Brian sits down with Samuel Cohen, CEO of Fairgen, for a no-fluff conversation about what is actually happening in synthetic data and who is positioned to win as the space matures.

Samuel cuts through the vendor noise fast: most companies claiming to train models on millions of survey responses are not doing that. What is under the hood is usually far simpler, and the lack of transparency is quietly eroding trust in the whole category. Fairgen's answer is to model at the individual level and be open about how it works.

The conversation also covers how collapsing time to insight is changing research workflows, where digital twins fit alongside real respondents in the next few years, and Samuel's unfiltered take on which players are well-positioned and which ones need to rethink their model now.

Key Takeaways:

• Why the data behind the model matters far more than which LLM is powering it

• What most synthetic vendors are actually doing versus what they claim

• Who wins as synthetic data matures and who is in trouble

• What are the best use cases for Digital Twins & Synthetic Data

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