adesso Blog

On 13 May 2024, Open AI published the new Large Language Model GPT-4o. The ‘o’ stands for ‘omni’ and already points to one of the model's great strengths, namely the intelligent interaction of text, audio and images. In my blog post, I show what these new possibilities mean for Gen AI use cases in the financial sector.

This is the first part of my three-part blog post on the role of artificial intelligence (AI) in the insurance industry. In this first part, I focus on the general opportunities and challenges of AI as well as specific applications of generative AI. The focus is on marketing and sales.

Everyone makes GenAI and that's right! But despite the hype surrounding GenAI, the fundamental field of machine learning (ML) must not be forgotten. Because there is still a lot of untapped potential for companies here. Few people understand what artificial intelligence (AI) actually includes and how to use it optimally for their own business. We have gained a lot of experience as trainers and based on this we have created suitable training offers.

AI is indispensable for companies' customer relationships in the digital world. It automates processes, analyses data intelligently and adapts content in real time. This enables customer needs to be better met, customer behaviour to be analysed in detail and all touchpoints of the customer journey to be optimised. I present further insights and solutions in my blog post.

Künstliche Intelligenz ist unaufhaltsam auf dem Vormarsch. Mit der Generativen Künstlichen Intelligenz (kurz GenAI) hat das Thema eine neue Dimension erreicht, die tiefgreifende Veränderungen mit sich bringt - auch in der Energiewirtschaft. Über welche Marktrollen sich die Anwendungsfelder erstrecken und wie der Einstieg gelingt, zeige ich in diesem Blog-Beitrag.

Microsoft Copilot increases your productivity and optimises your processes. But beware of data chaos! In this blog post, we show you the most important governance aspects when introducing Microsoft 365 Copilot and other AI services based on large language models.

The world of artificial intelligence (AI) has evolved rapidly with the introduction of generative models such as ChatGPT. This blog post takes a look at use cases for generative AI and considers the future possibilities of this technology.

Large Language Models (LLMs), above all ChatGPT, have taken all areas of computer science by storm over the past year. As they are trained on a broad database, LLMs are fundamentally application-agnostic. Despite their extensive knowledge, however, they have gaps, particularly in highly specialised applications, which in the worst case can only appear to be compensated for by hallucinations. To reduce this risk, "Retrieval Augmented Generation" (RAG) has been established.

Generative AI has been everyone’s mind since ChatGPT came on to the scene. But what exactly does this term mean and how is generative AI different from the well-established concepts of machine and deep learning? This blog post takes a general look at AI technologies and highlights the differences that make generative AI so intriguing and promising in an ever-changing world.