Beyond the technology alone, the success or failure of any Machine Learning (ML) initiative depends on its scalability. ML has also initiated a kind of move away from the conventional sequential mode of thinking. In order to ensure scalability, companies are using a certain metric called TOPS or Trillions of Operation Per Second. Getting the right inference post the business analytics functions performed using ML, also involves the use of multiple variables. These too need to be verified. The architecture adopted too needs to be flexible and heterogeneous. Project Trillium is one such being worked by Arm exploring the growth of ML. Arm has been one of the best in terms of scaling up.

Source:https://www.technologyreview.com/s/614660/the-success-of-machine-learning-rests-on-scalability/

Uploaded Date: 16th December 2019