AI for AI 1: By when will there be an AI that can do "intern-level" ML engineering?
Basic
23
4.0k
2029
14%
2025-01-01
60%
2026-01-01
54%
2027-01-01
60%
2028-01-01
63%
2029-01-01
33%
Later than that/never

Options are inclusive: if this happens tomorrow then all options resolve to YES.

This market will of course resolve somewhat subjectively. The overall idea is "there is a model that I can use instead of hiring an intern". Some things I expect such a model to be able to do:

  • Take a paper as input and give a runnable rough draft implementation (does not need to be bug free)

  • Experiment with hyperparameters for an existing model ("grad student descent")

  • Make some nice loss curve graphs (acceptable to use third-party tools for this e.g. WandB)

  • Take two existing algorithms/models and run comparisons between them ("Model A performs better on this benchmark", "Model B trains 3x faster")

  • Avoid trivial mistakes like no validation set, testing on your train set, etc

Some things I don't expect it to do:

  • Develop novel ML algorithms

  • Any kind of non-trivial distributed training (anything more complicated then "run your code with this flag to make it distributed")

  • Any kind of performance optimization (e.g. writing Triton kernels)

I will give myself one month (2024-07-20) to modify the resolution criteria based on feedback.

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