Artificial Intelligence: Five Trends for 2018 Cray Blog

As we start 2018 here at Cray, we believe artificial intelligence and, more specifically, deep learning will continue to dominate the emerging technology landscape conversation (and I know that some might argue block chain technologies have already surpassed AI, but that's another conversation). Since we have several subject matter experts at Cray, I thought it might be a good idea to reach out to the Cray AI team and ask them, "What is a trend for AI or deep learning you expect in 2018?" While 10x may be hard to repeat in the next year only based on software modifications, newer algorithms will provide a similar speed up for GANs, LSTMS, RNNs and so forth, and together will guide the requirements for hardware acceleration and scale-up into 2019. To quote Aaron, "This is the #1 most important thing for those in HPC to realize -- machine learning is coming for traditional science domains outside of analytics and informatics. Machine learning with neural networks is coming to the physical sciences at scale, and this means high-performance computing. You need a net of size N 2 trained on M data items to find cats in 2D images, but you need a net of size N 3 with M 2 data items to find the binding of drug molecules to proteins. As ML goes into the physical sciences with 3D data, these nets are going to'blow up' in terms of compute resources needed. These will be true HPC applications requiring true supercomputer scale."