Seas the Day spent 165 days at sea, setting off from Peru, South America, in May 2025. Rowing up to 15 hours a day, they travelled west across 8,213 nautical miles to Cairns, Australia. On Saturday, October 18th, 2025, Miriam Payne and Jess Rowe became the first all-female team to row the Pacific Ocean mainland to mainland, non-stop and unsupported.

Embracing the challenges of the high seas, the duo used this opportunity to empower especially young women, break several world records, and raise nearly £120,000 for The Outward Bound Trust, a UK charity that helps children develop lifelong skills through adventure.

The tale of their Great Escapade is one of two halves. It highlights the challenges faced when their rudder broke just seven days and 350 miles into their first attempt, forcing them to return to land and plan their re-start. On their second attempt, it acknowledges the sheer grit and determination given to keep spirits high when battling driving rain and wind, 30ft waves, sleep deprivation and losing an oar to the ocean. And, it details some of the more technical issues with their power system and emergency hand pump watermaker’s failure and focuses on how resilience and a positive mental mindset to manage these issues.

Seas the Day’s story is a testament to the power of a positive mindset and the sheer drive to continue going forward. The duo will inspire audiences to embrace their own personal challenges and discover the limitless possibilities that lie beyond their own comfort zones.

As AI systems get better and better, we come across unexpected bottlenecks: The technology seems to be ready, but often, the people who should use it aren‘t. In this talk, Gregor Schmalzried looks at the most intriguing current and upcoming developments in generative AI, particularly with agentic systems, and takes them one step further: In a world of abundant technology, which products and services become valuable? And what can we do to reduce fears, inspire minds, and bring everybody along for the ride of a lifetime?

Quantum computing promises substantial speedups for a narrow but important class of problems. Yet today’s discourse often oscillates between exaggerated expectations and unnecessary fear. In this talk Prof. Dr. Patrick Glauner provides a realistic roadmap of what quantum computers will - and will not - achieve over the next decade, highlighting practical constraints such as decoherence, error correction overhead, low levels of programming abstraction and various other often-overlooked challenges. Attendees will leave with a clear understanding of where quantum computing creates genuine value, where classical systems remain superior, and how organizations can prepare without falling for the hype.

Operators face enormous logistical challenges when expanding fibre optic networks. The trench network alone extends over a length that is almost equivalent to the circumference of the earth. Precise billing for these massive construction projects requires innovative solutions. Current methods for verifying route lengths rely on on-site personnel who must walk the constructed sections with a measuring wheel. This process is not only time-consuming and labour-intensive, but also hardly scalable given the dimensions involved.

In their talk, Thorsten Nieser, Dr. Sebastian Stamminger and Dr. Tetyana Kyrey will present an approach that uses AI image recognition for the automated analysis of road surfaces and pavements. Georeferenced camera images and LiDAR scans serve as the data basis. A deep learning model retrained by them evaluates the data and identifies relevant surface structures. The solution presented enables a significant improvement in quality through full inspection instead of random sampling, while also significantly speeding up the billing process. In addition, machine evaluation ensures greater objectivity and traceability of results.

The presentation focuses on practical implementation and the ‘surprises of real life’ - and on providing a clear answer as to where AI helps and where it does not.

Large Language Models have moved from research curiosity to production reality at a pace that has left security teams scrambling. Organizations are racing to integrate LLMs into agentic browsers, AI-integrated development environments, customer service chatbots, and internal knowledge systems – often without fully understanding the novel attack surfaces they're introducing.

This talk examines security challenges at the frontier of LLM adoption: Prompt injection attacks turning helpful assistants into unwitting accomplices, data exfiltration risks hiding within conversational interfaces, and the dangers of giving AI agents the ability to take real-world actions on behalf of users. Drawing from academic research, real-world implementations, and documented incidents, this talk will discuss what's working, what's failing, and what companies need to understand as these systems become embedded in critical workflows.

Generative AI inferencing has quickly become as indispensable as browser search, scaling usage across market sectors and audiences. But what do you do when online is not practical, desired, or secure for the data and content involved? Can these new AI PC’s power AI models offline and be functional alternatives to costly online services? Bob Duffy from Intel, and Markus Schüttler from TNG will answer this question while demonstrating AI Playground, an open-source project from Intel in partnership and collaboration with TNG. This easy to install and operate tool looks and acts like your favorite online AI tool, but leverages over 60 open-source models to perform a variety of AI features like chat, vision, document search, tool calling, image generation, image editing, and video generation, all from a single prompt experience while offline.

