FYI, @OpenAI: "At OpenAI, we think adversarial examples are a good aspect of security to work on because they represent a concrete problem in AI safety that ca

FYI, @OpenAI: "At OpenAI, we think adversarial examples are a good aspect of security to work on because they represent a concrete problem in AI safety that can be addressed in the short term." https://openai.com/blog/adversarial-example-research/ https://openai.com/blog/adversarial-example-research/ Hardly proof that deep learning is fundamentally flawed. Regarding real world issues, these issues come up when you don't separate training and test (and real world) sets properly. My worries would be with implementation.