Understanding information with AI
Interpreting different types of information is a task humans are inherently good at with just a little guidance and, from there, conclusions can be drawn and connections made. Artificial intelligence by contrast requires much more training but is capable of analyzing information and building connections in wholly different ways than humans, allowing for a novel perspective on key data.
In this episode, host Spencer Acain is joined by Dr. James Loach, head of research at Senseye Predictive Maintenance to explore the ways AI can analyze and interpret industrial data, the similarities between text generating LLMs and Senseye’s own time series foundation models. James also delves into what it took to make the time series foundation model a reality.
In this episode you will learn:
- The similarities between text and time series data (00:36)
- Challenges of building a time series foundation model (05:50)
Spencer Acain
Technical Writer for Global Marketing at Siemens Digital Industries Software
AI Spectrum
This podcast features discussions around the importance of AI and ML in today’s industrial world.
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