It has been three years since the open-source machine learning platform TensorFlow was launched, and now the team is announcing new and ambitious plans for the AI library. The TensorFlow Developer Summit took place in Sunnyvale, CA this week, where the TensorFlow team announced the alpha version of Tensor 2.0, TensorFlow.js 1.0, TensorFlow Lite and … continue reading
Founded 10 years ago by a group of MIT scientists, Massachusetts-based biotech firm Ginkgo Bioworks has found great success in leveraging a number of open-source technologies to speed up and automate a wide variety of synthetic biology laboratory tasks. The organization’s main focus is the genetic engineering of compound-producing bacteria for a range of industrial … continue reading
Uber’s AI engineering team wants to make deep learning more accessible with the open-source release of Ludwig. The deep learning toolbox based on TensorFlow aims to give users the ability to train and test deep learning models without having to write any code. “Ludwig is unique in its ability to help make deep learning easier … continue reading
Across industries, machine learning is augmenting and in some cases taking the place of human decision-making. In recruiting, legal sentencing, loan approvals and even college admissions, algorithms now play a part in determining candidate selection. The science behind AI provides a more efficient approach to complex decision-making. However, for those without a PhD in mathematics … continue reading
Google has proposed a new approach to natural language understanding architectures beyond a fixed-length context. Transformer-XL aims to make long-range dependence more practical in neural networks by using attention models. According to the company, long-range dependence is the contextual ability humans have to parse information that depends on something they’d read much earlier in a … continue reading
GitHub has released machine learning data from its 2018 State of the Octoverse report. According to the report, the top programming languages for machine learning on GitHub include Python, C++, JavaScript, Java and C#. In addition, the team took a look at the top machine learning projects on GitHub, which included TensorFlow, SciKit-Learn, spaCy, Julia … continue reading
Microsoft has announced ML.NET 0.9, the latest version of the open-source, cross-platform machine learning framework for .NET. ML.NET enables developers to leverages existing tools to build custom AI into their applications by creating machine learning models. Models can be created targeting common tasks including classification, regression, clustering, ranking, recommendations, and anomaly detection. ProtonMail launches new … continue reading
As the end of 2018 approached, many artificial intelligence technologies like visual testing, chatbots and language recognition had matured to the point of ubiquity. Two years since SD Times’ “Year of AI,” the conversations around AI and machine learning have shifted further and further away from potential applications and surprising new uses of the tech. … continue reading
Apache Ignite 2.7 is adding new deep learning and extended languages support with the announcement of its TensorFlow integration and support for Node.js, Python and PHP. Ignite is a distributed database, caching and processing platform for transactional, analytical and streaming workloads. TensorFlow is an open-source software library for deep learning and machine learning tasks. The … continue reading
Continuous delivery provider Harness launched the 24×7 Service Guard for its continuous delivery-as-a-service platform today, a machine learning-powered tool for health checking of APM, monitoring and logging tools. According to the company, the tool provides a “safety net” for application services by automating code rollbacks and providing “total operational visibility” into how services run. ”For … continue reading
Knowledge is the foundation of intelligence— whether artificial intelligence or conventional human intellect. The understanding implicit in intelligence, its application towards business problems or personal ones, requires knowledge of these problems (and potential solutions) to effectively overcome them. The knowledge underpinning AI has traditionally come from two distinct methods: statistical reasoning, or machine learning, and … continue reading
Several months after announcing its AI Principles, Google has revealed a new Fairness module in its Machine Learning Crash Course. According to the company, the fairness module will demonstrate how existing tools and techniques can be used to make machine learning systems fairer and more inclusive. “The Fairness module was created to provide you with … continue reading
