Computer vision technology aims to automate what the human visual system can do. It is mainly concerned with building artificial systems that obtain information from images or video and are trained to process, analyze and identify patterns. Despite the fact that multiple areas in the human brain are responsible for face processing, which makes us incredibly fast and efficient at remembering them, there is still a limit to the number of faces we can recognize. Another complication is that our memory can be easily tricked by wigs, false beards, glasses, makeup, etc., especially in busy areas during peak hours. Note: The presented solution is based on Computer vision technology, developed within Sirma Group since 2013 and now complements Ontotext's portfolio within Sirma AI.

Have you ever considered delivering a project that utilizes Semantic Technology or a Graph Database to validate your business case? One reason that drives people away from the direct application of such technology is that it is often considered too technical and hard to implement. While somewhat true, this is also misguided. There is simply a lack of organized, consistent resources focused on practical knowledge. This is one challenge we want to address with Ontotext's live, online training.

The Institution of Engineering and Technology (IET), a publisher of widely respected publications and information services for engineers and technicians, has chosen Ontotext's GraphDB to help it improve text indexing and discoverability in its Inspec database. With Ontotext's powerful graph database tool, the IET is continuing its reputation for innovative excellence by applying semantic technology to its text indexing. This technology promises to improve research access and deliver a superior experience to contributors and users. The Inspec database contains more than 16 million highly curated and specialised journal articles, conferences and videos relating to engineering and physics research, developed over the last 40 years. As an authority in the engineering world, the IET has accumulated deep expertise in cataloguing the wealth of content it maintains.

Todor Primov, life sciences product manager at Ontotext, discusses some of the ways artificial intelligence (AI) is changing the face of healthcare. A common joke among certain circles is that AI can be defined as "whatever we haven't done yet". While the current popularity of AI among investors, startups and the wider media is unparalleled, we need to retain focus on what exactly AI means, and its specific sector-based applications. In healthcare and pharmaceutical research, 'AI-like' technologies hold huge promise, but what are the problems these solutions are purporting to solve, and where are the business opportunities? Data volume is a problem in the healthcare sector too.