These days the COP25 Climate Summit is being held in Madrid. Many subjects are being discussed on the matter of a possible climate crisis, and how to face it. Has Machine Learning (ML) and Natural Language Processing (NLP) something to say about it? Surprisingly, yes, it does!

Is this the era of Fake News? We could say that fake news are one of the most prominent (and dangerous) phenomena on social media. Since they are spreading to traditional media as well, having a reliable way of identifying fake news is more relevant than ever.

All companies that have a large number of clients want to be “customer-centric”, always placing the customer as the center of their strategies. This translates into taking good care of them, promptly and 24/7, without increasing costs, if possible.

Data scarcity is one of the major bottlenecks that AI practitioners have to deal with when training production-level models. Obtaining additional data typically involves costly manual annotation processes which, as we described in a previous post are fraught with problems.

Live Chats are one of the most useful features an online store can offer to its customers. The idea is simple: the store’s website shows a small window in which the user can interact (chat) directly with a representative of the company. Fast, transparent and easy for the customer. 29% of today’s contact centers offer Live Chat technology to the customers they serve, and it’s expected to grow to 64% in a couple of years.

You have a chatbot up and running, offering help to your customers. But how do you know whether the help you are providing is correct or not? Evaluating chatbots can be complex, especially because it is affected by many factors.