Artificial intelligence is an umbrella term for technologies which make computer systems "intelligent", in the sense that they are able to solve problems and learn from their own experiences. Today, machine learning is one of the best known and most widely used of these technologies.
In simple terms, it is about using mathematics, statistics, rules, computer science, neurology and linguistics to collect, systematise and recognise patterns in large amounts of data. The use of rules, algorithms and patterns is becoming more efficient and advanced every day.
Machine learning is essentially about recognising patterns in large amounts of data. It could for example be language recognition which we find in different types of "chatbots" or dialog robots, which currently appear on many websites. This variant of artificial intelligence is based on the collection and systematization of large amounts of data using probability calculations and algorithms. The use of rules, algorithms and patterns is becoming more efficient and advanced every day.
As long ago as 1996, machine learning enabled the supercomputer Deep Blue to beat Russian chess grandmaster Garry Kasparov in a game of chess using basic pattern recognition.
At the time, the victory was a global sensation. Today, we encounter machine learning solutions based on pattern recognition every single day. For example, when the music service Spotify recommends new playlists for us based on our listening patterns, or when Amazon presents us with targeted offers based on previous purchases.
Deep learning – advanced, but relatively immature technology
Another technology is Deep learning, which involves the exchange of data in what are known as neural networks, networks which resemble the human brain and which are used to extract experiences from historical databases.
Deep learning attempts to mimic the neural structure of the human brain, to enable the computer to make independent decisions based on scenarios and situations which the computer has not previously encountered.
Today, autonomous vehicles are perhaps the best example of a practical application of Deep learning. Another example is the development of robots which are capable of performing complex surgery without any loss of concentration or shaky hands. A little further ahead into the future, we can expect to see household robots which are capable of working out for themselves how they should tidy away mum’s laptop or little brother’s toys.
Cegal sees huge potential in the AI market are currently exploring the use of AI in all the major branches of the company. As a global tech powerhouse, Cegal can enable our clients to leverage AI capabilities safely and ethically on their corporate data and systems, to optimize business processes, enhance customer experience, and create new revenue streams.
Cegal is currently exploring ways of improving technical support and customer user experiences for our products with AI that utilizes our own internal data. We are also embracing responsible personal use of AI such as ChatGPT and CoPilot for productivity and exploring new ideas.
Although AI is an exciting technology there are also ethical and regulatory things to consider when onboarding or implementing systems that include this technology. As a part of our ESG commitment we strive to deliver safe and responsible technological developments for our clients.
We are a UN global compact signatory and have policies that regulate safety around AI in our management system. As new legislation like the EU AI Act will become law it will be incorporated in Cegal as well.