NVIDIA at SEMICON West 2026

October 13–15 | San Francisco, California

NVIDIA is enabling the semiconductor ecosystem to accelerate digital transformation across chip design, manufacturing, and production. At SEMICON West 2026, NVIDIA and its partners will showcase how AI-driven chip design and manufacturing, accelerated computing, autonomous robotics, fab digital twins, and AI factories are powering end-to-end smart factories and scaling semiconductor workloads.

News From NVIDIA’s Keynote at SEMICON West

NVIDIA and Semiconductor Leaders Advance AI Across Chip Design and Manufacturing for AI-Defined Fabs

NVIDIA introduces cuPotential, a new NVIDIA CUDA-X™ library for AI agents that simulate atomic and molecular interactions. Semiconductor leaders are using NVIDIA accelerated computing and AI to advance chip design, manufacturing, simulation, and inspection for AI-defined fabs.

Explore Sessions at SEMICON West 2026

October 13

3:40-4:05 p.m. PT

Nikola Nedovic,
Senior Research Scientist, NVIDIA


October 14

9:10–9:20 a.m. PT

Gaurav Verma,
Vice President Engineering (Reliability) , NVIDIA

1–2:00 p.m. PT

Moderator: Yiyi Wang, Head of Global Semiconductor Business Development, NVIDIA

Panelists:
TSMC: Mao-Chih Huang, Director of the Manufacturing AI & System Development Division
Applied Materials: Brad Eaton, Managing Director, Product Marketing, Applied Global Services
Lam Research: Chris Carter, SVP and GM, Customer Support Business Group
Tokyo Electron: Dr. Akihisa Sekiguchi, SVP and GM, Corporate Innovation and R&D Division
Micron: Aaron Lum, Director of Physical AI, Smart Manufacturing

2:00–2:20 p.m. PT

Da Yang,
Senior Director of Product, Semiconductor and EDA, NVIDIA

2:25-2:45 p.m. PT

Brian Zimmer,
Research Scientist, NVIDIA

2:25–2:45 p.m. PT

Russell Dover,
Head of Autonomous Fab Strategy & Technology, Lam Research


2:50–3:10 p.m. PT

Pradeep Subrahmanyan,
Vice President, Physics Assisted Computational Solutions Group, Applied Materials

3:15–3:35 p.m. PT

3:40-4:00 p.m. PT

Rick Wunderlich,
Research & Development – General Manager, FANUC

4:05-4:25 p.m. PT

Michael DeGrace,
Head of Ecosystems Success, Universal Robots


Latest Semiconductor and EDA News

Image credit: TSMC
TSMC

NVIDIA and TSMC Bring AI Into Fabs to Advance Semiconductor Design and Manufacturing

TSMC is using NVIDIA accelerated computing and AI across lithography, process simulation, fab optimization, and vision-based defect inspection to improve speed, efficiency, and yield.

NVIDIA and Global Industrial Software Leaders Bring EDA Into the AI Era

Cadence, Siemens, and Synopsys are building NVIDIA-powered agents and GPU-accelerated EDA workflows for faster semiconductor design, verification, simulation, and manufacturing.

NVIDIA and Partners Build in America, for America

NVIDIA and its partners are expanding U.S. semiconductor production, electronics manufacturing, and AI factories—strengthening supply chains, creating skilled jobs, and powering the next wave of American innovation.

Image credit: Applied Materials
Applied Materials

NVIDIA and Applied Materials Advance Semiconductor Innovation From Atoms to Fabs

Applied Materials and NVIDIA are connecting materials discovery, process engineering, and fab optimization with accelerated simulation, AI, and digital twins—speeding innovation across the semiconductor lifecycle.

Image credit: Alsemy
Alsemy

Alsemy Accelerates Chip Modeling From Months to Minutes With Physics-Informed AI

Alsemy uses NVIDIA GPUs, NVIDIA PhysicsNeMo, and NVIDIA CUDA™-accelerated AI to replace slow, manual device modeling with fast, scalable workflows while maintaining the accuracy advanced-node chipmakers require.

Image credit: SK hynix

SK hynix

Using AI Physics for Technology Computer-Aided Design Simulations

SK hynix uses NVIDIA PhysicsNeMo to develop AI surrogate models for accelerating TCAD simulations.  The blog shares how its TCAD Intelligence team developed these models and offers steps for building your own. 

Samsung

NVIDIA and Samsung Build AI Factory to Transform Global Intelligent Manufacturing

Samsung and NVIDIA are building an AI factory with more than 50,000 NVIDIA GPUs, combining accelerated computing, AI, and fab digital twins to improve chip manufacturing, factory operations, and robotics.

SK hynix

NVIDIA and SK hynix Announce Multiyear Technology Partnership to Advance Memory for AI Factories

NVIDIA and SK hynix are codeveloping next-generation memory for AI factories and applying accelerated computing, AI, and digital twins to advance semiconductor design, simulation, and autonomous fab operations.

Featured Speakers

Da Yang

Senior Director of Product, Semiconductor, and EDA
NVIDIA

Yiyi Wang

Head of Global Semiconductor Business Development
NVIDIA

Nikola Nedovic

Senior Research Scientist
NVIDIA

Brian Zimmer

Research Scientist
NVIDIA

Partner Ecosystem


FAQs

NVIDIA is showcasing how the semiconductor ecosystem can accelerate digital transformation across chip design, manufacturing, and production. The event highlights how accelerated computing and AI technologies are powering smart factories and scaling semiconductor workloads.

The keynote, titled “The Next Generation of Chips Starts With AI,” will be presented by Tim Costa, General Manager of Industrial and Computational Engineering at NVIDIA. It will focus on how AI-driven supercomputing is transforming the future of chip manufacturing.

NVIDIA technologies accelerate design challenges by emulating AI and accelerated computing within electronic design automation (EDA) workflows. This approach helps tackle increasingly complex design requirements in the semiconductor industry.

Fab Digital Twins are true-to-life virtual replicas that allow manufacturers to conduct real-time simulation, process optimization, and collaborative factory planning. This enables manufacturers to simulate entire production stages before implementation.

Agentic AI uses sophisticated reasoning and planning to solve complex, multi-step problems. These systems ingest large amounts of data from multiple sources to develop strategies and complete tasks independently, enhancing overall production efficiency.

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