In the past weeks a lot has been said about last Google I/O's presentation of Duplex, an assistant powered by AI that can make phone calls and talk to humans to make arrangements for you. Some people are so impressed by the achievement that they are already pointing out the ethical consequences of not being able to tell apart a human from a machine, and some are playing it down, highlighting that we have only seen a demo.
An ontology is a data structure that groups entities in domains or types (for example the entities ‘dog’ and ‘cat’ are grouped under the type ‘animals’), and establishes relations between those entities. Its uses in Computational Linguistics are vast, one of the most interesting for us is the application of ontologies for chatbot training. When two humans communicate, they have a shared knowledge of the world that they presume in any spoken interaction. However, a chatbot lacks this indispensable knowledge. An ontology can help the chatbot discern that a person can walk a dog, but a dog walking a person is not something possible in our world.
Your data holds secrets. Uncovering them is absolutely essential to business success. But mining volumes of text-based data for insights poses a big resource challenge for companies, which is why text analytics tools have become so business critical. There are two different approaches in the market machine learning and deep linguistic analysis, as we mention in different articles. In this post, we will dig more in depth in both of them.
According to last year data there are 1,5 million cyber attacks per year, overall it may not sound much but it amounts to 4000 attacks every day or around 200 per hour. Some of them can be irrelevant or small enough to get noticed, however other they can create chaos and millionaire losses for the companies affected; like the cyber-attack that took place last Friday affecting big market players.