While artificial intelligence (AI) and machine learning (ML) are emerging technologies, we know they can help an organization parse large data sets and glean actionable insights. But do AI-infused processes actually make a difference in organizations that employ DevOps? The answer is explored in a recent survey by Tricentis. Working in partnership with Techstrong Group, […]
Iterative Adds Registry to GitOps Portfolio for ML Models
Iterative added a registry for machine learning models to its portfolio of Git-based tools for infusing artificial intelligence into applications. Iterative CEO Dmitry Petrov said the Iterative Studio Model Registry is intended to make it easier for application development teams to track which models are being used as the number of applications infused with AI […]
VW CEO Fired for Dev Fails | Fiber Shortage Hits | Google Fires Blake Lemoine
In this week’s The Long View: Herbert Diess is out at VW because software is hard (yo), fiber optic cable is hard to find, and the guy who said LaMDA was sentient is dumped by Google.
Google FLoC is Dead | Meta AI Supercomputer Lives | ARM Deal is Dead
In this week’s The Long View: Google’s FLoC proposal is dead, Meta/Facebook is buying RSC—a huge AI supercomputer, and Arm “will IPO” instead of selling to Nvidia.
Driving Software Delivery Automation With AI/ML
What if we could use an artificial intelligence (AI) engine to predict the next lines of software code to build? What if machine learning (ML) could trigger the creation of automated test cases to validate our solutions? Automation has been a focus for the information and communications technology (ICT) industry for years, and there are […]
DevSecOps Implementation: Intrusion Detection
Originally, this series was just going to be four articles on the DevSec side of DevSecOps. There are many reasons for this, but primarily because that side is cleaner. The other reason is that these topics are beyond the work we were doing at Accelerated Strategies Group. But we’ve had a number of requests to […]
A Buyer’s Guide to AI and Machine Learning
B2B software sales and marketing teams love hearing the term “artificial intelligence” (AI). AI has a smoke and mirrors effect. It sounds impressive. But, when we say “AI is doing this,” our buyers often know so little about AI that they don’t ask the hard questions. In industries like the DevTools space, it is crucial […]
DevOps Chat: Increasing Delivery Velocity, with Launchable
Jenkins founder Kohsuke Kawaguchi (KK) and respected DevOps veteran Harpreet Singh have launched a new company called Launchable. Launchable aims to help you improve your delivery velocity by prioritizing and applying some ML and intelligence to testing. There is still much work to be done but with these two industry luminaries behind it, the expectations […]
Five Challenges of Machine Learning DevOps
As organizations add machine learning (ML) to their workflows, it’s tempting to try to squeeze model creation and deployment into the existing software development lifecycle (SDLC). However, ML is fundamentally different than traditional applications, and it’s important to account for that in a new, unique process called the machine learning development lifecycle. We have identified […]
Aspects of Machine Learning on the Edge
Machine learning (ML) is hard. Making it work within the confined environment of an embedded device can easily become a quagmire unless we consider, and frequently revisit, the design and deployment aspects crucially affected by ML requirements. A bit of upfront planning makes the difference between project success and failure. For this article, our focus […]