In this post, Nathaniel Reynolds, Associate Director of Informatics Architecture & DevOps at Moderna Therapeutics, talks about service mesh, removing limitations with open source, and how AI helps developers do more. No one can predict the future, but here’s a safe bet: in the next five to ten years, we aren’t going to have fewer applications. We’re going to have more. And that means connectivity requirements are going to get bigger and bigger over time.

By Victor Sonck, Developer Advocate at ClearML Reporting your findings to colleagues, managers, or even your future self is a core component of any modern ML workflow. Having one central place where you can easily build a summary of your work makes it that much easier. That’s where ClearML Reports come in.

By Vidushi Meel, Freelance Technical Writer What is MLOps? Learn what Machine Learning Operations are, how it works, why it’s needed, the advantages of using MLOps, and why MLOps matters in this complete guide.

GitHub Actions is a powerful continuous integration and continuous delivery (CI/CD) platform that allows developers to automate build, test, and deployment pipelines. Workflows automatically build and test code whenever an event occurs, such as a pull request or a deployment of merged pull requests to production. Best of all, you can use it without leaving the comfort of your own repository!

As artificial intelligence (AI) has shifted from a movie concept to a real-world phenomenon, it’s become clear that AI will change how we do business. Smart factories, connected shop floors, and supply chain automation are already commonplace, yet manufacturing and shipping are not the only sectors adopting AI and machine learning (ML). AI is also revolutionizing software development in surprising ways.

Contrary to what we see in the movies, artificial intelligence (AI) today is not capable of doing and learning everything on its own. It greatly and principally depends on the feedback that it gets from people. “Human in the Loop” (HITL) refers to the role of human feedback in the AI training process. Before getting into the concept of humans in the loop, let us understand the need for accurately annotated data and get the annotated data at speed.

As the utilization of machine learning and MLOps (machine learning operations) continues to gain traction within organizations, it is imperative to stay abreast of the latest advancements and developments in the field.

With inflation and other disruptive market dynamics massively impacting consumer behavior, is it any surprise that personalization tops the list of strategic actions for CMOs in 2023? Yep, people tend to stick around when digital products and experiences fulfill their personal needs quickly and accurately. And topping the list of powerful tools for personalization? Machine learning and AI, of course, from product recommendations to targeted offers based on digital customer and behavioral data.

8 years ago, when I founded Iguazio together with my co-founders Yaron Haviv, Yaron Segev & Orit Nissan-Messing, I never thought I would be making this announcement on our company blog: McKinsey acquired Iguazio! When we first embarked on this journey, we realized that while AI has the ability to transform any industry - from banking to retail to manufacturing - in reality most data science projects fail.