COVER STORY - AGE OF AI
CHANGING THE GAME H
NVIDIA’s John Linford gives his take on how generative AI is influencing product design and engineering
aving pioneered accelerated computing since the early 1990s, NVIDIA has become one of the largest and
most influential companies in the artificial intelligence (AI) space. With arguably the world’s most advanced platform for generative AI, the firm is enabling industries across the globe to deploy generative AI applications into production at scale. As such, there are few better placed
to provide insight on AI’s current and future impact on product design than NVIDIA’s principal technical product manager, John Linford. International Design Engineer picked his brains on the progress made so far in AI design tools and their application. “Designers are now using AI-
12
www.engineerlive.com
enhanced tools to create products for industries like automotive, manufacturing, aerospace and energy,” he says. “AI is helping optimise material layouts for maximum strength and minimal weight while taking into account physical constraints like stress, strain, fatigue and thermal limits. AI surrogate models for thermal diffusion, fluid flow and linear deformation provide real-time product performance feedback as the design evolves and enable designers to anticipate physical figures-of-merit like drag or surface pressure before high fidelity simulations are performed.” Simulation-based design processes
are also undergoing transformation, with AI reducing computation
time and improving accuracy in simulations of complex physical systems, he adds: “Everything manufactured is first simulated, and physics-informed neural networks (PINNs) enable simulations that are orders-of-magnitude faster than traditional approaches. PINNs enhance AI models by incorporating the governing equations of physics directly into the machine learning framework. This produces surrogate models that combine physics-based causality with simulation and observed data, enabling real-time prediction. NVIDIA PhysicsNeMo includes PINN architectures appropriate for external aerodynamics, fluid flow and other applications.”
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52
