How can climbing all 14 highest peaks transcend physical achievement and become a vehicle for inspiration?

Nima Rinji Sherpa shares his journey from Makalu village to becoming the youngest person to summit all 14 of the world’s highest peaks. He talks about his holistic philosophy, which emphasizes adaptability, mental fortitude, and symbiotic respect for nature, challenging conventional approaches to climbing. Through personal anecdotes and documentary insights, Nima reveals strategies for transforming tragedy into resilience, empowering a new generation to pursue purpose beyond the peaks.

Embeddings are the foundation of how Large Language Models understand the world. Yet, when you try to read about them, you are bombarded with scary words like tensors, matrices, and multi-head attention. No need! Let's try and actually get a grip on how embeddings work. Join Elias Schecke and Dennis Schulz to understand how powerful embeddings can be as a tool for Natural Language Processing. Of course, they will bring their own demo application that adds a correct, fitting, and tasteful emoji to whatever chat message you feed it with - so your parents will finally be able to pick the correct emoji when writing to you.
Elias and Dennis will explain why they translate language into high-dimensional vectors. Then, they will build a sample application for emoji search, explaining semantic search, finetuning, and multi-modal embeddings along the way. They will also give an overview over benchmarks and how to scale your semantic search application.

What happens if, during a sabbatical, you don’t end up writing a book but instead create a music album - with artificial intelligence as a co-producer? This talk demonstrates how a complete album can be produced in just a few weeks using various AI tools - from the very first lines of lyrics and the arrangement to the mastering process.

The language models employed generate song lyrics and inherit stylistic traits through targeted in-context learning with the creator’s own songs. Suno AI provides initial musical ideas, Splitter AI separates vocals, drums, and instruments, and Basic Pitch converts audio signals into MIDI data. Additionally, MidJourney, Sora, and AI-based mastering engines are used. The workflow combines creative control with efficient automation - far from one-click solutions.

Music producer Ivo Moring (known for DJ Ötzi’s “Ein Stern”) will also offer insights into professional music production in the mainstream sector. He explains how established production processes work in major labels, what role AI already plays, and the challenges it presents.

This talk delivers a practical overview of the tools, workflows, and creative potential of modern, AI-supported music production - offering concrete takeaways for developers, creatives, and tech enthusiasts alike.

The team's vision is to empower every BMW employee to independently derive insights from data while ensuring compliance with governance, security, and quality standards. Bringing this vision to life within a complex and enterprise-scale data environment required a fundamental shift in how they approach data accessibility. Join the team on their journey as they share how they leveraged agentic AI to democratize data analysis across BMW’s central data lake, the Cloud Data Hub. They present the design of a platform solution that makes big data analysis available to all users, including those without technical expertise, through an intuitive and AI-driven interface.
Discover how they evolved from static SQL-based workflows to a dynamic multi-agent system that orchestrates data discovery, querying, visualization, and documentation through a coordinated network of purpose-built AI agents. Their architecture is built to thrive in heterogeneous data environments with a strong focus on explainability, security, and robustness. Within this talk, they will also share practical insights from deploying agentic systems at scale and provide actionable insights into enabling enterprise-scale self-service analytics powered by AI.

In the era of LLMs, one gets notoriously confronted with the question of where we stand with applicability of large-scale deep learning models within scientific or engineering domains. Or slightly differently put, what type of scaling is needed for disrupting verticals besides language and vision. The discussion starts by reiterating on recent triumphs in weather and climate modeling, which culminated in the first foundation model for earth systems. Secondly, the challenges and conceptual barriers which need to be overcome for the next wave of disruption in engineering are discussed.

Artificial intelligence promises enormous potential - but the path from the initial idea to productive rollout and sustainable operation is complex. In this presentation, Mark Brinkmann shares his experiences from recent years. He shows what typical success factors and stumbling blocks look like throughout the entire life cycle - from conception to development to operation. A special focus will be on STACKIT, the cloud platform that serves as the foundation for sovereignty and security.

What if a digital teammate could click, read, and type across the web and your internal tools - so you don’t have to? Meet TWAIN, TNG’s Web AI Navigator: a multi-agent system that actually gets work done. From filing and updating Jira issues, digesting Confluence pages, and booking travel to triaging and replying to emails, TWAIN autonomously navigates real workflows instead of stopping at suggestions.

Dr. Maxim Stykow and Alexander zur Bonsen will share how they built it and what they learned the hard way. Under the hood, TWAIN combines browser automation, internal API access, and LLM planning, with the Model Context Protocol (MCP) enabling a plug-and-play ecosystem of tools for “infinite” extensibility.

