AI/ML turns legacy data into high-value assets, as it takes a lot of data to train AI properly. Using past simulation results and data to learn and approach new design challenges is similar to leveraging the expertise of a team of senior designers but with a more significant advantage. Sign up for this upcoming presentation.
Venue:
Virtual
AI/ML-based methods bring the ability to make use of historical data. Typically, when a volume of data is collected, there is a responsibility to sort through that information to pull out what is most needed, what is less valuable, and what should be discarded. The less useful or discarded data often gets stored away in old formats on computer hard drives, becoming mainly inaccessible and seemingly worthless. However, AI/ML thrives off a backlog of data and makes excellent use of them.
AI/ML can turn these obsolete legacy data into high-value assets, as it takes a lot of data (and math) to train AI properly. In this manner, AI/ML can benefit from unused or old data by recycling them to use as training material. Using past simulation results and data to learn and approach new design challenges is similar to leveraging the expertise of a team of senior designers but with a more significant advantage.
If you are responsible for an engineering department, or in charge of NPI and Product Development /Strategy then you should definitely dial into this online webinar.
Speaker: Christophe Bianchi, Chief Technologist, EMEA
