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Building AI infrastructure for both research and user-facing products, and bridging the gap between

TRACK A: HARDWARE & SYSTEMS
Hardware
Systems

Author:

Dylan Curley

Engineering Manager
Google

Dylan Curley has spent the majority of his career in AI from a software engineering background. He focuses on large scale AI systems infrastructure, automation, scaling, and reliability. These days Dylan manages a team of SREs (reliability engineers) at Google, who are responsible for the vast majority of AI systems across Alphabet including launching & operating the latest advances in Generative AI (Bard, Workspace, Search, YouTube, etc). He has also spent time working on AI for medical research and astrophysics, and advises startups in AI.

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Dylan Curley

Engineering Manager
Google

Dylan Curley has spent the majority of his career in AI from a software engineering background. He focuses on large scale AI systems infrastructure, automation, scaling, and reliability. These days Dylan manages a team of SREs (reliability engineers) at Google, who are responsible for the vast majority of AI systems across Alphabet including launching & operating the latest advances in Generative AI (Bard, Workspace, Search, YouTube, etc). He has also spent time working on AI for medical research and astrophysics, and advises startups in AI.

 

Tom Mason

Chief Technology Officer
Stability AI

Tom Mason

Chief Technology Officer
Stability AI

Tom Mason

Chief Technology Officer
Stability AI
Generative AI

Author:

Juergen Weichenberger

VP of AI Strategy & Innovation
Schneider Electric

Juergen has 20 years of experience in building complex solutions leveraging advanced analytics, data science, database design, architecture and other cutting-edge technologies. Working in the AI industry since the mid-1990s, Juergen have built solutions for various industries and leveraged various methods over time. He joined Schneider Electric in 2022 as Vice President AI New Value Stream. His focus is to produce industry grade solutions, translating the combination of core algorithms, robotic, cybernetics and human intelligence. Previously, he worked as Senior Data Science Executive in Accenture and hold various roles related to AI and data. He holds a PhD degree in Business intelligence and new marketing methods from The Philipp University of Marburg, MBA in Executive General Management and MA in Applied Computer, bioinformatics and cybernetic from Paris Lodron Universität Salzburg.

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Juergen Weichenberger

VP of AI Strategy & Innovation
Schneider Electric

Juergen has 20 years of experience in building complex solutions leveraging advanced analytics, data science, database design, architecture and other cutting-edge technologies. Working in the AI industry since the mid-1990s, Juergen have built solutions for various industries and leveraged various methods over time. He joined Schneider Electric in 2022 as Vice President AI New Value Stream. His focus is to produce industry grade solutions, translating the combination of core algorithms, robotic, cybernetics and human intelligence. Previously, he worked as Senior Data Science Executive in Accenture and hold various roles related to AI and data. He holds a PhD degree in Business intelligence and new marketing methods from The Philipp University of Marburg, MBA in Executive General Management and MA in Applied Computer, bioinformatics and cybernetic from Paris Lodron Universität Salzburg.

 

Walid Hadid

Big Data Integration Partner
The Weir Group

Walid Hadid

Big Data Integration Partner
The Weir Group

Walid Hadid

Big Data Integration Partner
The Weir Group

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

Author:

Maximilian Stauder

Head of Computer Vision & AIoT
Schwarz
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Maximilian Stauder

Head of Computer Vision & AIoT
Schwarz
Edge AI
AI Infrastructure
Systems
Hardware

Author:

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.

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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.