In this episode of the Engineer Innovation podcast AI Expert Justin Hodges and (not so expert) Stephen Ferguson explain how engineers can start using Artificial Intelligence and Machine Learning TODAY, and quickly achieve massive productivity savings and extra insight into their simulations.
In the second half of the podcast we go through a “code-along-with Justin” example using a publicly available dataset.
We talk about:
• Using ChatGPT to massively increase engineering productivity
• The key steps required to perform any AI or Machine Learning project
• Some common pitfalls
• A way to rapidly assess which AI approach is most useful for your project
• Learning resources that will allow you to get started in AI today
For more unique insights on all kinds of cutting-edge topics, tune into sie.ag/6eCRJ8.
Here are the links to the resources mentioned in this episode:
• A bunny jumping on the back of a dog (created in Mid Journey AI) : sie.ag/6R12nz
• Kaggle Machine Learning Competitions - including the Digit Recognizer competition in which Stephen ranked 563 : sie.ag/5Jymve
• Machine Learning Specialization Coursera: sie.ag/5upGo
• Justin’s Data Set: sie.ag/eWA8H
• Lazy Predict: sie.ag/3fpraz
• Simcenter Studio: sie.ag/as4Xw
• Justin’s LinkedIn profile: sie.ag/32v8g1
This episode of the Engineer Innovation podcast is brought to you by Siemens Digital Industries Software - bringing electronics, engineering, and manufacturing together to build a better digital future.
▶️ About Simcenter:
Engineering departments today must develop smart products that integrate mechanical functions with electronics and controls. They should utilize new materials and manufacturing methods, and deliver new designs within ever shorter design cycles. This requires current engineering practices for product performance verification to evolve into a Digital Twin approach, which enables us to follow a more predictive process for systems-driven product development.
Simcenter™ software uniquely combines system simulation, 3D CAE and tests, to help predict performance across all critical attributes, early and throughout the entire product lifecycle. By combining physics-based simulations with insights gained from data analytics, Simcenter helps you optimize design, and deliver innovations faster and with greater confidence.