Developing these systems is just part of the challenge. Making sure they only do what they’re supposed to do may be even harder.
New techniques and approaches are starting to be applied to AI and machine learning to ensure they function within acceptable parameters, only doing what they’re supposed to do.
Getting AI/ML/DL systems to work has been one of the biggest leaps in technology in recent years, but understanding how to control and optimize them as they adapt isn’t nearly as far along. These systems are generally opaque if a problem develops in the field. There is little or no visibility into how algorithms are utilized, or how weights that determine their behavior will change with a particular use case or interactions with other technology…
To read the full Semiconductor Engineering article by Ed Sperling, click here.