RAIL Director

@Rhodes_AI_Lab

We're a group of Rhodes scholars interested in applying AI and Machine Learning to important social challenges. Read more here:

Vrijeme pridruživanja: kolovoz 2017.

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  1. 4. sij 2019.

    RAIL works on issues of ML & society, check out some of our recent work here. Want to get involved? Get in touch director@rhodeslab.com!

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  2. 15. lis 2018.

    Come learn about RAIL and our activities this year at our welcome session — tomorrow, 5pm at the Maths Institute. Projects, talks, & community are some of what’s in store!

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    6. stu 2017.

    by which solves social problems using artificial intelligence 1/3

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  4. 17. stu 2017.

    Here's our call for partners: our team does pro bono work for organizations who want to apply machine learning-powered solutions for social good. DM us for more information!

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    6. stu 2017.

    Applied AI to antibiotic drug discovery with public health England. 3/3

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  6. 25. lis 2017.

    Report from recommends that core public agencies no longer use black box AI and algorithmic systems

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    Robots could make medicine better and fairer—but only if we erase bias in the data they learn from.

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  8. 23. lis 2017.
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    22. lis 2017.

    What is the best paper on AI you've read that is more than ten years old? (And doesn't directly involve Bengio/Lecun/Schmidhuber/Hinton.)

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  10. 23. lis 2017.

    @AndrewNKaplan

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  11. 23. lis 2017.

    This thread on algorithmic accountability in NYC is really needed as more and more significant decisions are made with the aid of algorithms

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    3. lis 2017.

    Here is database of cancer CT images, if anyone wants to work or practice on

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    DeepMind proposes that the human hippocampus makes predictions about the future, and AIs should mimic it.

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    20. ruj 2017.

    "We're in a very empirical era in machine learning...but theory is lagging behind." - Michael Jordan ( ) – mjesto: Hilton San Francisco Union Square

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    We had ~120 persons apply in the first 24 hours, and total of ~270 by 48 hours. Wow!

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    14. ruj 2017.

    LOLA: Agents that learn by modeling other agents:

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    I talked to several infosec professionals about the possibility that hackers are weaponizing AI

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    11. ruj 2017.

    Only 3% of Companies’ Data Meets Basic Quality Standards. Yikes! That's why we spend 80% of our time cleaning data.

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    Microsoft joins Facebook in sharing research with everyone

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  20. 10. ruj 2017.
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