Machine learning accompanies us every step of the way, although we do not always realise it. It makes our lives easier when shopping, travelling, suggests interesting music and films, and even prevents car accidents, crimes or heart attacks. How? Through data, of course.
Machine learning is an area of artificial intelligence that, through experience (i.e. exposure to data), is able to automatically learn, improve, interpret data and situations more accurately and, as a result, predict the future (of course, we mean predictions from numbers, not fortune-telling or the stars).
Early collision detection – Tesla cars have built-in cameras to monitor other vehicles, cyclists and road users. Thanks to an on-board computer, artificial intelligence and a permanent connection to the internet (through which they connect to Tesla’s central servers), the car is able to warn the driver of impending danger and even prevent an accident. How?
Several hundred thousand cars of the brand travel a total of several million kilometres every day. Based on the recording and analysis of so many images, the cars ‘know’ that if the vehicle in front of them brakes too frequently and unevenly, for example, or pulls slightly to the side of the road – an accident could occur. Tesla then informs the driver of the danger and either tells the driver to slow down or automatically does so to increase the distance from the vehicle ahead.
This is, of course, thanks to Tesla’s server and self-learning machines, which, based on thousands of recorded footage, are able to predict a dangerous driving situation or accident before it happens.
Heart monitoring – this example is the same as the previous one, except that here we do not have a camera, but sensors that collect information about the patient’s heart behaviour (heart rate, etc.). Because the heart monitoring device can communicate with the server of the pharmaceutical company that manufactured it, the patient data (anonymously, of course) is compared with other results from around the world. In this way, the sensors can alert a person in time that his or her heart rate is approaching a dangerous level, after which a stroke, heart attack or simply cardiac arrest, for example, could occur. Such a small device can save lives.
Unusual body behaviour – in fact, some smart sports bands and smart watches work in a similar way, which, by observing abnormal body behaviour (for example, someone has fainted, or has been carried away by an avalanche in the mountains and has travelled several hundred metres in no time), can inform specific people stored in the phone book about the accident or automatically call the 112 / 911 emergency number. One such situation is depicted in Apple’s advertising by telling three stories that really happened.
3. Online shopping
Amazon, Wallmart, BestBuy – virtually every major online shop, auction portal and even price comparison website uses machine learning technology. A huge part of this is played by the famous cookies, which “remember” which pages we have browsed before, which shops we have visited and which products we have looked at the longest. Not to mention what we have simply bought before. Based on such a shopping ‘map’, the algorithms are able to deduce what other things we might need, like, and what we might want to buy. Sections on the site such as ‘customers also bought’, ‘usually bought together’, or ‘see also’ could theoretically be a summary of the shopping baskets of other, previous customers of the shop… but it could also be a tailor-made, 100% made for us, incentive to shop even more, because machine learning can predict (with varying degrees of success) our shopping behaviour and preferences. As you can see, with machine learning in everyday life it is like with a knife – it can be a helpful tool, it can also be a murder weapon. It all depends on us how we use the self-learning function of machines.
In business, regardless of the size of the company, machine learning can revolutionise the work of several departments or even the entire company. By analysing an organisation’s data (sales, logistics, finance, marketing, etc.), machine learning can predict e.g:
- how much of a carbon footprint we will produce in production or transport
- at what point a part on the production floor will be consumed
- by how much production materials will become more expensive or cheaper
- how the price and demand for a particular product will change
- and more!
Machine learning helps analysts to see areas previously unexplored or overlooked, all on the fly, in real time. And while it is important to remember that artificial intelligence is still learning about, for example, creativity (or how to tell a dog from a muffin) and needs human support, it is an invaluable support for any analyst or business user.
For this reason, it is better to start your machine learning adventure with a trusted Partner such as BPX. If you want to see how machine learning can help your business, contact us: email@example.com
Find out more about machine learning tools: https://www.bpxglobal.com/solution/altair/