Before we dive straight into the AI we need to build a bit of context the type of AI that we’re about to look at is called a neural network that’s basically a computing system that’s modeled after the human brain. There are processing nodes that act as neurons and the neurons layers behave as segments of the brain.
This concept an idea is nothing new and it has been around since the 1980’s, but it’s only become feasible in the lats five years due to GPUs with hundreds of cores being cheap and accessible in addition to this the avaible open source tools for neural networks are making it easier to create pushing progres parabolically faster.
Also an AI that’s been released by gamilon – a Boston company. This one can rewrite as own code based on experience and probabilities rather than hard variables is creators say that it could make the tedious part of coding AI completely automatic. To give you an idea how fast some areas of AI are progressing here’s a video of Jeff Dean ( TED talk)
link -> https://www.youtube.com/watch?v=BfDQNrVphLQ
So in a way, computers can now see and recognize objects better than human for the firs time ever. This has never happened before, in the same talk he goes him to give an example of how unreliable human opthalmologists, were for diagnosing certain eye diseases. In experiments any two human opthalmologists will only agree with each other’s diagnosis 60% of the time and what’s worse if you give any single ophthalmologist the exact same image that they diagnosed a few hours earlier they’ll only agree with themselves 65% of the time. In 2017 artificial intelligence image recognition has been proven to perform better than professional humans in this field.
Possible financial solutions to AI disruption, this includes concepts such as universal basic income based on blockchain technology and insights into how some researchers are starting to think about such things.