There are many misconceptions about artificial intelligence, with many people still thinking of AI as the creation of science fiction writers and filmmakers, when the reality could not be further. Actually, artificial intelligence and machine learning systems are already present in every aspect of our lives, helping us find the music we like, navigate traffic or even arrange products in a store so we buy as much as possible. Here are some concrete examples of how AI is being used in various industries.
Faster and more efficient complaint handling
Afiniti’s collaboration with T-Mobile is a good example of how machine learning systems can be found in places where we don’t expect them at all. In this case, artificial intelligence was tasked with selecting the most appropriate customer service agent for each customer and problem based on voice and text processing. This has made the handling of customer complaints much more efficient and has saved T-Mobile an extra $70 million a year as a result of reduced leadtimes of customer handling.
Autonomous vehicles in agriculture
Blue River has partnered with John Deere, the Ferrari of tractors, and the result is another step towards the full mechanisation of agriculture. Self-driving tractors have been experimented with by several manufacturers, but John Deere’s latest development is fully autonomous, meaning no one has to sit in it, you just take the tractor to the land you want to work, configure it with a mobile app and it does the work on its own. The tractor’s work can be monitored via the app, which also sends a notification if the vehicle hits an obstacle that could damage it. Apart from that, however, the only time you need to deal with the tractor is when you need to refuel it. In addition to the fact that the tractor can work at night, saving you a lot of time, with the help of Blue River’s AI-based software it also uses the pesticide much more efficiently, with savings of up to 90%.
Optimising car production
A key part of car manufacturing is the production of catalytic converters, as they are made using very expensive materials. Early detection of defective parts and rejects is crucial to optimise production. Every 1% improvement in the manufacturing process means an annual cost reduction of £18 million for one car manufacturer. C3 AI’s optimised production planning programme based on the analysis of time-series data has resulted in savings of £180 million per year after they created a machine learning system that filtered out low-quality activated carbon filters and optimised processes.
Skirt trend forecasting
In the clothing industry, knowing what will be in fashion next season can be a huge advantage. The French company Heuritech has developed an artificial intelligence that uses machine vision to predict what skirt trends are likely to be on the horizon, based on images found on public web pages. Thanks to the software’s prediction, one global clothing company has seen a 12% increase in revenue.
Artificial intelligence in the pharmaceutical industry
Hungarian pharmaceutical blue chip company Richter is one of Neuron Solutions‘ partners, as artificial intelligence is playing an increasingly important role in the field of drug discovery. Pharmacology, which investigates the effects and mechanisms of different drug candidates to support drug development, is based on the systematisation and analysis of data from experiments and the search for correlations in the data. The effects of a drug are complex, often non-linear, relationships that can be explored by identifying complex patterns. Machine learning is a promising method for finding and recognising these relationships and patterns. With the involvement of Neuron Solutions, Richter is able to make more accurate predictions, reveal pharmacological effects and speed up the process of testing the efficacy of drugs.
