Machine learning – what is it? How to use machine learning in your company?

Artificial intelligence is associated by many with autonomous robots or self-driving vehicles. However, it turns out that a much more popular niche of the AI field is the ability to self-learn, or so-called “self-learning. machine learning. You may not realize how many solutions around you are based on machine learning. The potential of such solutions is really considerable, and many of them can be successfully implemented in enterprises.

What is machine learning?

Machine learning is a concept that has become widely recognized thanks to the program ChatGPT . It’s software based on artificial intelligence that improves its own information through exposure to data. Algorithms in the software also try to anticipate upcoming decisions and forecast the information needed. A good example is the Autocomplete available on the vast majority of smartphones. At the beginning, when writing a sentence, there are very common phrases, typical of the average user. After gathering more experience (read: writing more sentences and sending more messages), the system adds suggestions that are much more tailored. Thus, typing “ab” we can get a variety of suggestions: “so that”, “abecade”, “absinthe”, “abstraction”, “Abelard”, “abstainer”, and even “abulance” if we constantly made a spelling mistake. The machine learning system is therefore open to new knowledge, so that, as the name suggests, it learns on its own.

The origins of machine learning

The reason why machine learning technology was created and developed was to perform certain repetitive tasks much more efficiently. This is indicated by the history of machine learning, which dates back to the 1960s and IBM. There, a project was established under the leadership of Arthur Samuel, which resulted in predicting chess moves and preparing players to respond to their opponent’s plays. Proof of the sophistication of such a system was the defeat of chess grandmaster Garri Kasparov in a game against Deep Blue. A machine learning computer dealt with a Russian chess genius in 19 moves in 1997. This would not have been possible without the input of data into a computer that analyzed the previous games of Kasparov and many other prominent chess players. Another noteworthy event was the discovery and identification of previously unknown molecules of organic compounds based on spectroscopic spectra. Thus Dendral – that was the name of the machine learning system – made the discovery in 1965.

How can machine learning be used in a company?

Machine learning surrounds us in many areas – in addition to the Autocomplete cited earlier, machine learning is present in search engines. From Google to Bing, Yahoo, DuckDuckGo or Yandex, each relies on machine learning to make keyword suggestions, while the results received are more accurate. Machine learning is proving particularly useful where there is customer interaction. Interactive service, virtual assistant, chatbot or remote helpdesk system are just the most popular examples. A particularly useful feature of machine learning is to select tailored ads and products that can translate into higher profits. A machine learning system can also have strictly defensive tasks, such as anti-spam protection or blocking threatening software. Without the support of machine learning, it is difficult to talk about smooth functioning in the field of e-marketing, remote customer service or online stores.

Will machine learning replace humans?

The solutions proposed by machine learning are good, but not perfect – there is always a risk that the implemented information is incorrect or outdated. This affliction is particularly evident in ChatGPT, which generally gives outdated information or does not include the full data area. Thus, machine learning is not capable of replacing humans at this point, at least not in many areas. However, there is no denying that there is great potential in machine learning. When designing IT solutions, more and more software houses are implementing machine learning. However, this requires numerous tests and the uploading of a kind of “knowledge base” in order to work as efficiently as possible. This allows your company to automate some tasks and improve its security. In turn, you will gain time, energy and money for development and implementation in your areas, which until now you had to spend on contacting customers or cleaning your email inbox from spam.