Data sharing and open interfaces for AI optimization. With Paul Patras at Net AI and the University of Edinburgh

Data sharing and open interfaces for AI optimization. With Paul Patras at Net AI and the University of Edinburgh

We know that AI models need high-quality, reliable data to produce good outcomes. But do operators have access to the data and can share it across vendors? Do we have the standards in place to facilitate this, and are they sufficient to share data reliably?

In this episode of Sparring Partners, Paul Patras, CEO and Co-founder of NetAI and Professor of Mobile Intelligence at the University of Edinburgh, works on these issues on a daily basis and takes us through how shared and synthetic data and standards are essential to effective AI deployment in the telco networks, and what to do when the necessary is not accessible.

What we talked about:

  • Why is it difficult and yet necessary to share data
  • Standards are crucial, but not sufficient
  • Collaboration within the ecosystem is crucial to success
  • Digital twins and synthetic data are a valuable complement to network data

You can watch the video of this podcast on Sparring Partners on Substack

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