So at a high level, there are five basic steps to building a supervised neural network to differentiate a dog from a cat in a picture. We define a narrative AI use case Then we collect and annotate data sets related to that use case Then we use computation to training an algorithm to accomplish the use case Then we conduct an Independent Validation of the Algorithm Finally, we can deploy the use case and monitor it for any issues that may come up
But there’s a big problem….
What you see here is only a small portion of the photo that was submitted to this classification service
This is the full photo!
So as you can see, the story of this picture isn’t that Roo is a hound. It’s that Roo is a troublemaker who just shredded the Tilkin family’s couch!
And this service missed both the couch and the culprit.
That inability to appreciate the larger context is something that AI is still weak at doing.
Pistoia Alliance debates AI in life science
2 October, 2017
Where will AI/Deep learning have
an impact in Life Science & Health
Pistoia Alliance Debates
27 September 2017
Poll Question 2: What is your familiarity
with AI/Deep learning?
A. I am using AI/Deep learning
B. I am experimenting with AI/Deep learning
C. I am aware of AI/Deep learning
D. I know next to nothing about it