Join the talk for:

• Live, end-to-end demos of TWAIN handling tasks that usually take multiple tabs and many clicks.
• Architecture patterns for robust AI agents at work, not just in labs.
• Battle-tested solutions to messy realities: SSO/auth flows, flaky DOMs, context limits, rate limits, and error recovery.
• How they bake in privacy-first principles while keeping the experience conversational - and a little bit magical.

You’ll leave with practical patterns, gotchas to avoid, and checklists you can reuse to bring similar agents into your own environment. This talk is for engineers, architects, and product folks who want AI that moves the needle from “chat” to “ship”. Bring your questions and your toughest workflows.

How to select LLMs to deploy on a GPU cluster for hundreds of engineers? LLM Benchmark results are proudly presented for every new model, but what's behind the numbers? Lennard Schiefelbein und Jonathan du Mesnil de Rochemont guide you to designing benchmarks that actually measure the real-world problem-solving skills of LLMs.

In this talk, they discuss methods for measuring business-relevant LLM skills such as coding, tool calling and performance in agentic workflows. After exposing some of the issues with popular benchmarks, they show you different methods to evaluate LLMs. Discover techniques such as evaluations with ground truth, LLM-as-a-judge and testing LLM-generated code. Additionally, they highlight common pitfalls, and show you how prompt variations and generation parameters can silently impact your benchmark. They provide a decision framework balancing latency, cost, and output quality for selecting LLMs.

You will be equipped to better understand the advertised performance of LLMs - beyond the score. Get ready to evaluate LLMs like an engineer!

Your computer can understand the visual world around you - or even create a new one. From FaceID and Snapchat Filters to Stable Diffusion, visual AI has become part of many everyday applications - and it's easier to integrate than ever. Let's discover the secrets behind computer vision and visual GenAI! Starting from the very basics of computer vision, the speakers will explore how we can leverage deep learning techniques to process, analyze, and alter visual information.

They will kick things off with a brief introduction into how images and videos are processed in computers. After that, they will do a deep dive into Convolutional Neural Networks (CNNs): the type of neural network that took the world of computer vision by storm. They will show you how different CNN architectures help mastering different disciplines of computer vision like classification, segmentation, or pose detection. Finally, they will look into GenAI and explore how diffusion models like Stable Diffusion generate and complete images. Throughout this learning experience, the theoretical concepts with a plethora of live demos will be visualized and their application in a selection of real-world business cases will be shown. Can't wait to get started on your own? They will introduce you to some open source vision frameworks like MediaPipe or YOLO which you can try out at home.

How can you create high quality unit tests for your Java code completely automatically? In their talk, the team will show the inner workings of how they achieve this goal using AI Agents powered by Large Language Models (LLMs). Their tooling delivers high code coverage and extensive business logic testing across diverse Java projects.
They employ a divide-and-conquer strategy and supply the model with necessary context from the repository to understand the codebase. Additionally, a feedback loop based on containerized test execution allows the system to iteratively improve the generated tests. Here, large complex codebases present particular challenges. They will demonstrate strategies to tackle these for test generation. Finally, they will compare the results obtained with several commercial and open-source LLMs.

The limits of scalability have been reached. AI training compute has increased by 10^21 since AlexNet, but these models can’t just get bigger forever. The most powerful language models today use less than 10% of their parameters for any given token, achieving significant computational savings while maintaining high quality. The efficiency comes from Mixture-of-Experts (MoE) architectures, which route different inputs to specialized expert networks instead of activating all parameters, saving compute. Drawing from latest trillion-parameter model design choices, this talk will cover why sparse architectures through MoE represent the most viable path for efficient AI scaling in production systems.

Six months ago, the team was skeptical about AI-assisted development. Today, AI agents handle the boilerplate while they focus on architecture and innovation - and their productivity has fundamentally transformed.

This isn't another AI hype talk. It's an honest journey from skeptics to advocates, with real data and live demonstrations showing how agent-assisted coding transforms daily workflows. You'll see their actual before/after productivity measurements and learn why early-adopting teams are gaining significant competitive advantages in delivery speed and code quality.

Through live coding sessions and real project examples, they will demonstrate how AI agents excel at routine tasks while developers focus on higher-value problem-solving. They will address the real barriers keeping organizations hesitant - legacy codebases, massive repositories, limited AI knowledge - with practical solutions from their extensive production experience across multiple enterprise clients.

Idgard, a security-first file-sharing application, demands stringent operational requirements to guarantee user data privacy. Especially its core promise, namely no unauthorized access, not even by developers or operational personnel, restricts operational possibilities drastically. This talk explores these challenges and technical intricacies of establishing a secure, bare-metal Kubernetes environment to meet these requirements, covering network bootstrap, immutable cluster setup, multi-layer access control, and robust monitoring and alerting mechanisms.

