Blog posts

[ad_1] In our last blog post, we elaborated on some of the challenges that slow down the adoption of machine learning (ML) in the healthcare sector. We also pointed out that to generate sustainable value for both patients and physicians, it is necessary that all stakeholders are willing to go beyond the proof-of-concept stage and […]

[ad_1] NextGen meets NextGen Basel (May 5th, 2022) – Curix, a NextGen resilience AIOps solution proudly announces their strategic partnership with Swiss Digital Network (SND), Digital Architects Zurich (DAZ) and Machine Learning Architects Basel (MLAB), bringing together the powerful AI-based immune system for IT CuriX, with the in-depth method and integration knowledge of Swiss Digital

[ad_1] In this blog post we describe the concepts of monitoring and observability and explain how they can be applied to machine learning operations. We aim to give answers to questions such as “Why do I need observability?”, “What are some of the unique issues for observability imposed by data and model pipelines, in addition

[ad_1] Artificial intelligence (AI) and machine learning (ML) are key drivers of digital transformations in today’s organizations. Many companies want to benefit from AI and ML in hopes of turning data into value. As Venturebeat points out however, «Artificial intelligence (AI) in the lab is one thing; in the real world, it’s another. Many AI

[ad_1] As a great number of today’s organizations increasingly design and implement software using data and AI solutions, a growing community has emerged with heightened awareness of the challenges in transitioning a product from development to production. This shift emphasizes the need for models to not only function effectively, but to meet the specific needs

[ad_1] Before leveraging data and turning it into value, are you concerned with accessing the right data, transforming it, and setting up (ideally reliable, replicable, and secure) pipelines? At the same time, are you aiming to ensure data quality and smooth collaboration with other teams and stakeholders? Some stakeholders want to leverage data for business

[ad_1] Building an effective machine learning pipeline is an essential part of the end-to-end MLOps lifecycle, which follows up the concept of building reliable data pipelines by applying DataOps, as explained in our previous blog post. A pipeline for machine learning is a set of instructions that manages the data flow into and out of

[ad_1] With more than 20 years of field experience and working with the leading IT partners, Digital Architects Zurich developed a blueprint to support digital transformation. In this blog post, we will present this blueprint for the Digital Highway for reliable and continuous software delivery and operations. The challenge of successful Digital Transformation In order

[ad_1] According to Reuters, ChatGPT, the popular chatbot from OpenAI, is estimated to have reached 100 million monthly active users in January, just two months after launch, making it the fastest-growing consumer application in history. While this is phenomenal news, ChatGPT also crashed repeatedly, struggling with the usage load. OpenAI then announced a $20 monthly

[ad_1] If you let a software engineer come up with an ideal set-up for application operations, you will most likely hear about a concept that is very similar to that of Site Reliability Engineering (SRE) as Ben Treynor, VP of engineering at Google and founder of Google’s SRE team, describes.  The motivation to introduce and define such a role is based on conflicting goals in modern operating models. Two examples of such conflicts