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EFF Publishes AI Progress Metrics as Open Source Notebook

posted by n1 on Wednesday June 21 2017, @07:47AM   Printer-friendly
from the welcoming-our-robotic-overlords dept.

An Anonymous Coward writes:

The Electronic Frontiers Foundation (EFF) have published a breakdown of AI problems such as machine vision and game playing, with associated metrics and datapoints that compare against human-level performance. The code lives here and contributions are welcome. In addition to the usual suspects, they also have open problems in AI safety and security (e.g. resistance to adversarial examples) though with no associated metrics yet.

You can use this notebook to see how things are progressing in specific subfields or AI/ML as a whole, as a place to report new results you've obtained, as a place to look for problems that might benefit from having new datasets/metrics designed for them, or as a source to build on for data science projects.

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  • (Score: 0) by Anonymous Coward on Wednesday June 21 2017, @12:29PM (1 child)

    by Anonymous Coward on Wednesday June 21 2017, @12:29PM (#528974)

    We don't need "actual" AI to replace almost all "knowledge" jobs anyone remotely familiar with "professionals" knows that their primary characteristic is not knowledge but spin

    pub med is already a better diagnostician than any doctor I have ever heard of much less met, better even than house and he has script advantage

  • (Score: 3, Interesting) by takyon on Wednesday June 21 2017, @01:23PM

    by takyon (881) <takyonNO@SPAMsoylentnews.org> on Wednesday June 21 2017, @01:23PM (#528996) Journal

    I didn't say we need actual/"strong" AI to kill jobs. Even plain Google search killed off many knowledge jobs. You don't need so many paralegals (for research, anyway).

    But if strong AI can be created, and I think they will, then you will see a decline of STEM jobs, since AI would be capable of conducting science, designing buildings, creating new technologies, etc. They will have the advantages of brute force calculation and machine learning, but with the creativity to "think outside of the box" and present their work.

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