Deep learning is capable of incredible things, but if you are working with mostly structured data for straightforward purposes, Machine Learning can be a much more viable and affordable application, especially as a smaller organization with limited resources.
Popular open source tech can help future-proof your teams.
Deep learning should deliver systems that not only think, but keep learning and self-directing as new data flows in. Enterprise is taking note.
An open-source GPU initiative could drastically speed analytics, including analyses using deep learning.
Continuum Analytics, H2O.ai and MapD Technologies create open common data frameworks for GPU in-memory analytics
A collaboration between Royal Philips and PathAI shows high promise in improving breast cancer diagnoses with deep learning technology.
“If companies can access a quantum computer through an API in the cloud, they can take advantage of the speed without that overwhelming overhead.”
Will computers "see" better than radiologists?
To solve real-world problems with AI, a deep learning system would need to be trained on a trillion parameters in 20 minutes. That may happen soon.
To learn to drive like a human, driverless cars will require massive amounts of data, programming, and computing power.