Interview with Zack Kass: The Next Renaissance
Motley Fool Hidden Gems Investing
The Motley Fool
4.3 • 3.1K Ratings
🗓️ 11 January 2026
⏱️ 19 minutes
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| 0:00.0 | I don't really care if there's a bubble. I don't care. And I'll tell you why I don't care. |
| 0:08.8 | I don't care because I've studied history long enough to know that bubbles pop and sometimes it's healthy. |
| 0:13.2 | Like, sometimes market corrections are actually quite good. |
| 0:27.4 | That was Zach Cass, author of The Next Renaissance, AI and the expansion of human potential. |
| 0:29.5 | I'm Motleyful producer, Mac Greer. |
| 0:35.4 | Now, Zach Cass is a global AI advisor and the former head of go-to-market at OpenAI. He was at at Open AI when the company launched ChatGPT back in |
| 0:40.0 | 2022. Motleyful contributors Rachel Warren and Rich Lou Mello recently talked to Cass about the future |
| 0:46.7 | of AI and about his new book, The Next Renaissance. You started your career in AI almost 15 years ago, as you say, in the book, and, you know, |
| 0:56.7 | at Open AI as head of go-to-market, you helped the company grow from $1 million to over $2 billion |
| 1:02.3 | in annual revenue. |
| 1:03.3 | But you say that nothing really prepared you for November 30th, 2022, the day that Chat, GPT was |
| 1:09.4 | released. |
| 1:10.0 | So I'd love if you would tell us about your background, your journey, what led you to hear, and then walk us through that experience, that moment in time when the world was introduced to Chat GPT. Sure. Well, I'm not sure that anything would have prepared me for that date. So even as you frame the question, I was thinking, like, what would have prepared me? I went to Berkeley for college. I studied history and computer science. |
| 1:30.0 | I graduated and got a job at a machine learning company. |
| 1:33.3 | And the focus was on, at the time, building datasets. |
| 1:37.2 | It was a company called Figure 8 building datasets for the purposes of machine training. |
| 1:42.7 | Of course, now this has become exceptionally normalized |
| 1:45.0 | and quite lucrative companies like Mercor |
| 1:47.8 | and label box and surge, et cetera. |
| 1:50.6 | And we were principally selling data at the time |
| 1:53.0 | to companies like Facebook, Google, and Amazon |
| 1:57.1 | who could afford these large statistical machine learning models, |
... |
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