adesso Blog

The first two parts of my blog post dealt with the general opportunities and challenges of AI, specific applications of generative AI and AI in the various phases of the customer journey. In the third and final part, I take a closer look at the future developments of AI in the insurance sector.

Microservices are a prevailing trend in software architecture that breaks down large systems into independent units. They offer advantages, but are not always necessary. Alternatively, a modularised monolith can be useful, especially if the boundaries between microservices are fluid. In this blog post, I will discuss modularisation concepts in the Java ecosystem, with a focus on Spring Modulith.

The energy transition in Germany and Europe poses major challenges for the electricity grid, as renewable energies are dependent on the weather and lead to fluctuations in feed-in. In this blog post, I examine whether Bitcoin mining can help stabilise the grid as a flexible load by using times of energy surplus and shutting down quickly when needed.

This blog post was written as part of the GenAI Solutioning Unit. In it, we show that there are various ways to specialise a language model on a domain-specific basis. This is important for advising our customers and is aimed at anyone interested in GenAI.

In modern data processing, companies are faced with the challenge of choosing the right database technology for their specific requirements. PostgreSQL and Databricks are two widely used solutions, each with their own strengths. In this blog post, I will highlight the differences between PostgreSQL and Databricks, analyse their respective advantages and disadvantages and give specific use cases that justify a switch to Databricks.

Demographic change is challenging the German care system. Politicians and associations are looking for funding models and technological progress is offering new care concepts. The aim is to use apps and wearables to improve the independence and quality of life of people in need of care and relieve the burden on relatives. We show how this works in our blog post.

In the manufacturing industry, there is often talk of digital transformation. This is intended to pave the way for Industry 4.0. The opportunities and potential benefits of digitalisation are well known. The question is: why is it still only making slow progress? I get to the bottom of this question in my blog post.

It goes without saying for every driver that if a strange noise occurs, the reason must be identified. The standard procedure is to go to the garage to identify the cause of the fault. Although this costs a certain fee, the damage to be expected without an inspection may far exceed such a financial outlay. This is a typical instance of predictive maintenance, a sub-area of predictive analytics: preventing damage before it has a full impact. In industry, the principle is the same, only on a larger scale where thousands - if not millions - of devices produce immense amounts of data.

Many companies are just starting out with their first prototypes in the area of large language models. It is a good idea to deal with regulatory and security issues at an early stage. What needs to be considered from the outset, what needs to be done during the course of the project and how can operations be set up securely and in compliance with regulations? Even if not all the details have been clarified in the regulatory area, for example, I would like to address these questions in this blog post.