Tulip's Augmented Ops Podcast | TwinThread

This content was originally produced and recorded by Tulip's Augmented Ops Podcast. It features key insights from TwinThread Co-founder and CEO Erik Udstuen's recent appearance. With the Tulip team's permission, we've included links to the original article and recording.

Below is a brief summary of the topics covered.

Content Summary

This episode of the Augmented Ops Podcast shares insights on how Industrial AI and Digital Twins change how companies scale solutions, why working with existing data infrastructure is key to success, and why industrial companies require more than Generative AI to solve their problems.

Here are some key takeaways from the conversation:

• Connecting and Cleaning Industrial Data - Industrial companies have long faced challenges with data quality, but the technology to collect, structure, and enrich industrial data has evolved. By connecting to and gathering the many different types of data within a plant to power its models, TwinThread captures a high-resolution view of what's happening on the floor.
• Digital Twins Offer Scalable Foundation - Plants produce a high volume of high variation data across different lines and processes. By normalizing and standardizing this data in digital twins, TwinThread can build models that are replicable at scale.
• AI = Action - For TwinThread, Industrial AI goes beyond insights. It delivers clear recommendations that enable timely and effective actions.
• New Industrial Data Standards vs Interoperability - Young companies' difficulty bridging the gap between modern automation and decades-old data infrastructure is nothing new. Among this ecosystem of cloud-native vendors, Erik sees a common understanding of how applications and workflows interoperate with legacy equipment as critical. Customers can then obtain the full value of what they already have rather than adopting entirely new data standards.
• The Challenge of Scale - Scaling Industrial AI starts with quick and easy connectivity to legacy data infrastructure. Once data is standardized in the digital twin, reaching scale means enabling customer domain experts to build their own solutions in a no-code/low-code environment. By democratizing these tools and empowering SMEs closest to the problem, you help them develop scalable solutions that stick.
• Operator Adoption and Engagement - Operator buy-in for any Industrial AI solution is essential. By embedding Industrial AI-driven recommendations into familiar HMI/SCADA interfaces and workflows, TwinThread minimizes behavior changes and lowers barriers to adoption.
• Industrial AI v Generative AI - Generative AI may dominate the tech headlines, but industrial processes demand a broader AI toolkit. For that reason, TwinThread built Industrial AI as a superset of which Generative AI is a single component.

Podcast 

Other Links

Tulip - https://tulip.co/

Augmented Ops - https://www.augmentedpodcast.co/ 

Social Media (LinkedIn):

• Erik Udstuen- https://www.linkedin.com/in/erik-udstuen-00000/
• Roey Mechrez, PhD - https://www.linkedin.com/in/roey-mechrez/