The media update team
looks into what machine learning is, and how it is creeping into all facets of life.
Machine learning is the training of machines by humans, where algorithms learn from historical data submitted to it by humans. The data needs to be consistent and accurate for learning to take place as efficiently and effectively as possible. Critically, the amount of historical data given to the machine, especially in its early stages, must be of a large enough quantity so correlations can be created and results validated.
There are two types of machine learning: supervised, and unsupervised.
Supervised machine learning is when a machine is given the data to extract information from, as well as what it should output. For example, a machine could be given a list of food items, where it needs to identify “apples” and “pears” as fruit. As the machine-learning program runs, it would know that every time it saw “apple” or “pear”, it would have to be classified as “fruit”.
Unsupervised machine learning, on the other hand, is when the machine is given the freedom to extract its own insights from the data. This type of machine learning is used to find new patterns or trends in the data, which users may not be aware of already.
Where is machine learning being applied in our everyday lives?
It is likely that you have come into contact with machine learning without even realising it. If you have ever used Google Maps to chart your way home, you have encountered an intelligent learning system. Google Maps, and traffic app Waze, incorporates data submitted by users. As new data enters the system, both Google Maps and Waze adjust their projected routes.
Uber uses machine learning to predict rider demand so that ‘surge pricing’, where there is a sharp rise in fare price due to low supply and high demand, will no longer be a feature of its app in the future. Machine learning is also used by the company to estimate the time of arrival for drivers, meal delivery times for Uber Eats, and optimal pick-up locations.
Will machine learning be part of future technologies?
Self-driving cars is a technological advancement that the likes of Google, Ford, and Tesla are already experimenting with. It is believed that self-driving cars will mean fewer accidents
, optimising traffic on the roads, and if fewer cars are the roads, it reduces pollution. Smart traffic lights
, which will be able to assess varying traffic patterns in real-time and adjust accordingly, will also make traffic in congested cities more efficient once they enter the mainstream.
Customer service is another field that will be revolutionised through machine learning. Chatbots designed to solve customer queries, without the need for human intervention, are already entering the market and will become more sophisticated as time goes on.
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As the amount of available data increases, it becomes more difficult to find the information you are looking for. Data intelligence company Newsclip is using artificial intelligence to get to the insights that lie underneath that growing pile of data. Read more in our article, Newsclip demonstrates the power of AI in text processing