Topic: machine learning
New open-source project introduces code-free deep learning approach
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
Can developers make AI’s “black box” transparent?
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
Transform-XL from Google makes long-term context in neural networks more practical
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
SD Times news digest: GitHub’s top machine learning languages, Ping’s API cybersecurity solution, and Lumigo’s serverless app funding
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
SD Times news digest: ML.NET 0.9, GDPR.eu, and Improbable’s response to Unity
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
Ethics at the fore of AI conversations
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 adds new integration with TensorFlow’s deep learning framework
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
Harness launches ML-powered health checks and rollbacks
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
Guest View: Knowledge graphs — The path to true AI
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
SD Times news digest: Google’s machine learning Fairness module, Orkus Access Governance Platform, and C3 7.8
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
How Axon prioritizes ethical design
While Google is amassing data on everyone, nudging them to do this or that or buy this or that, Axon is trying to make the world a safer place. Perhaps somewhat ironically, the company builds technology solutions and weapons for law enforcement, self-defense and the military. Axon — formerly known as TASER International — has … continue reading
How to achieve ethical design
Ethical design is at the very early stages when it comes to high-tech innovations. Other industries including healthcare, financial services, energy and others have had to ponder various ethical issues and over time they became highly regulated because the safety and security of their customers or the public at large are at stake. In the … continue reading
Get access to this and other exclusive articles for FREE!
There's no charge and it only takes a few seconds.
Sign up now!