How we run our in-house generative AI accelerator: Framework for ideation

As one might expect, lots of students who graduate with a doctorate in an AI-related field end up joining an AI company, whether a startup or big tech giant.

According to Stanford’s 2021 Artificial Intelligence Index Report, the number of new AI Ph.D. graduates in North America entering the AI industry post-graduation grew from 44.4% in 2010 to around 48% in 2019. By contrast, the share of new AI Ph.D.s entering academia dropped by 44% from 42.1% in 2010 to 23.7% in 2019.

Private industry’s willingness to pay top dollar for AI talent is likely a contributing factor.

Jobs from the biggest AI ventures, like OpenAI and Anthropic, list eye-popping salaries ranging from $700,000 to $900,000 for new researchers, per data from salary negotiation service Rora. Google has reportedly gone so far as to offer large grants of restricted stock to incentivize leading data scientists.

While AI graduates are no doubt welcoming the trend — who wouldn’t kill for a starting salary that high? — it’s having a alarming impact on academia.

A 2019 survey co-authored by researchers at the Hebrew University of Jerusalem and Cheung Kong Graduate School of Business in Beijing found that close to 100 AI faculty members left North American universities for industry jobs between 2018 to 2019 — a outsized cohort in the context of a specialized computer science field. Between 2004 and 2019, Carnegie Mellon alone saw 16 AI faculty members depart, and the Georgia Institute of Technology and University of Washington lost roughly a dozen each, the study found.

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