Conference: AI in the Industry
At the AI Conference on January 24, 2024 in Frankfurt, experts will explain how AI will change their company and how they can prepare for these changes. In the three sessions Business, Technology and Use Cases, they will discuss with participants at eye level in small groups, where ideas and questions can be contributed.
For many companies, AI in industry means new business models, new technologies, new processes and new applications - certainly also with large language models such as ChatGPT, the most discussed topic in recent months. Yet AI in industry is more than just a huge language model with special requirements for the models.
The industry is asking, what do business cases look like or how do I deploy trained models and who is actually responsible for the MLOps?
Join us as the future of AI in the industry is defined.
AI in the Industry
Business – Technology – Use Cases
In product management for the TwinCAT automation solution, Fabian Bause deals with the integration of machine learning processes into industrial automation. This includes infrastructure components in hardware and software that allow AI to be integrated into the PLC environment, components for the distribution and management of AI models on machine controllers and LLMs to support machine programmers in their daily work.
Claudia Becker is the founder and Managing Director of EDGIZE. With her company, she primarily supports technology-oriented companies with digitalization projects, innovation projects and change projects. EDGIZE takes a holistic approach: in addition to developing new technologies, products and processes, it also trains and promotes new skills and working methods among its clients. Because new technologies also require new approaches.
About the presentation:
The latest developments in the field of AI will fundamentally change technological development processes. The engineer of tomorrow will have to be more committed to the art of engineering than to engineering science. Imagining, experimenting and creating new systems will become the focus of their work. That is why we ask: Can the engineer do Ki? What does the future of engineering look like with and through Ki?
Bastian Best is a patent attorney and helps IP professionals to obtain better patents for the megatrends of the digital future: AI and Machine Learning, Big Data, Web3 and Internet of Things. He lectures worldwide on patents for future technologies, teaches digital patents at ETH Zurich and shares his knowledge on LinkedIn and YouTube. For this year's 50th anniversary of the European patent system, he is named as one of the "50 Leading Tech Voices" by the European Patent Office. His digital patent law firm BESTPATENT has repeatedly been recognized by the Financial Times as one of "Europe's Leading Patent Law Firms".
Dr. Tristan Behrens is an artificial intelligence expert, AI composer and AI trainer. He has an extensive track record in successful deep learning projects. His biggest focus is deep neural networks for composition. He has released several albums of music composed with computers. Since January 1, 2023 he is Artist in Residence at KI Salon Heilbronn.
Composing music with language models
II his lecture, Tristan will show how language models can be used to compose music, effectively bridging the gap between NLP and symbolic music generation. Tristan will talk about his work and experiences in this field.
Entwicklungsleiter bei fruitcore robotics
Christian Heining has been Chief Product Officer at up2parts GmbH since the company was founded in 2019 and is responsible for product development based on artificial intelligence for the machining industry, particularly in the area of work preparation automation. With a degree in mathematics, Dr. Heining holds a doctorate in numerical simulations and has more than a decade of expertise in the development and simulation of complex machine components.
Dr. Tim Herfurth is Lead Data Scientist and has been working for the innovation service provider Zühlke Engineering since 2021. He studied physics and then completed his doctorate in computational neuroscience. Since then, Tim Herfurth has held various roles as a data scientist in service and development. At Zühlke, he works both in implementation and in consulting on the use of AI for various companies in industry and medicine.
Dr.-Ing. Robin Hirt , founder and Managing Director of prenode GmbH in Karlsruhe, is an expert in the field of artificial intelligence (AI) in mechanical engineering. Driven by the vision of the autonomous factory, prenode has constantly built up an IIoT service that supports companies in using advanced technologies such as machine learning and AI tools to optimize the operation of machines and sustainably improve production.
Benedikt Schmidt is Product Owner and Senior Principal Engineer at ABB, specializing in Machine Learning and Advanced Analytics. His current focus involves developing analytics and machine learning solutions for control systems to advance towards autonomous plant operation. He holds a Ph.D. in computer science from Technische Universität Darmstadt. Prior to his current position, he worked at ABB Corporate Research, where he applied artificial intelligence to enhance automation and control processes.
Stairway to Autonomous – How Augmented Operator amplifies human potential
The process industry is more and more leveraging the capabilities enabled by the tremendous digitalization efforts of the recent decades. A significant goal is humans partnering with autonomous systems to realize safe, smart and sustainable operations.
We talk about a transformation process towards this goal - an evolution that can be organized alongside assistance applications. Like cars evolving from assistance to autonomous. We give insights into ABBs work on Augmented Operator, blending state of the art artificial intelligence and profound work on user experience, noting the "what works, what does not" from customer projects.
Franziskos Kyriakopoulos is co-founder and managing partner of the Linz-based AI start-up 7LYTIX and a passionate data scientist and specialist in predictive analytics. He has been working intensively with complex systems for almost two decades as part of his research activities at the Complexity Science Hub of the Medical University of Vienna and has many years of experience in the fields of data science, applied artificial intelligence and data visualization. His expertise in using data science and AI in real business use cases for companies in a wide range of industries enables 7LYTIX to always offer innovative AI products for forecasting and analysis.
