Deep Learning Frameworks: Difference between revisions
Jump to navigation
Jump to search
(새 문서: Background ===Reference=== <reference/>) |
No edit summary |
||
| Line 1: | Line 1: | ||
There have been many Deep Learning (DL) frameworks, like Theano, CNTK, Caffe2, and MXNet. Nowadays, they appear to be dead or dying, as just two frameworks heavily dominate the DL scene: Google TensorFlow (TF), which includes Keras and PyTorch from Meta aka FaceBook. | |||
However, there is no reason to believe such a duopoly will persist forever. All the time, new DL frameworks are proposed. We have no idea which DL framework will be popular in, say, ten years. | |||
Google has at least two (perhaps more) competing AI teams: Google Brain and DeepMind. Even in the TensorFlow era, DeepMind used their own layer API called Sonnet (instead of the usual Keras) | |||
===Reference=== | ===Reference=== | ||
<reference/> | <reference/> | ||
Revision as of 17:00, 25 March 2023
There have been many Deep Learning (DL) frameworks, like Theano, CNTK, Caffe2, and MXNet. Nowadays, they appear to be dead or dying, as just two frameworks heavily dominate the DL scene: Google TensorFlow (TF), which includes Keras and PyTorch from Meta aka FaceBook.
However, there is no reason to believe such a duopoly will persist forever. All the time, new DL frameworks are proposed. We have no idea which DL framework will be popular in, say, ten years.
Google has at least two (perhaps more) competing AI teams: Google Brain and DeepMind. Even in the TensorFlow era, DeepMind used their own layer API called Sonnet (instead of the usual Keras)
Reference
<reference/>