In their conversation, Thomas and Sima discuss:
– How a public methodology can build consumer trust in the data acquisition industry.
– The intersection of data science and neuroscience in building predictive AI models.
– The differences between a predictive AI model and a generative AI model.
– Divergences between data sets collected in a lab setting and data sets gathered in real-world situations.
– Limits on what current AI technology is capable of, and the possible limits of future AI tools.
– Ideal use cases for designers and marketers using different kinds of AI tools.
Although the technology is still evolving, the methodology Thomas’ organization is using to push predictive AI forward holds a world of possibilities for data scientists and digital marketers.
– Infinity Squared – LinkedIn
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