Sampo is an experienced entrepreneur with a number of ventures under his belt. He brings a wealth of experience from the intersecting worlds of technology, corporate training and marketing. As Head of Learning Groups at MinnaLearn, he is currently pioneering innovative methods in AI education and using his diverse skill set to revolutionize the way we approach learning. Sampo's experience founding multiple companies has given him deep insights into lifelong learning that he is passionate about sharing with other learners and leaders.
Dr.-Ing. Carlos Paiz Gatica is Product Owner in the Industrial Analytics division at Weidmüller, where he is responsible for the Industrial AutoML product. The development has received several awards, including the German Excellence Award. Mr. Paiz Gatica studied electrical engineering at the Instituto Tecnológico in Mexico. He then completed a master's degree in AI and robotics at Chalmers University in Sweden. He received his doctorate in electrical engineering from Bielefeld University in 2011."
In his presentation, he will talk about the crucial role of domain experts in the development of AI solutions in the industry as well as AutoML as a key technology and enabler. Carlos will also present lessons learned and practical examples.
Title: Why AI is unthinkable without open source - and why it's worth contributing!
Open source is eating the world! Many IT innovations are already unthinkable today without open source technologies. This is also the case with AI - almost no AI application can do without the use of open source software.
But open source projects are rarely purely hobby projects - many companies actively contribute, not only financially, but also with development capacity.
In this format, we take a look at how the world of open source software works, how companies benefit from participation opportunities and discuss the opportunities that arise here for German industry.
About the person:
Dr. Dominik Riemer is Managing Director of Bytefabrik.AI GmbH, an open-core software provider for AI-based data analysis of automated production facilities. He is also active in the Apache Software Foundation and a member of the project management board of Apache StreamPipes, a self-service solution for industrial data analysis.
Jan R. Seyler, Director of Advanced Development for AI and Controls at Festo SE & Co. KG, is passionate about robotics and artificial intelligence. With over 7.5 years at Festo, he has significantly contributed to AI and control systems in automation. Seyler also lectures in Applied AI at HS Esslingen and IoT at DHBW Stuttgart, sharing his passion for technology and innovation. He actively contributes to the academic community e.g. by chairing the IAAI - the biggest conference for deployed AI solutions.”
In his talk "Can Machines Build Machines" Jan Seyler delves into the burgeoning field of generative models in AI, spotlighted by advancements like GPT-4, DALL-E 3, Midjourney, and Stable Diffusion. He explores the synergy of generative evolutionary design with AI in developing technical components and mechanical engineering. The talk presents initial research findings, discusses challenges, and aims to clarify the capacity of AI in machine construction. It offers insights into AI's role in future engineering and design processes.
Thoma Sykora, computer scientist, founder and managing director of SABO Mobile IT GmbH
The company he founded develops innovative software for medical technology and to support industrial production processes with a focus on human-machine interfaces. Several research projects with German universities resulted in SABOT - Smart Assistant Bot, an AI platform that enables people to enter into dialog with speech.
His 40 years as an international entrepreneur in the IT industry allowed him to experience the essence of innovation. However, in his view, the applicability of machine learning holds the greatest potential for innovation and new ventures compared to anything that has gone before. Engaging in dialog with machines through speech is the vision that Thomas Sykora is pursuing with the product SABOT - Smart Assistant Bot.
Jakub M. Tomczak is Associate Professor and Head of the Generative AI Group at Eindhoven University of Technology (TU/e). Previously, he was an assistant professor at Vrije Universiteit Amsterdam, deep learning researcher (engineer, collaborator) at Qualcomm AI Research in Amsterdam, Marie Sklodowska Curie fellow in the group of Prof. Max Welling at the University of Amsterdam, and assistant professor and postdoc at TU Wroclaw. His main research interests include deep generative modeling, deep learning and Bayesian inference with applications in image and text processing, life sciences and molecular sciences. He is editor of the "Transactions of Machine Learning Research" and advisory board member of the most important AI conferences (e.g. NeurIPS, ICML, AISTATS). He is also the author of the book "Deep Generative Modeling" and founder of Amsterdam AI Solutions.
Managing Director & Founder, Katulu GmbH
Christian Wagner, born 19.09.1967
30 years of experience in the manufacturing industry, especially in machining. Involved in the automation and digitalization of manufacturing companies for 5 years. Establishment of the Automation division in the HOFFMANN Group from 2019 to 2022. Now independent consultant for the manufacturing industry.
INDUSTRIAL COACH - Strategic development and support for sales, product management and brand @ suppliers and manufacturers in the manufacturing industry (metalworking)
In industry, Automated Visual Inspection (AVI) is vital for quality control in modern production lines. Collecting sufficient data for training neural networks is crucial to acquiring a fast, effective, and robust AVI system. However, data collection is typically expensive and time-consuming, especially for defective data. Therefore, Ruyu’s main research field is producing synthetic defects with limited data, using popular generative models such as Generative Adversarial Networks (GANs) and Diffusion Models. In addition, Ruyu is particularly interested in evaluating synthetic data's effectiveness and identifying valuable synthetic data for downstream tasks.
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