TRACK A: SERVER/CLOUD AI INFRASTRUCTURE
AI Infrastructure
Generative AI
Dimitri Metzger
Digital, Data, & IT for Medical AI R&D
Merck
In the case study I provide a deep dive into the area of food production (bakery goods) in europe´s largest bakery factory. The case study is about how we successfully implemented Computer Vision to monitor our production process to evaluate 3.5 mio. bakery goods every day. I will show how this leads to a reduction of food waste during production and how this is aligned with environmental/sustainability goals in food production. I will motivate why AI on the edge was identified as being a crucial success factor and which considerations we took as Schwarz group to get started in this area 3 years ago. I will discuss – based on the case study – how we selected and benchmarked hardware chips (Nvidia, Intel, GPU vs CPU…), how we needed to change software engineering to accommodate for Edge AI, how we integrated edge AI models into our cloud-based infrastructure, how we do the deployment and how/why we still use cloud-based GPUs for model training.
Edge AI
ML Ops
Systems
Maximilian Stauder
Head of Computer Vision & AIoT
Schwarz
Edge AI
AI Infrastructure
Systems
Hardware
Sakyasingha Dasgupta
Founder & CEO
EdgeCortix
Sakya is the founder and Chief Executive officer of EdgeCortix. He is an artificial intelligence (AI) and machine learning technologist, entrepreneur, and engineer with over a decade of experience in taking cutting edge AI research from ideation stage to scalable products, across different industry verticals. He has lead teams at global companies like Microsoft and IBM Research / IBM Japan, along with national research labs like RIKEN Japan and the Max Planck Institute Germany. Previously, he helped establish and lead the technology division at lean startups in Japan and Singapore, in semiconductor technology, robotics and Fintech sectors. Sakya is the inventor of over 20 patents and has published widely on machine learning and AI with over 1,000 citations.
Sakya holds a PhD. in Physics of Complex Systems from the Max Planck Institute in Germany, along with Masters in Artificial Intelligence from The University of Edinburgh and a Bachelors of Computer Engineering. Prior to founding EdgeCortix he completed his entrepreneurship studies from the MIT Sloan School of Management.
TRACK B: INDUSTRIAL EDGE AI INFRASTRUCTURE
AI Infrastructure
Edge AI
Hardware
Walid Hadid
Big Data Integration Partner
The Weir Group
As billions of IoT devices permeates into our daily lives, their resource limitations and connectivity constraints have confined them to only a narrow subset of machine learning capabilities within the broader scope of AI. Edge Processing stands as a pivotal solution, optimizing large-scale data mining and aggregation by relocating the data processing segment of an application to more resourceful devices edge devices within the local network. The integration of GPU-accelerated ML inference on edge devices opens new avenues for harnessing the full potential of AI, fostering a future where intelligent decision-making in IoT is not only accessible via cloud.
Mo will commence the talk by outlining the current landscape of IoT networks, emphasizing the increasing demand for intelligent decision-making at the edge. Traditional challenges associated with centralized cloud-based ML models will be highlighted, setting the stage for the exploration of decentralized solutions.
We will delve into the technical considerations for integrating GPUs, including model optimization, compatibility with popular ML frameworks, and the advantages of parallel processing. Real-world examples will be presented to showcase the transformative impact of GPU-accelerated ML inference on edge devices, enabling the deployment of pre-trained models using latest hardware without compromising performance. Practical considerations, such as power efficiency and scalability, will also be addressed to provide a comprehensive understanding of the benefits and challenges associated with this approach.
AI Infrastructure
Edge AI
Mo Haghighi
Distinguished Engineer
Discover Financial Services
Dr Mo Haghighi is a director of engineering/distinguished engineer at Discover Financial Services. His current focus is hybrid and multi-cloud strategy, application modernisation and automating application/workload migration across public and private clouds. Previously, he held various leadership positions as a program director at IBM, where he led Developer Ecosystem and Cloud Engineering teams in 27 countries across Europe, Middle East and Africa. Prior to IBM, he was a research scientist at Intel and an open source advocate at Sun Microsystems/Oracle.
Mo obtained a PhD in computer science, and his primary areas of expertise are distributed and edge computing, cloud native, IoT and AI, with several publications and patents in those areas.
Mo is a regular keynote/speaker at major developer conferences including Devoxx, DevOpsCon, Java/Code One, Codemotion, DevRelCon, O’Reilly, The Next Web, DevNexus, IEEE/ACM, ODSC, AiWorld, CloudConf and Pycon.
AI Infrastructure
Generative AI
Hardware
Systems
Charles Phiri
Executive Director/Principal Architect AI/ML Innovation
JP Morgan
TRACK A: SERVER/CLOUD AI INFRASTRUCTURE
AI Infrastructure
Systems
AI Infrastructure
Generative AI
Hardware
Software
Moderator
Galina Sagan
Prinicpal
Hitachi Ventures
Galina Sagan is a Principal at Hitachi Ventures, a global venture fund (with >600m USD AUM) with Hitachi being a single LP. Galina specializes in Enterprise SaaS B2B and digital investments. Some of the relevant deals include Trustwise AI, Archetype AI, Rescale and WekaIO. Formerly a Senior Investment Associate at Speedinvest, a pan-European early stage fund with > €1 billion AUM.
Galina has been recognized as one of GCVs Rising Stars in 2022.
Asim Shah
Generative AI Research Engineering Lead
Citi Bank
Euan Wielewski
Machine Learning Lead
NatWest
Jürgen Weichenberger
VP of AI Strategy & Innovation
Schneider Electric
Kamran Naqvi
Chief Network Architect EMEA
Broadcom
Euan Wielewski
Machine Learning Lead
NatWest
AI Infrastructure
Hardware
Systems
Ola Tørudbakken,
Director AI Systems
Meta
Ola has 30 years of experience building distributed systems and high-performance networking across AI, HPC, Enterprise and Telco.
Ola currently serves as Director of AI Systems at Meta. Previously Ola was SVP Systems at Graphcore, driving their 2nd generation AI systems. Ola came to Graphcore through the acquisition of Skala Technologies, an AI startup he co-founded. Prior to Skala, Ola worked as Chief Architect of Networking and Netra Servers at Oracle. Ola joined Oracle through the acquisition of Sun Microsystems. At Sun, Ola served as Distinguished Engineer, amongst many things responsible for the famous 3456-port Magnum Infiniband Switch now on display in the Computer Museum, Silicon Valley. Prior to Sun Ola was at Dolphin ICS, acquired by Sun Microsystems in 2000. Ola started his career as a research scientist at SINTEF, a Norwegian industrial research organization.
Ola is a recognized industry expert in distributed systems, holds over 48 patents, has published several papers in leading publications, and participated in numerous standardization bodies. Ola holds an MSc degree in Computer Science from University of Oslo in 1994