Kong announced the launch of the latest version of Kong AI Gateway, which introduces new features to provide the AI security and governance guardrails needed to make GenAI and Agentic AI production-ready.
Amazon Web Services and Microsoft Corp. announced a new deep learning library, called Gluon, that allows developers of all skill levels to prototype, build, train and deploy sophisticated machine learning models for the cloud, devices at the edge and mobile apps.
The Gluon interface currently works with Apache MXNet and will support Microsoft Cognitive Toolkit (CNTK) in an upcoming release. With the Gluon interface, developers can build machine learning models using a simple Python API and a range of prebuilt, optimized neural network components. This makes it easier for developers of all skill levels to build neural networks using simple, concise code, without sacrificing performance. AWS and Microsoft published Gluon’s reference specification so other deep learning engines can be integrated with the interface.
Developers build neural networks using three components: training data, a model and an algorithm. The algorithm trains the model to understand patterns in the data. Because the volume of data is large and the models and algorithms are complex, training a model often takes days or even weeks. Deep learning engines like Apache MXNet, Microsoft Cognitive Toolkit and TensorFlow have emerged to help optimize and speed the training process. However, these engines require developers to define the models and algorithms up front using lengthy, complex code that is difficult to change. Other deep learning tools make model-building easier, but this simplicity can come at the cost of slower training performance.
The Gluon interface gives developers the best of both worlds — a concise, easy-to-understand programming interface that enables developers to quickly prototype and experiment with neural network models, and a training method that has minimal impact on the speed of the underlying engine. Developers can use the Gluon interface to create neural networks on the fly, and to change their size and shape dynamically. In addition, because Gluon interface brings together the training algorithm and the neural network model, developers can perform model training one step at a time. This means it is much easier to debug, update and reuse neural networks.
“The potential of machine learning can only be realized if it is accessible to all developers. Today’s reality is that building and training machine learning models require a great deal of heavy lifting and specialized expertise,” said Swami Sivasubramanian, VP of Amazon AI. “We created the Gluon interface so building neural networks and training models can be as easy as building an app. We look forward to our collaboration with Microsoft on continuing to evolve the Gluon interface for developers interested in making machine learning easier to use.”
“We believe it is important for the industry to work together and pool resources to build technology that benefits the broader community,” said Eric Boyd, Corporate VP of Microsoft AI and Research. “This is why Microsoft has collaborated with AWS to create the Gluon interface and enable an open AI ecosystem where developers have freedom of choice. Machine learning has the ability to transform the way we work, interact and communicate. To make this happen we need to put the right tools in the right hands, and the Gluon interface is a step in this direction.”
The Gluon interface is open source and available today in Apache MXNet 0.11, with support for CNTK in an upcoming release.
Industry News
Traefik Labs announced significant enhancements to its AI Gateway platform along with new developer tools designed to streamline enterprise AI adoption and API development.
Zencoder released its next-generation AI coding and unit testing agents, designed to accelerate software development for professional engineers.
Windsurf (formerly Codeium) and Netlify announced a new technology partnership that brings seamless, one-click deployment directly into the developer's integrated development environment (IDE.)
The Cloud Native Computing Foundation® (CNCF®), which builds sustainable ecosystems for cloud native software, is making significant updates to its certification offerings.
The Cloud Native Computing Foundation® (CNCF®), which builds sustainable ecosystems for cloud native software, announced the Golden Kubestronaut program, a distinguished recognition for professionals who have demonstrated the highest level of expertise in Kubernetes, cloud native technologies, and Linux administration.
Red Hat announced new capabilities and enhancements for Red Hat Developer Hub, Red Hat’s enterprise-grade internal developer portal based on the Backstage project.
Platform9 announced that Private Cloud Director Community Edition is generally available.
Sonatype expanded support for software development in Rust via the Cargo registry to the entire Sonatype product suite.
CloudBolt Software announced its acquisition of StormForge, a provider of machine learning-powered Kubernetes resource optimization.
Mirantis announced the k0rdent Application Catalog – with 19 validated infrastructure and software integrations that empower platform engineers to accelerate the delivery of cloud-native and AI workloads wherever the\y need to be deployed.
Traefik Labs announced its Kubernetes-native API Management product suite is now available on the Oracle Cloud Marketplace.
webAI and MacStadium(link is external) announced a strategic partnership that will revolutionize the deployment of large-scale artificial intelligence models using Apple's cutting-edge silicon technology.
Development work on the Linux kernel — the core software that underpins the open source Linux operating system — has a new infrastructure partner in Akamai. The company's cloud computing service and content delivery network (CDN) will support kernel.org, the main distribution system for Linux kernel source code and the primary coordination vehicle for its global developer network.