Sorry about this, but i think there are some big flaws in your comment.
> You insist that there is something a machine cannot do. If you will tell me precisely what it is that a machine cannot do, then I can always make a machine that will do just that!
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Know anything about the Halting problem & NP-Hard? There are things that computers will never-ever be able to perform, even if we go quantum.
> Computers will continue to get better at human things as we continue to get better at understanding how human things work
Your argument is the basic concept of symbolism, and deep learning is one of the multiple connectionism types of learning, a whole different world in ML.
> Fraud detection relies heavily on unsupervised learning
No, i have been working in Fraud and no, it is supervised with lot of manual feedback.
> unsupervised learning was usually SVD + clustering or some variation on that. The current state of the art, things like deep belief networks, are able to achieve markedly superior results.
Sorry, No Free Lunch for learning algorithms...
> historically it has been wise to include a human element in fraud detection, I don't believe there is any reason to assume that trend will continue indefinitely into the future.
> You insist that there is something a machine cannot do. If you will tell me precisely what it is that a machine cannot do, then I can always make a machine that will do just that! - Know anything about the Halting problem & NP-Hard? There are things that computers will never-ever be able to perform, even if we go quantum.
> Computers will continue to get better at human things as we continue to get better at understanding how human things work
Your argument is the basic concept of symbolism, and deep learning is one of the multiple connectionism types of learning, a whole different world in ML.
> Fraud detection relies heavily on unsupervised learning
No, i have been working in Fraud and no, it is supervised with lot of manual feedback.
> unsupervised learning was usually SVD + clustering or some variation on that. The current state of the art, things like deep belief networks, are able to achieve markedly superior results.
Sorry, No Free Lunch for learning algorithms...
> historically it has been wise to include a human element in fraud detection, I don't believe there is any reason to assume that trend will continue indefinitely into the future.
Yes, and it will.