April 3, 2018
To be successful with any AI project, one must take steps to fully comprehend “what deep learning is, how it works, and what its most effective applications are.” Ignoring these steps can only doom product development as well as introduce inefficiencies in team productivity.
In a recent article by the chief scientist at Conversica, a company that provides AI software for marketing and sales, Dr. Sid J. Reddy provided insight into the basics of “deep learning” and how “the more nodes and layers in a neural network, the more sophisticated its learning capabilities can become.”
As Dr. Ready also points out, mislabeling and overuse should be avoided. In many cases there is the vendors’ tendency “to label almost anything ‘deep learning.’” This sets up the vendor for a negative experience “because the technology is less effective without sufficient data and domain expertise.”
When all is said and done at the end of the day, the challenge and duty of today’s AI professional remains “to ensure that deep learning applications live up to their billing and deliver benefits to users and society.”
The complete article can be read here: https://venturebeat.com/2018/03/02/deep-learning-is-only-as-good-as-its-data/