It is the most exacting of surgical skills: tying a knot deep inside a patient's abdomen, pivoting long graspers through keyhole incisions with no direct view of the thread. Trainee surgeons typically require 60 to 80 hours of practice, but in a mock-up operating theatre outside Cambridge, a non-medic with just a few hours of experience is expertly wielding a hook-shaped needle – in this case stitching a square of pink sponge rather than an artery or appendix. The feat is performed with the assistance of Versius, the world's smallest surgical robot, which could be used in NHS operating theatres for the first time later this year if approved for clinical use. Versius is one of a handful of advanced surgical robots that are predicted to transform the way operations are performed by allowing tens or hundreds of thousands more surgeries each year to be carried out as keyhole procedures. "The vast majority of patients, despite all the advantages of minimal-access surgery, are still getting open surgery, because so few surgeons have the skills," said Mark Slack, head of gynaecology at Addenbrooke's hospital, Cambridge, and co-founder of CMR Surgical, the company behind Versius.

Artificial Intelligence (AI) may conjure up images of robots and science fiction. But AI has practical applications in today's data-driven organization for product recommendation engines, customer support, inventory management, and more. To support AI in order to drive concrete business outcomes, a strong data foundation is needed. This webinar will discuss practical applications for AI in your organization, and how to build a data architecture to support its use. Donna Burbank is a recognized industry expert in information management with over 20 years of experience helping organizations enrich their business opportunities through data and information.

The industrial world has been in the throes of digitization for well over a decade. Primarily through enterprise resource planning (ERP) and manufacturing execution systems (MES), critical planning, scheduling, warehousing, inventory management, and logistics processes have been automated and simplified. But these gains have been restricted to technology silos, supporting separate functions of the factory rather than improving the performance of the plant -- and its extended supply chain -- in a broader way. Those days may finally be in the past, as manufacturers now have a golden opportunity to take advantage of digitization's promised outsized benefits. The advent of complex smart sensors, artificial intelligence, big data pools, and robotics, combined with the vast connections of the cloud, is heralding a new era for manufacturers, marked by totally integrated factories that can rapidly tailor products to individual customer needs and respond instantly to shifting demands and trends.

Proficient in swordsmanship, a keen archer and an expert in all kinds of medieval combat, Kingsley definitely isn't what you would expect from one of Britain's most successful and decorated entrepreneurs.

From the smartphone to smart homes and smart cities, technology is becoming ever more integral to our domestic, social and business lives. As consumers we all want seamless services that are both endlessly scalable and highly personalised. We recognise that businesses who satisfy those needs will likely succeed in gaining our trust and a share of our wallet. Firstly, the skills required to build our increasingly technological future will need to be drawn from the biggest possible talent pool. Secondly, a lack of diversity in the design, build and decision-making stages of products, technologies and services will make them less likely to appeal to the fickle consumer and therefore succeed.

The use of artificial intelligence in our everyday lives is on the increase, and it now covers many fields of activity. Something as seemingly banal as avoiding a traffic jam through the use of a smart navigation system, or receiving targeted offers from a trusted retailer is the result of big data analysis that AI systems may use. While these particular examples have obvious benefits, the ethical and legal implications of the data science behind them often go unnoticed by the public at large. Artificial intelligence, and in particular its subfields of machine learning and deep learning, may only be neutral in appearance, if at all. Underneath the surface, it can become extremely personal.

The numbers were mind-boggling to contemplate at this year's CogX AI Festival. By 2025 there will be 1036 (yes, that is 10 to the power of 36) IoT devices in the world that will be connected and sharing data. IoT will converge through AI, which will not be limited by time, only by computing power. Making decisions is where AI will have the biggest impact. 'This is the year AI moves from classifying the past to making decisions for the future' proclaimed Vishal Chatrath, CEO of Prowler, at the keynote.

The tumour is hard to miss on the scan. The size of a golf ball, it sits bold and white on the brain stem, a part of the organ that sends messages back and forth between body and brain. In many ways it is the master controller: from the top of the spinal cord, the brain stem conducts every heartbeat, every swallow, every breath. For this young man, the cancer came to light in dramatic fashion. The growing tumour blocked fluid draining from his brain, triggering a huge seizure.

A.CG: The first and most obvious use of machine learning in insurance is that risk and claims will be calculated by software and decisions to insure or to pay out will be made by software - software, not people - and at least many holders of policies will feel that they are being treated mechanically without due regard to the human nuances of their circumstances. NP: What will be interesting over the next 6-12 months will be AI's compatibility with regulation. The main issue that insurers will have is how heavily regulated the industry is. Regulations will only increase (with the introduction of AI), we also have the Insurance Distribution Directive (IDD) coming in later this year. The senior manager's regime will be coming into the insurance space by the end of this year and extending into early 2019.

As reported by the Informationsdienst Wissenschaft, Continental intends to use its collaboration with the DFKI both to optimize its internal processes and to advance the mobility of the future, especially concepts for autonomous vehicles. To this end, the company and the research institute want to set up a research laboratory for intelligent technologies (FIT) at DFKI's Kaiserslautern site. Continental employees will work together with the scientists of the DFKI on basic research, but also tackle specific problems. For Continental, DFKI is the most recent of a number of cooperation partners, including technology companies Nvidia and Baidu, Oxford University, Darmstadt Technical University and the Indian Institute of Technology Madras (India). Continental has already begun to develop a platform for highly automated driving with the AI processor manufacturer Nvidia.