In today’s data age, getting data analytics right is more essential than ever. A robust data analytics implementation enables businesses to hit key performance metrics, build data and AI-driven customer […]
MLOps Vs. DevOps: What’s the Difference?
Machine learning operations, or MLOps for short, is a key aspect of machine learning (ML) engineering that focuses on simplifying and accelerating the process of delivering ML models to production […]
Top 3 Requirements for Next-Gen ML Tools
As the machine learning market matures, new tools are evolving that better match data science and machine learning teams’ needs. Vendors, both open source and private, have been quick to […]
Positioning ML Devs and Teams for Success
Intelligent applications are (by their very nature) complex. While conventional software basically consists of one thing (code), intelligent software involves code, models and data. As previously discussed, three distinct fields—DevOps, […]
What is MLOps? DataOps? And Why do They Matter?
Let’s look at three distinct disciplines—DevOps, MLOps and DataOps. In 2011, Marc Andreessen famously proclaimed that software was “eating the world.” A little more than a decade later, it’s all but […]
Iterative Adds Experiment Versioning to MLOps Platform
Iterative today added an experiment versioning capability to an open source platform for managing machine learning operations (MLOps) using GitOps workflows. Dmitry Petrov, Iterative CEO, said the latest version of […]
Oracle Adds AI Services to Cloud Portfolio
Oracle today unfurled Oracle Cloud Infrastructure (OCI) AI services, a collection of services that make it easier for developers to use application programming interfaces (APIs) to invoke a wide range […]
Mona Allies with New Relic to Converge MLOps and DevOps
New Relic and Mona, a provider of a platform for monitoring the models used to provide artificial intelligence (AI), announced today they have formed an alliance to help bridge the […]
Learn a Bit About AI
Every once in a while, a trend becomes broad enough that I feel the need to offer career advice. This year it will be simple: Know enough about AI/ML to […]
Why You Should Use GitOps to Experiment With AI
As the pace at which artificial intelligence (AI) models are being constructed and inevitably updated starts to increase, it’s becoming more apparent that the pace at which data science teams […]
