary to implement such an approach as a long term solution. [26] Fundamentally, however, it will be incumbent on Mozilla and other open technology advocates to press on these issues, especially in America, China, Canada, Australia, and Europe, where the greatest investments in AI are happening. [26] As part of my Mozilla Tech Policy Fellowship, I?ll be looking into these questions and possible interventions to help fight to keep AI and IoT as parts of the open technology ecosystem. [26] The more AI systems learn about us, the harder it will be to understand what it is they know or to take that knowledge to a competing AI service if we want to switch to new more open devices. [26]

With new advances in artificial intelligence?--?particularly in the fields of machine learning and sensor technology?--?questions of "open" versus "closed" have arisen again. [26] ECOMP eventually morphed with the Linux Foundation's Open-O Project to form the current Open Network Automaton Platform (ONAP). [18] Rice provided more color by noting AT&T was using the lessons it learned in open sourcing its ECOMP framework into the Linux Foundation. [18] The use of open application programming interfaces (APIs) would allow for easy integration if desired. [18] "It provides a very similar experience to what you've come to expect from Google Home. but, it does it in an open way so you can build your own skills." [31] What is becoming quickly clear is that the traditional open strategies, such as permissive licensing and code/documentation publication, may not work as well or even at all. [26] Some preliminary work on the IoT aspects of these problems are underway at Mozilla?s Open IoT Studio. [26]

Whatever knowledge or intelligence is derived by AI-driven IoT from our data will be fiercely guarded by most ML/AI providers. [26] An artificial neural network (ANN) was trained to learn from experts and nonexperts' behavior for pattern cutting task, whereas the assessment of transferring task was performed using a preestablished threshold. [19]

The term "open source" refers to a philosophy of sharing code, ideas, and innovations, enabling the knowledge base of an entire industry to grow more quickly than if that knowledge remained proprietary. [24] Additional open enabling technologies include Analytics Zoo, an analytics + AI platform for Apache Spark and BigDL, with tools for end-to-end analytics and AI application development support. [33] Making it open to all can lead to an entire industry of AI software built around a machine learning ecosystem. [25] The new platform is part of a broader effort to open up opportunities for AI collaboration in the telecommunications, media and technology sectors. [25] AT&T is a Platinum Member of The Linux Foundation, Dolan noted, and the two organizations worked together on the Open Network Automation Platform launch last year. [25] "The Acumos Project community that we are helping get started will have the opportunity to work together under an open governance model at a neutral entity within the nonprofit Linux Foundation," he told LinuxInsider. [25] Open community involvement is a proven way to accelerate ideas and innovation. [33]

It is currently in preview - come join us as we continue to build ML.NET in the open. [45]

"AI can associate energy usage with weather forecasts and business calendars to more reliably shift between energy sources, like solar, wind and fossil fuel generation, on the fly, without over production or unexpected shortages." [25]

RANKED SELECTED SOURCES(45 source documents arranged by frequency of occurrence in the above report)

1. (20) The Top Twelve Open Source Artificial Intelligence Tools - open source for you

2. (16) How Open Source Software Drives IoT and AI

3. (14) 12 Opensource Tools for Artificial Intelligence (AI) |H2S Media

4. (14) List of artificial intelligence projects - Wikipedia

5. (13) LF Deep Learning Foundation Advances Open Source Artificial Intelligence With Major Membership Growth - MarketWatch

6. (12) Why open source should drive AI development in Life Sciences - OpenText Blogs

7. (12) How Will Artificial Intelligence Impact Open Technologies?

8. (12) Top 8 open source AI technologies in machine learning | Opensource.com

9. (11) New Collaborative Platform to Spur Open Source AI Development | Developers | LinuxInsider

10. (10) Artificial intelligence for open source risk management | Synopsys

11. (9) Ten Popular Tools and Frameworks for Artificial Intelligence

12. (9) Three ways open source software makes IoT stronger - IoT Agenda

13. (8) How Netflix Deploys Open Source AI to Reveal Your FavoriteS | Its FOSS

14. (7) Open Source Model Infrastructure | DataRobot Artificial Intelligence Wiki

15. (6) Top 20 Python AI and Machine Learning Open Source Projects

16. (6) Powering enterprise solutions for deep learning & artificial intelligence through open source | 01.org

17. (5) Google gave the world powerful open source AI tools, and the world made porn with them -- Quartz

18. (5) AT&T Joins the Open-Source Artificial-Intelligence Arms Race | WIRED

19. (5) Linux Foundation pushes open-source AI forward with the Deep Learning Foundation | ZDNet

20. (5) FOSSID Awarded Grant for Artificial Intelligence in Open Source Auditing by Sweden's Government Agency for Innovation

21. (5) Linux Foundation Spawns Child Foundation for AI | Data Center Knowledge

22. (5) 10 Open-Source Tools/Frameworks for Artificial Intelligence - DZone AI

23. (5) AT&T and Others Building Open Source AI Marketplace for Businesses

24. (4) AT&T Tackles Artificial Intelligence with Open Source Acumos Proj

25. (4) Development of a Laparoscopic Box Trainer Based on Open Source Hardware and Artificial Intelligence for Objective Assessment of Surgical Psychomoto. - PubMed - NCBI

26. (4) Best Artificial Intelligence (AI) Software in 2018 | G2 Crowd

27. (4) Google makes AI tool for precision medicine open source | Healthcare IT News

28. (3) Amazon and Microsoft are teaming up on A.I. without Google

29. (3) 11 Open-Source Frameworks for AI and Machine Learning Models - DZone AI

30. (2) Google releases open source reinforcement learning framework for training AI models | VentureBeat

31. (2) Google's Open Source AI Lets Anyone Hunt for Alien Planets At Home - Motherboard

32. (2) How new IBM partnership could speed AI | American Banker

33. (2) Microsoft and Amazon Have Partnered to Bring AI to the Masses

34. (2) Mycroft reveals newest open source AI product

35. (2) Concept to Clinic - Open Source ML/AI Challenge

36. (2) artificial intelligence - Open-source software for human brain simulation - Stack Overflow

37. (2) Uber Open Sources Pyro, a Deep Probabilistic Programming Language

38. (2) Amazon joins Facebook and Microsoft in support of open-source AI platform

39. (2) Artificial intelligence open source libraries : Open Source Conference | O?Reilly OSCON

40. (1) Intel AI Lab open-sources library for deep learning-driven NLP | VentureBeat

41. (1) TensorFlow

42. (1) Top 10 Python, AI and Machine Learning Open Source Projects

43. (1) Where can I find open source artificial intelligence code? - Quora

44. (1) GitHub - allenai/ai2thor: An open-source platform for Visual AI.

45. (1) .NET Machine Learning and AI

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