We propose a model to tackle classification tasks in the presence of very little training data. To this aim, we approximate the notion of exact match with a theoretically sound mechanism that computes a probability of matching in the input space. Importantly, the model learns to focus on elements of the input that are relevant for the task at hand; by leveraging highlighted portions of the training data, an error boosting technique guides the learning process. In practice, it increases the error associated with relevant parts of the input by a given factor. Remarkable results on text classification tasks confirm the benefits of the proposed approach in both balanced and unbalanced cases, thus being of practical use when labeling new examples is expensive. In addition, by inspecting its weights, it is often possible to gather insights on what the model has learned.

Most artificial intelligence is actually not human-shaped robots or talking computers. The risk of artificial intelligence to jobs should be considered by a Government working group, a law firm and a business organisation say. In a call to action paper, the Institute of Directors and law firm Chapman Tripp have highlighted the risks, opportunities and challenges that artificial intelligence presents. Institute chief executive Simon Arcus said artificial intelligence had the greatest potential to affect people's jobs. "What we don't want to have is a whole lot of efficiencies created by artificial intelligence that displaces people and leaves people with no jobs and no future."

Elon Musk famously called it "our greatest existential threat". Physicist Stephen Hawking said that, limited by slow biological evolution, humans wouldn't be able to compete and would be superseded. But the technology that sparked those fears - artificial intelligence - is also being touted as the biggest potential advance in our history. A recent international study found that 50 per cent of experts questioned believe that artificial intelligence - or AI - will be smarter than humans within the next 24 years. And 90 per cent of those surveyed believed that milestone would be reached within 60 years.