While AI systems differ in some points from "traditional" systems, testing them does not have to be more difficult - knowing the right questions to ask will go a long way. In this talk we will:

• Arm you with a checklist of questions to ask when preparing to test an AI system
• Show you that testers and data scientist have common ground when testing AI systems

Keep calm and test on - AI systems are not that different from "normal" systems.

Target Audience: Testers, Data Scientists, Developers,…

Security engineering from TARA and security requirements to security testing demand mechanisms to generate, verify, and connect the resulting work products. Traditional methods need lots of manual work and yet show inconsistencies and imbalanced tests. Generative AI allows novel methods with semi-automatic cyber security requirements engineering, traceability, and testing. In this industry presentation, we show two promising approaches with NLP and transformers and how to embed them into an…

The introduction of ChatGPT, CoPilot X brings in a lot of hype over developer experiences, especially documentation. But are we ready to chat with our documentation, instead of reading, using these tools? How can we, as maintainers, leverage these tools to offer a better experience in documentation for developers as our users? Join my talk and let's find out.

Target Audience: Engineers, Developers
Prerequisites: Programming
Level: Advanced

Discover the transformative power of GenAI in software testing. This lecture showcases a powerful GenAI-powered test framework that enhances testing efficiency. Learn how GenAI analyzes applications to generate automated test cases, uncover hidden defects with generative AI's random exploratory tests. Experience AI-powered peer reviewers for code analysis and quality evaluations. Explore Smart Report AI, providing comprehensive analysis and insights into test execution, results, and defects.…

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…

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…

In the evolving AI landscape, the EU AI Act introduces new standards for assuring high-risk AI systems. This presentation will explore the tester's role in navigating these standards, drawing from the latest research and from our experiences with an Automatic Employment Decision System, a high-risk AI. We'll discuss emerging methodologies, conformity assessments, and post-deployment monitoring, offering insights and practical guidance for aligning AI systems with the Act's requirements.

Target…

One of the fundamental challenges for machine learning (ML) teams is data quality, or more accurately the lack of data quality. Your ML solution is only as good as the data that you train it on, and therein lies the rub: Is your data of sufficient quality to train a trustworthy system? If not, can you improve your data so that it is? You need a collection of data quality “best practices”, but what is “best” depends on the context of the problem that you face. Which of the myriad of strategies…

Expanding horizons has many facets. It means taking advantage of new opportunities that arise from technical progress, such as Large Language Models, or societal challenges like Sustainability. Expanding horizons also means taking responsibility. AI and data analytics have a direct impact on our future life, good and bad. Expanding horizons also means reflection on existing practice. We have perhaps forgotten the benefits of structured monoliths, or have sometimes overdone it with agility, which…

During the talk, we'll dive into the historical context of Generative AI and examine their challenges. From legal compliance to fairness, transparency, security, and accountability, we'll discuss strategies for implementing Responsible AI principles.
It's important to note that the landscape for AI-driven products is still evolving, and there are no established best practices. The legislative framework surrounding these models remains uncertain, making it even more vital to engage in discussions…

Are Large Language Models (LLMs) sophisticated pattern matchers ('parrots') without understanding or potential prodigies that eventually surpass human intelligence? Drawing insights from both camps, we attempt to reconcile these perspectives, examines the current state of LLMs, their potential trajectories, and the profound impact these developments have on how we engineer software in the years to come.

Target Audience: Developers and Architects
Prerequisites: A basic understanding of Large…

Artificial Intelligence (AI) has become integral to software development, automating complex tasks and shaping this field's future. However, it also comes with challenges. In this talk, we explore how AI impacts current software development and possibilities for the future. We'll delve into AI language models in programming, discussing pros, cons and challenges. This talk, tailored to both supporters and skeptics of AI in software development, doesn't shy away from discussing the ethical…

Great engineers often use back-of-the-envelope calculations to estimate resources and costs. This practice is equally beneficial in Machine Learning Engineering, aiding in confirming the feasibility and value of an ML project. In my talk, I'll introduce a collaborative design toolkit for ML projects. It includes Machine Learning Canvas and MLOps Stack Canvas to identify ML use cases and perform initial prototyping, thus ensuring a business problem can be effectively solved within reasonable cost…

In this session, we focus on the topic of software product management (PdM) and how PdM practices are rapidly changing. Together we explore and define how to do PdM for digital products as well as software-, data- and AI-intensive systems. Some questions we explore include:

1. How to change current PdM practices to work with digital technologies and digital offerings?
2. What is the future of PdM practices and what are the key characteristics of digital product management?

Target Audience: Product…