IBM's Watson is simply a question answering system. As its creators claim, it can understand, reason, learn and interact by incorporating machine learning techniques, natural language processing and automated reasoning. Right now, its achievements may seem ordinary, however, when it first came into existence around 10 years ago, they were simply astonishing. Since Watson can analyse large amounts of data, it can detect anomalies invisible to the human eye. What is more, it has been built in such a way to understand questions asked in natural language and give simple, yet detailed answers.

Feedback plc (LON:FDBK) expects to see a substantial increase in revenue from its TexRAD software in the second half of the current financial year. The medical imaging firm has previously reported a significant number of purchase orders for research versions of TexRAD in the first half of its current financial year (i.e. to the end of November), but investors hoping this would show through immediately in the interim results were disappointed. The majority of the installations were done just before the end of the reporting period so the sales made only a modest contribution to revenue. Nevertheless, Feedback trimmed its half-year loss before tax to £130,000 from a loss the year before of £155,000 on revenue that dipped to £204,000 from £225,000. "We are encouraged by the continued strong interest shown in TexRAD and the number of research papers being published, which highlight its numerous potential applications, particularly in areas such as liver, prostate and adrenal cancers," the company said.

In the era when everything is getting smarter, AI couldn't have been left behind. Not only do most companies want to have a share in it, they also wish to make it better. For sure technological growth and smart solutions had a lot to do with it. Nowadays researchers have access to much more complex, yet affordable tools. This, mixed with cloud computing and the development of the neural network, makes the studies even more compound.

Let us tell you a little bit about a branch of AI, namely deep learning. It is the software focused on simulating the activities going on in the layers of the brain – neurons in a neocortex, which distinguishes images, patterns, and data. Well, it is, and it wasn't easy to achieve, as it took programmers almost 65 years to get to where they are now. It all started with the development of neural networks in the 1950s when everything circled around simulations of the brain on a very basic level. Twenty years later, the network was able to differentiate patterns and simple images.