|second from the bottom, does it say fake or false?|
I like to say that big data is leading us from the Information Age into the Approximation Age. More data doesn't always mean more precision, and although dirty data is a negative term today, I wonder if in some time to come, we may begin to see the value in uncertainty. In fact, regarding autonomous vehicles, this seems to be where we're already headed already.
Here's a little ditty on using imprecision in algorithm development:
“A paper he wrote as a postdoc at Microsoft Research, Escaping From Saddle Points—Online Stochastic Gradient for Tensor Decomposition, describes how a programmer can use the imprecision of a common machine learning algorithm, known as stochastic gradient descent, to his advantage.
[related to unsupervised learning]
“Hopefully we will see more growth in this field, especially interesting results such as this which find that the weaknesses associated with a certain algorithm can actually be strengths under different circumstances.”