29 GLOSSARY Artificial Intelligence
DEEP LEARNING Deep learning is a type of machine learning (see below) that uses algorithms inspired by the operations of a biological brain. Deep learning isn’t always about copying the human mind, although the processes may look very similar to those involved in human decision making and behaviour. Deep learning usually employs complex neural networks (see below) and is superior to mere algorithmic AI in that it gets better and better the more data it is fed. The principles behind deep learning have been around for a while, but it’s only recently we have had the computing power and the ability to manipulate large datasets to realise it. In deep learning, a system can be trained to make decisions based on context. Real world deep learning applications have included live translation of text – not just ASCII, but text read from a sign or from the page of a randomly magazine – and adding appropriately chosen sound effects to a silent film. Deep learning is being used to identify and classify image content and we’ve seen that function applied copiously in the latest MAM systems. MACHINE LEARNING Machine learning is a variety of artificial intelligence in which a computer – or software, specifically – is allowed through repeated exposure to a variety of data to teach itself. Currently, machine learning might involve the supervision of a human being, who can tell
the AI how accurately it has met its goals. Deep learning is one type of machine learning, which utilises neural networks. In machine learning, computers
are – by any meaningful definition of the word – genuinely learning, and just as we can’t exactly see what is happening in the brain of a child as it learns to ride a bike, we can’t always tell exactly how machine learning is taking place. We’ve given the computer a set of algorithmic tools and we can see that it is getting better and better, maybe more creative too, in solving a task, but how it is actually doing may be obscure – a black box. NEURAL NETWORK Neural networks are a system of computer hardware or software inspired by the operation of a biological brain. A neural network consists of connected units, which act a bit like artificial neurons in a biological brain. Each ‘neuron’ can transmit a signal to the next. An artificial neuron that receives a signal can process it and then signal the additional artificial neurons connected to it. Artificial neurons are usually split into layers, with different layers potentially forming different functions.
TURING TEST Alan Turing (played by Benedict
Cumberbatch in The Imitation Game ) was one of the great pioneers of computing. After helping the British Army break German codes in the Second World War with the famous Enigma machine, he worked to develop early computers, including writing an algorithm called Turochamp which could play chess. The computers to run Turochamp didn’t yet exist – the user had to look up each move in a huge collection of printed pages. In a 1950 paper, ‘Computing Machinery and Intelligence’, Turing determined a threshold at which a machine could be said to ‘think’ – when a human interviewer would be unable to determine through conversation whether the subject was human or not - the Turing Test.
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