- AI, Data Science, Machine Learning: Main Developments in 2016, Key Trends in 2017 - Jan 10, 2017.
2017 is here. Check out an encore installation in our "Main Developments in 2016 and Key Trends in 2017" series, where experts weigh in with their opinions.
- New Deep Learning Book Finished, Finalized Online Version Available - Apr 12, 2016.
What will likely become known as the seminal book on deep learning is finally finished, with the online version finalized and freely-accessible to all those interested in mastering deep neural networks.
- Deep Learning Adversarial Examples – Clarifying Misconceptions - Jul 15, 2015.
Google scientist clarifies misconceptions and myths around Deep Learning Adversarial Examples, including: they do not occur in practice, Deep Learning is more vulnerable to them, they can be easily solved, and human brains make similar mistakes.
- (Deep Learning’s Deep Flaws)’s Deep Flaws - Jan 26, 2015.
Recent press has challenged the hype surrounding deep learning, trumpeting several findings which expose shortcomings of current algorithms. However, many of deep learning's reported flaws are universal, affecting nearly all machine learning algorithms.