4 Matching Annotations
  1. Mar 2019
    1. 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?

    1. 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. 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.

    1. Same-different problems strain convolutional neural networks

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