AI Researcher in 2012: Deep learning, transformers and the scaling era
The work of AI Researcher is summarised as 2012’s “Deep learning, transformers and the scaling era.” The figure beside that summary is 2017. A salary line in a job advert is not the job. Publishing a paper alongside code, trained weights and a public benchmark result has become an expected package rather than an optional extra, turning a lab's internal milestone into a reproducibility test the whole fiel
What does an AI researcher actually do day to day? Most days split between reading recent papers, writing and debugging training code, waiting on and analyzing results from long-running experiments, and discussing findings with collaborators. Contrary to the popular image, a large share of the job is diagnosing why a model is underperforming or a result won't replicate, not brainstorming new architectures from scratch.
Do I need a PhD to become an AI researcher? For an independent research role at a university or a top industry lab, effectively yes — a PhD remains the field's real credential, since there is no licensing exam. Strong engineers without one increasingly enter through industry residency programs or a public record of open-source work and cited preprints, but titles like 'research scientist' still skew heavily toward doctorate holders.
Is AI research itself at risk from AI? Parts of it clearly are: literature summarizing, boilerplate experiment code and first-draft related-work sections are already routinely AI-assisted, and labs are openly experimenting with systems that propose and run their own experiments. Framing what a result actually means, and taking responsibility for a published claim, have proven much harder to hand over.
Say AI Researcher with 2012, “Deep learning, transformers and the scaling era,” and 2017. Pay does not replace those three.2012
Figures to keep
- Year of the account
- 2012
- Figure from the work
- 2017
- Occupation
- AI Researcher
- The task line
- Deep learning, transformers and the scaling era
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