OXG was founded in 2023 as subsidiary of Vodafone to build a fiber network telco as cleanly as possible: pulling fiber cables using a modern Cloud-first approach for the tech stack.

This worked - mostly. Today OXG employs a mixture of self-built and third-party components. While the glue components holding the proprietary business logic come as shiny, server-less, Cloud-native, fully-scripted one-click-deployment artifacts, like every other company OXG is still bound by reality.

Setting up some of the not-so-Cloud-native applications felt like smuggling a dinosaur onto a spaceship – complete with hard-coded passwords, expensive extra luggage, suspicious security findings, and a boarding process that involved three deployment pipelines and a lot of coffee.

This talk will give an overview of the ups and downs of the last two years including the reason why holding a gym membership is the same as having a backup & recovery plan.

Farmers still wake up with the sun, but now, their first stop isn’t the field. It’s the dashboard. From fertilizer application being backed by satellite imagery to monitoring real-time flow rates from sprayers, agriculture is being redefined by data. The challenge is turning these insights into executable field plans. Discover how the digital farming platform bridges the gap between field and office by leveraging a microfrontend and microservice architecture. Learn how the team combines mobile and web applications to empower farmers, distributors, and technicians with seamless data flow and user experiences. They will walk through the technical challenges they faced and address issues around consistency, cross-team alignment, and complexity. Join the talk to see how Yara Farming Solutions Europe transforms digital farming.

Humans are innate problem solvers. The desire to discover secrets, unravel mysteries, and solve puzzles runs deep in human nature. Many of us even make a living out of it: Professionals in STEM fields tackle complex puzzles every day. But what makes a problem feel like a joyful challenge rather than a tedious task? This talk highlights the core of enigame's daily work - codes, ciphers, patterns, logic, and creativity - through the lens of puzzle hunts.

The core elements of designing puzzles that truly engage people are explored, using examples from Europe's largest puzzle hunt, enigame. It is shown how well-crafted puzzles can foster creativity, build mental flexibility, and create a strong sense of community and collaboration.

According to robotics research, robots are able to perform tasks autonomously in more and more contexts of action. With the help of artificial intelligence, robots can learn to adapt to different environments and challenges. We are then talking about artificially intelligent autonomous robots. How does this adaptive, technically autonomous behaviour of a robot relate to human autonomy, which we regard as a constitutive element of personhood?

This talk examines this question from the perspective of technology assessment. In which contexts does it make sense to allow autonomous robots to act instead of humans? When is collaboration between humans and robots the method of choice? And in what way does human autonomy meet technical autonomy in this collaboration? The different degrees of autonomy in autonomous driving can be used as an example here.

Robots driving go-karts at 30 km/h, guiding visitors through the German Museum and cycling - what could possibly go wrong? Daniel Klingmann and Tobias Lübbe introduce these exhibitions to demonstrate recent advances of humanoids.

"Hold that raw egg for me, will you?" By giving an overview of robotics in prosthetics - where joint actuation and control systems already work - they reveal gaps for humanoids: making context-aware decisions, staying stable on uneven terrain, and performing delicate hand movements.

Robotics is transitioning from factory floors to our everyday lives, particularly through humanoid robots. This session features a live demonstration of our Unitree G1 android, exploring how advances in AI, increasing data availability, and edge computing hardware are transforming science fiction into reality.

The session begins with an overview of robotics and its market potential. Next, robot training is examined, demonstrating how integrated hardware and software bridge the gap between simulation and real-world deployment. Finally, Vision-Language-Action (VLA) models are explored for enabling meaningful human-robot interaction and future applications.

The traditional user experience (UX) design paradigm is no longer applicable in the context of AI. It is not possible to design deterministic user flows when systems generate different outputs from identical inputs. Most AI failures aren’t model failures—they’re context failures.

This talk outlines pragmatic methods for designing AI-powered products, encompassing four pivotal dimensions: non-deterministic UX patterns, generative UI systems, context engineering workflows, and enterprise risk assessment. Learn about concrete methods for testing unpredictable systems, measuring effectiveness without traditional metrics, and communicating the design intent that makes or breaks AI implementations.

You’ll leave with an actionable framework, assessment tools, and design & communication patterns — moving beyond AI hype to systemic design practice.

TNG Technology Consulting proudly advertises an academic staff ratio of 99.9% on its website. But what is the real value of academic education? Can grades truly predict later success in the labour market? And are physics students really the smartest of them all? Time for an education-economics perspective. This talk explores the “return” of education and the predictive validity of grades. Expect latent abilities, selection effects, instrumental variables, plenty of noise, a touch of AI, and a few fun facts from the world of higher education.