In today's economy, creating intelligent customer experiences is a key differentiator for organizations looking to compete and gain a competitive advantage. Use of AI and especially Generative AI became more prevalent in the business world. We will discuss some of the work we did on creating an AI-Driven CX Platform that offers data management, Customer360 views, personalization and chatbots infused with Generative AI, and advanced security features. We will also discuss practical use cases and outcomes of our approach.

Target Audience: Managers, Decision Makers, Leaders
Prerequisites: None
Level: Advanced

Keeping up is the ultimate challenge for employees and companies within fields of massively fast-emerging trends shaping how to work and deliver. Learning and spreading expertise is also key to success while householding the knowledge of older technologies to maintain systems efficiently. The classic learning approach needs too much time to scale understanding and to adopt new technologies, especially remotely. It needed to be extended to a more self-defining and community-driven model with the ambition of being highly interactive and hands-on.

Target Audience: Engineering Manager, Agile Coaches, Employee Engagement, Senior & Executive Leaders
Prerequisites: None
Level: Advanced

Extended Abstract:
In our talk, we examine a case study on a three-year journey of creating, establishing and organically scaling a continuous learning community within GFK SE. The community started with two people and an idea – and is now an online event with hundreds of participants, from all over the globe!
But the talk doesn’t start with the solution! The story we would like to show you started in the darkness of two COVID-19 home offices occupying an MS Teams call. As was for many other people, the rash switch from mostly in-person, physically-centred collaboration to an environment that eradicated the physical elements of collaboration and made us all equally miserable, exposed a lot of practices that were not so visible before. So was the reality of learning in our company – people learned a lot from each other, but very localized, on a very small scale. Knowledge-sharing, workshops were done in groups of ca 5-10 people at most and were happening completely ad-hoc, all over the place, and as a result, topics would often be done multiple times even in the same physical location, with varying contents, recommendations and quality. With two words – it was all fragmented and invisible. On the other hand, as we went remote, it became really hard to do the same thing, so people, especially trainers, started complaining that it was so complex and time-consuming to do all this now via MS Teams. This is where the recognition started, that behind training content itself, there is so much more that impacts a successful or awful training experience.
Over the course of a few months, we gathered data, started a trainer community and came up with a lofty idea and a vision of what we wished to achieve.
When we started, we had three goals in mind:

1. Spread knowledge and skills efficiently to avoid reinventing the wheel
2. Contextualise learning – make not just the topic relevant, but take the examples, case studies and context for the sessions from our own “GFK kitchen”
3. Grow even more trainers and leaders – we ask trainers to come with a less experienced co-trainer who can in this way easily learn and practice how to be a trainer, gaining leadership skills

In addition to that, we also envisioned some benefits that would come from the unique synergies of the format – building trust, expanding people’s networks into other locations and work contexts through participating in a safe, learning-centred environment; breaking down functional silos more and more through continuous exposure into different areas and problem spaces; employee retention through an opportunity to recognize, grow and engage employees that were very interested in being trainers or mentors.
We were two people, and immediately everyone around us said it can’t be done. As we are in a talk about our success story, obviously we faced mountains of issues and our enthusiasm and idea almost died at one point, but we did it and are here to share with you all the nitty and gritty details, drama and recipes on how to make this happen!

This session will introduce embedding vectors and their use in artificial intelligence. It will illustrate how these constructs can be effectively utilized in enterprise AI solutions, specifically in conjunction with prompt engineering. Rainer Stropek will present practical demonstrations using Microsoft's Azure Cloud and OpenAI's ChatGPT 4 model, showcasing real-world application scenarios and potential business benefits. Attendees will gain insights into emerging AI trends and practices in enterprise contexts.

Target Audience: Architects, Developers, Data Scientists
Prerequisites: Basic knowledge about LLMs, ability to read source code
Level: Advanced

Extended Abstract:
This session aims to demystify the technical concepts of embedding vectors and their integration into the Artificial Intelligence (AI) world, with a specific focus on enterprise applications.
We provide an accessible introduction to embedding vectors – the mathematical constructs that translate complex data types into a format that machine learning algorithms can comprehend. Attendees will grasp the foundational principles of embeddings and their pivotal role in enhancing the capabilities of AI algorithms.
Next, we delve into the realm of prompt engineering. Here, we explore how the strategic crafting of prompts can steer AI models, such as OpenAI's ChatGPT 4, toward generating more precise and contextually accurate responses. We'll explain the process and strategies involved in prompt engineering, offering a roadmap for businesses to adopt these practices effectively.
Rainer Stropek will demonstrate these principles in a practical setting using Microsoft's Azure Cloud. We will walk through real-life scenarios, showing how enterprises can implement such technologies.
The session targets AI enthusiasts, software architects, developers, and data scientists. By the end of this session, participants will have gained a better understanding of these AI concepts, and how they can be harnessed.

Mehr Inhalte dieses Speakers? Schaut doch mal bei sigs.de vorbei: https://www.sigs.de/autor/rainer.stropek

"Σπεύδε βραδέως" in ancient Greek, or "festina lente" in Latin translates as "hurry slowly" an oxymoron saying to indicate the need for balancing deliberation and urgency.
In this talk we comment on the prevailing perceptions relating to speed of software development and how in a DevOps context what sometimes is perceived as fast from an individual's perspective has a deleterious effect on team performance while practices traditionally viewed by developers as cumbersome have in fact a positive effect on team performance and effectiveness.

Target Audience: Software Engineers and DevOps Practitioners
Prerequisites: None
Level: Advanced

Extended Abstract:
The talk draws on the experience of multiple projects but uses the team setup and 2020/2021 data of the NHS Covid19 app's backend services teams as a showcase for a team that managed to avoid neglecting subjects like peer reviews, documentation, testing etc. in a high pressure, high pace environment.