Leveraging Gen AI for Advanced Equipment Data Analytics in Semiconductor Manufacturing at Samsung
Fully autonomous semiconductor manufacturing ('lights-out manufacturing') is becoming achievable through the integration of advanced AI technologies. In this talk, Dr. Jae-Yong Park, VP of Technology at Samsung Semiconductors discusses this transformative approach in detail, combines sensing, analysis, and control systems, drawing parallels with autonomous driving technology. By leveraging foundation models, multi-modal AI, reinforcement learning, and knowledge graphs, Samsung is revolutionizing chip production processes.
Dr. Park introduces Samsung's comprehensive framework for autonomous semiconductor manufacturing, encompassing various key technologies and their practical implementations. These applications range from advanced process control to predictive maintenance and endpoint detection, demonstrating how AI is being deployed to optimize semiconductor production, enhancing manufacturing efficiency at Samsung's facilities and paving the way for fully autonomous semiconductor fabs.
© Industrial AI Conference (IAC) Stanford 2024
Multi-Modal Foundation Models for Chemistry and Materials from IBM Research
Kristin Schmidt, PhD, Principal Research Scientist & Research Manager, IBM Research - shared that deep learning has emerged as a powerful tool for predicting molecular properties and generating molecule candidates, significantly advancing scientific exploration in various fields such as drug discovery and materials science. This progress can be attributed to the successful application of foundation models, which leverage large-scale pre-training methodologies to learn contextualized representations of input tokens through self-supervised learning on extensive unlabeled corpora. The pre-trained foundation models are subsequently fine-tuned for specific downstream tasks. In this presentation, we will introduce the suite of foundation models for chemistry and materials being developed by IBM Research. These models encompass a range of representation types, from SMILES annotations to 3D atomic positions of compounds. We will illustrate how these foundation models can be applied in diverse downstream use cases, showcasing their potential to accelerate scientific discovery.
© Industrial AI Conference (IAC) Stanford 2024
Data Mesh Applied: A Decentralized, Connected & Context-Aware Data Supply Chain for AI
Zhamak Dehghani, CEO of Nextdata explains how data mesh offers a decentralized approach to data sharing, focusing on one of its core principles: domain-oriented, computational data products. She will also showcase the application of data mesh and data products in Retrieval-Augmented Generation (RAG) and traditional machine learning (ML) development flows, using containerization technology — the abstraction of the data supply chain — implemented by her team at Nextdata.
AI and the Future of Voice Interfaces with Pete Warden, Useful Sensor CEO & Founder
The current generation of voice interfaces have failed to gain user adoption. Amazon has invested tens of billions of dollars in the Alexa platform, and people still only use it to set alarms and play music. In this talk Pete will explore why speech interfaces haven't worked so far, and how new advances in AI can address some of those issues. He will focus on applications like integrated user manuals for equipment, real time language translation, and other ways this will impact industrial environments.
© Industrial AI Conference (IAC) - Stanford 2024
Notes on Industrial AI from Hitachi's GM of the Advanced AI Center Chetan Gupta
Chetan Gupta, Hitachi's GM of the Advanced AI Center and VP of Hitachi America’s Industrial AI Lab, shares his insights on the evolution of AI applications within the industrial sector. From the pre-Generative AI era to the present, Chetan explores the opportunities and challenges shaping the industry today. By reflecting on Hitachi's research efforts and customer needs, he provides a valuable perspective on how AI is transforming industries now and what the future may hold as technology advances.
Fireside Chat with Quoc Le, Google DeepMind's Distinguished Scientist
James Cham, Bloomberg Beta's Founding Partner chats with Quoc Le, Google DeepMind's Distinguished Scientist on what's next for Gen AI.
© Industrial AI Conference (IAC) Stanford 2024
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Leveraging Gen AI for Advanced Equipment Data Analytics in Semiconductor Manufacturing at Samsung