April 28, 2020
Did you know that a Canadian artificial intelligence predicted the coronavirus epidemic 10 days before WHO talked about it?
If the use of artificial intelligence is already recognized in the medical field, this technology can surely be used in many other sectors. While cloud-based AI solutions can be fairly inexpensive these days, is this the solution for the future for your company?
How does AI work in event prediction?
In order to better understand artificial intelligence functioning in event prediction, we called upon the knowledge of one of our experts: Sarah Belghiti, Data Scientist - Valtech London.
The term Artificial Intelligence describes a set of technologies combined to imitate and sometimes even exceed human intelligence. She tells us that in the case of a prediction, the underlying technology is a statistical or machine learning model.
A machine learning model is either a regression, if the value to predict is continuous. For example, if you want to know how much electricity in GWh will be consumed every hour tomorrow. It can also be a classification in the case of a categorical target. For example, if you want to know if a failure will occur on this equipment in the next 6 months.
These algorithms are fueled by historical data of the predicted value as well as by other explanatory variables in order to learn the patterns and the relationships between all of these elements. This phase is called the training. Namely, the more data the model receives, the more patterns it learns and, therefore, the better it can predict the future!
What can artificial intelligence software actually do for your company?
Predicting major events such as a banking crisis, a pandemic or even a natural disaster is what many AI companies are already doing. In the spotlight: BlueDot, a Canadian company whose AI predicted the COVID-19 epidemic, more than a week before it was identified as a major threat by the World Health Organization. This prediction was obtained thanks to an algorithm which reviewed hundreds of thousands of press articles as well as air traffic data.
Aside from these large-scale predictions, there are countless AI applications for business. To name a few, it is currently possible:
- To predict how much your customers will spend over a certain period of time;
- To suggest potential purchases to your customer in a personalized manner, based on their purchase history;
- To converse directly with your prospects through a conversational robot;
- To analyze social flows to find out if we are talking about your brand for good or bad
Did you know that most large companies currently consider AI to be a highly strategic tool? Indeed, they are heavily investing in research and initiating their own Data Science teams, which suggests that the models will become more and more precise over time and that AI can truly be applied to many sectors.
The Principle Access Barriers to AI
Access to data is one of the most common problems that companies face when it comes to AI. While some companies aren’t collecting the relevant data in order to resolve their use cases, many of them are putting a lot of effort into trying to refine the raw data so that it’s unmanageable by most algorithms. Other companies tend to face complications with access to information that is sometimes very confidential, even internally.
Another frequently encountered difficulty relates to the technological resources necessary for artificial intelligence. Some companies with collaborators capable of developing very intelligent algorithms cannot actually produce them. As Sarah Belghiti explains,
"Running a Data Science production environment requires having additional roles within the team, including DevOps and Data Engineers." - Sarah Belghiti
That being said, the technological evolution brought by AI implies a transition of the job market, with new professions and new trainings to be created. Faced with this fact, let us reassure you. Put in the right hands, like any other tool, AI is there to help humans in certain repetitive tasks, allowing them to spend more time on activities with a higher added value.