The Rennteam Uni Stuttgart e.V. is among the most successful student motorsport teams worldwide, having achieved a total of eleven world championship titles. Following a concise overview of the team structure and its history, the presentation focuses on the hands-on development of an electric Formula Student race car. The technical deep dive covers system architecture, vehicle design, and the interdisciplinary integration of mechanics, electronics, and software. A key emphasis is placed on the driverless system, which combines advanced sensor technology, precise localization, and autonomous trajectory planning. The presentation highlights the successful collaboration between students and industry partners in the development of future-oriented technologies and their validation under real competition conditions.

Chess pieces are heavy and our arms are weak. Luckily, there are strong robots – and with simulation environments and Robot Foundation Models (RFMs), teaching them to move chess pieces has never been easier. In this talk, our Innovation Hacking team teaches you how to train your robot in simulation environments and make it perform in the real world.

They open with an introduction to RFMs, what makes them special and how they are used. Then they hop to a deep dive of NVIDIA's Gr00t, how it's built, how it was trained, how you can use it. After that, they castle over synthetic data generation: They will show you how you can generate robot training data in NVIDIA Isaac Sim and how to further enhance the data with generative AI. Finally, it's time to promote their simulated model to the real world: Our speakers explore how to close the sim2real gap and show how far they can actually push the language and reasoning capability of their trained model.

En passant, they capture the content with code examples and live demos that show both the impressive capabilities and the hilarious failures of this project. Spoiler alert: Not every game ends with a checkmate.

How can you make robot learning accessible to everyone? In this talk, Steven Palma introduces LeRobot, a Hugging Face initiative designed to bring Artificial Intelligence into the physical world by making AI for robotics more accessible through end-to-end learning.

In this talk, he will take the audience on a comprehensive tour of the LeRobot platform, exploring its core pillars for open-source robotics:

• Robots & simulation: Utilizing affordable, real-world hardware like the SO-101 arm, alongside robust simulation environments

• Control & teleoperation: Streamlining data collection through unified robot teleoperation and control systems

• Datasets: Navigating the explosive growth of community-driven datasets stored on the Hugging Face Hub - a surge approaching 30,000 datasets that may signal the "ChatGPT moment of robotics"

• Models: Training with ready-to-use, state-of-the-art (SOTA) Vision-Language-Action (VLA) models in PyTorch, including Action Chunking with Transformers (ACT) and SmolVLA.

• Inference & evaluation: Testing and evaluating policies across various layouts and goals using environments like LIBERO.

Finally, he will highlight the endless possibilities unlocked by the global community, such as multi-task co-training for zero-shot and few-shot motion transfer. Palma will also cover the latest advancements in the LeRobot v0.5.0 release, which supercharges open-source robot learning in every dimension.

Has this ever happened to you: You just spent €50,000 on a humanoid robot, but it's not very fun at parties, so you have to train it to dance using reinforcement learning in a simulation environment on your €100,000 GPU cluster? What do you mean "no"?

In this talk, Thomas Endres and Jonas Mayer will teach you how you can train your humanoid robot to dance using Reinforcement Learning (RL) in simulation environments. They're gonna kick things off with an introduction into RL, covering the basics of policies and rewards. After that, they’ll take you through your first steps in simulation environments with the introduction of NVIDIA Isaac Sim and the Unitree RL Lab. Our speakers will run through the steps of shaping a walking policy, one hilarious fall at a time. Finally, they're going to shake things up with a dancing policy: You will learn how you can retarget human motion from videos to the Unitree G1 robot and train an imitation policy that can dance just as poorly as you.

Throughout the talk, the speakers will do a live training of a walking policy on stage, starting early on in the presentation and checking up on the progress from time to time. For the grande finale, our humanoid robot will close the session with a dancing performance, not missing out on a single step.

Do you wish you had an equal that can play Counterstrike just as godlike as you? Thanks to recent development in Robot Foundation Models (RFMs), robots can learn how to play video games just like you, imitating your best and worst behavior.

In this talk, Thomas Endres and Jonas Mayer show you how you can use imitation learning to teach an RFM to play arbitrary games. They draw first blood with an introduction into Robot Foundation Models. You'll learn how they work, what kind of data they are designed to process and how that makes NVIDIA's Gr00t perfect for playing video games. After that they quick scope the concept of imitation learning, what kind of data they need to train their Gr00t and how they can collect it from games. Finally, they'll tell the story of leveling up the model from total noob to global elite - one failure at a time - and share all the things that they learned along the way.

Throughout the talk, Thomas and Jonas spray live demos into their slides. To close the game, they challenge one member of the audience to beat Gr00t live on stage in a 1v1.

Cognitive scientist Steven Pinker discusses the intellectual journey that led him from the study of language and visual cognition, through a synthesis of evolution and computation to explain the human mind, to his defense of the concept of human nature, culminating in his advocacy of the reality and future prospect of human progress.