The Myth of Machine Learning
Recently there has been a surge in the number of companies claiming machine learning capabilities, from startups to large organisations. The media is full of "machine learning" claims, investors seem to be dropping large amounts into startups claiming to have "machine learning" or "artificial intelligence" capabilities. From Logo design companies to delivery companies, they all claim to have implemented "machine learning". I recently saw a press release for a US based app development company that had raised a significant 7 figure sum, claiming they had developed "Human assisted machine learning" ! One has to ask, what is that ? Any machine "learning" has to be assisted by humans anyway, who would configure the algorithms, applications and hardware, not to mention the training ?
Neural Networks and AI genetic algorithms have been around for a long time. So why now ? The answer is data (and to some extent computing power). In order to even attempt to do anything smart with "learning algorithms" one must have large sets of data. Since "Analytics" we have that data, sensors and devices connected to the Internet and mini-computers in our pockets, always connected. So gathering data is not a problem. The problem is what to do with the data.
Fundamentally (despite outlandish claims by the media) , Neural Networks can be "trained" to classify sets of input data into categories.
The diagram above shows a plane in 3D space that separates two sets of data (classification). If we project that plane into 2D space we have a non-linear equation.
If there is a means of determining if the classification was successful or not the classification can "learn" as the input evolves. Most current claims of "machine learning" are really simple rules that are able to cluster input data, there is nothing much too these claims. These are more like the old "expert systems" which have a pre-programmed set of rules that help the computation determine some output result. You can imagine this as a large set of IF THEN statements. It is a myth that these systems can learn or that there is any form of "intelligence" in these systems. Somehow we have jumped from these very limited capabilities to machines running the Earth. I guess the one thing we can learn from the media of late (BREXIT and Trump) is that you can't believe what you read !
Whilst I am positive that there are some very clever people out there working on all sorts of clever algorithms, I feel that propelled by media hype there is a big myth surrounding Machine Learning. In some ways it is in the interests of academics, business leaders, marketeers ect. to promote this myth as this fuels their funding.
Neural Networks and AI genetic algorithms have been around for a long time. So why now ? The answer is data (and to some extent computing power). In order to even attempt to do anything smart with "learning algorithms" one must have large sets of data. Since "Analytics" we have that data, sensors and devices connected to the Internet and mini-computers in our pockets, always connected. So gathering data is not a problem. The problem is what to do with the data.
Fundamentally (despite outlandish claims by the media) , Neural Networks can be "trained" to classify sets of input data into categories.
The diagram above shows a plane in 3D space that separates two sets of data (classification). If we project that plane into 2D space we have a non-linear equation.
If there is a means of determining if the classification was successful or not the classification can "learn" as the input evolves. Most current claims of "machine learning" are really simple rules that are able to cluster input data, there is nothing much too these claims. These are more like the old "expert systems" which have a pre-programmed set of rules that help the computation determine some output result. You can imagine this as a large set of IF THEN statements. It is a myth that these systems can learn or that there is any form of "intelligence" in these systems. Somehow we have jumped from these very limited capabilities to machines running the Earth. I guess the one thing we can learn from the media of late (BREXIT and Trump) is that you can't believe what you read !
Whilst I am positive that there are some very clever people out there working on all sorts of clever algorithms, I feel that propelled by media hype there is a big myth surrounding Machine Learning. In some ways it is in the interests of academics, business leaders, marketeers ect. to promote this myth as this fuels their funding.
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