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  1. Mar 2019
  2. www.charlottestix.com www.charlottestix.com
    European Union AI Ecosystem | Charlotte Stix | Artificial Intelligence Policy
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    1. alexisowl 31 Mar 2019
      what EU leadership in AI could look like and what might be needed to get there.

      So, EU strategy is investing in ethical AI and by this avoiding direct competition with China and US but still having their place at the party?

      AI
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    charlottestix.com/european-union-ai-ecosystem
  3. jack-clark.net jack-clark.net
    Import AI 138: Transfer learning for drones; compute and the “bitter lesson” for AI research; and why reducing gender bias in language models may be harder than people think
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    1. alexisowl 24 Mar 2019
      The authors say that “while suggested debiasing methods work well at removing the gender direction, the debiasing is mostly superficial. The bias stemming from world stereotypes and learned from the corpus is ingrained much more deeply in the embeddings space.”

      So that debiasing thing can be hard after all...

    2. alexisowl 24 Mar 2019
      If compute is the main thing that unlocks new AI capabilities, then we can expect most of the strategic (and related geopolitical) landscape of AI research to re-configure in coming years around a compute-centric model, which will likely have significant implications for the AI community.

      Reminds me of a discussion about what's more important for the recent successes in ML: algorithms, compute, or the abundance of data.

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    jack-clark.net/2019/03/18/import-ai-138-transfer-learning-for-drones-compute-and-the-bitter-lesson-for-ai-research-and-why-reducing-gender-bias-in-language-models-may-be-harder-than-people-think/
  4. blog.acolyer.org blog.acolyer.org
    Same-different problems strain convolutional neural networks
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    1. alexisowl 24 Mar 2019
      Same-different problems strain convolutional neural networks

      Wow, this is fascinating. I wonder if SD problems could be the next major roadblock for AGI...

      deeplearning
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    blog.acolyer.org/2018/09/21/same-different-problems-strain-convolutional-neural-networks/