Digital twins have become one of the most talked about topics because of their promise to leverage innovation to improve design, visually enhance collaboration, and increase asset reliability and performance. However, rail is a very traditional and safety-sensitive industry, and with the backdrop of owner-operators and project delivery firms needing to work within tighter budgets, shorter deadlines, and with increased legislation, change can be slow and challenging. While the risks associated with changing a tried-and-true formula weigh heavily on the minds of those responsible, the upside is that the highly complex nature of rail networks and systems allow for the opportunity to innovate and leverage technology to change the way rail networks do business. Many owner-operators around the world have recognized the potential for digital twins in their work and have begun to explore the opportunities for applying big data analytics, artificial intelligence (AI), and machine learning (ML) throughout the design, construction, operation, and maintenance of rail and transit networks. What Is a Digital Twin?

PVI is a newly formed, well-funded digital ventures lab that is focused on creating disruptive technologies and business models that will optimize how the banking industry does business, services their clients and grows their holdings strategically. The financial services industry is facing major change: many of the business models that power traditional banks and insurance companies will change radically over the next ten years. Pivotus Ventures is a new innovation studio chartered with imagining and creating key technologies and business models that will transform finance and commerce over that period. Pivotus was founded by a group of startup entrepreneurs looking for a way to combine the power of the startup model with the direct access to capital, customers and infrastructure that only exists within established financial services institutions. To do this, we are building a number of small, organic, cross-functional teams that will take ownership of imagining, designing, and creating one potentially disruptive new business every 6-18 months.

The companies said that by combining their respective technologies and know-how, Toyota and PFN would develop service robots capable of learning in typical living environments and executing a variety of tasks. Toyota's robotic development has for 15 years included a variety of different applications besides automotive manufacturing, including social, medical and rehabilitation. Its Human Support Robot, first developed in 2012, is intended to support independent living, including for the elderly and disabled. Toyota is working to improve robotic capabilities in tasks such as picking up and carrying objects, to potential uses in applications such as health management. According to the company, HSRs continue to undergo trials at elderly-care facilities; it has also been used by research and development at 49 organizations in 13 countries.

IT and data leaders are constantly challenged to keep up with new trends in emerging and disruptive technologies, and to determine how each can best aid the organization. In the midst of all the changes going on in 2019, it gets increasingly hard to know where to invest in all this new technology. To help add clarity, here are my thoughts on some of the most important trends that will shape data management and software development for the next couple of years. The business multi-verse expands through multi-cloud as data inefficiencies are solved: Multi-cloud promises tremendous reward if it can be used properly, but data inefficiencies and complicated compliance policies hinder progress for many. Expect to see some of those data inefficiencies fade away as effective data strategies are implemented and new technologies unleash true multi-cloud functionality to the masses.

As it is, the world is unfair. The question now is, do we want automated tech to be unfair too? As we build more and more AI-dependent smart digital infrastructure in our cities and beyond, we have pretty much overlooked the emerging character of artificial intelligence that would have a profound bearing on our nature and future. Are we happy with algorithms making decisions for us? Naturally, one would expect the algorithm to possess discretion.

D23 Expo Disney Parks panel attendees learned today that Genie is here to help you with your vacation planning, and you aren't limited to just three wishes. Disney's Genie is the latest artificial intelligence system to help guests build their own Walt Disney World vacation as magical as possible. Unveiled by Disney Parks, Experiences, and Products Chairman Bob Chapek, Genie is here to help seamlessly plan each Disney day whether you are a first-time guest or seasoned pro. You will be given suggested itineraries based on your interests. Do you want to be a princess in the Magic Kingdom, unleash your inner foodie across the World Showcase, or are you looking to get lost in adventure at Disney's Animal Kingdom?

Nowadays Artificial Intelligence represents an essential technology and an area of high strategic importance that generates tremendous benefits, bringing solutions to numerous societal challenges. The recent innovations have huge disruptive potential. Society needs to be prepared to harness the power of AI, and understand its impact on the economy and society. In the digital era, learning the way AI works and its implications for our lives has become fundamental. Are you wondering how AI might affect your job or your life?

The evolution of novel data processing technologies is fast paced and the volume of data being generated is growing by the second. The food industry stands to benefit from this and has been testing and adapting various routes for using data science techniques to enhance the production of safe and healthy foods. Data science requires a multidisciplinary approach and a broad range of skill sets, from mathematics and statistics, computer science and machine learning to artificial intelligence (AI). Data science also needs to have strong ties to the actual domain knowledge[1] in order to ask the right questions and select the right data. Predictive analytics and scientific modelling are interesting areas of data science and the activity in this space is growing.

A new generation of swarming robots which can independently learn and evolve new behaviours in the wild is one step closer, thanks to research from the University of Bristol and the University of the West of England (UWE). The team used artificial evolution to enable the robots to automatically learn swarm behaviours which are understandable to humans. This new advance published this Friday in Advanced Intelligent Systems, could create new robotic possibilities for environmental monitoring, disaster recovery, infrastructure maintenance, logistics and agriculture. Until now, artificial evolution has typically been run on a computer which is external to the swarm, with the best strategy then copied to the robots. However, this approach is limiting as it requires external infrastructure and a laboratory setting.

Between walking at a leisurely pace and running for your life, human gaits can cover a wide range of speeds. Typically, we choose the gait that allows us to consume the least amount of energy at a given speed. For example, at low speeds, the metabolic rate of walking is lower than that of running in a slow jog; vice versa at high speeds, the metabolic cost of running is lower than that of speed walking. Researchers in academic and industry labs have previously developed robotic devices for rehabilitation and other areas of life that can either assist walking or running, but no untethered portable device could efficiently do both. Assisting walking and running with a single device is challenging because of the fundamentally different biomechanics of the two gaits.