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Bayesian networks can be used to compute probabilities of causes given effects. Bayesian networks belong to a class of models called probabilistic graphical models. Probabilistic models are particularly good in handling uncertainty.
Managing AI projects poses a new set of challenges compared to, for instance, managing traditional software development projects. We examine some of these challenges.
From text-based news, we extract company and network-level signals that show when companies are at higher probability of stock price decline. Using the described methodology, we were able to show that companies which reached the maximum risk value in our risk model, during any given quarter is up to 13 percentage points more likely to have stock price decline one month later than the average company.
The era of information – We live in a time period characterized by the shift from traditional industries to an economy based on information technology. Thanks to this, companies are more aware every day of the value of the information they accumulate in a seemingly natural way.
The purpose of this article is to introduce the concept and explain it by giving examples of its implications for the artificial intelligence sector in line with Silo.AI’s work on the topic and GDPR compliance. And, most especially, to explain the ways to help prevent organisations leaving privacy to chance and encourage them to have it by design instead.
Silo.AI is an artificial intelligence as a service company with a strong foundation in academia and practice. The company’s purpose is to democratize artificial intelligence and help its customers become AI-first companies, transforming and creating new business using AI. Silo.AI executes AI projects to solve practical business problems.