Top 5 Trends Tecnology
Advanced machine learning gives rise to a spectrum of smart machine implementations — including robots, autonomous vehicles, virtual personal assistants (VPAs) and smart advisors — that act in an autonomous (or at least semiautonomous) manner. This feeds into the ambient user experience in which an autonomous agent becomes the main user interface. Instead of interacting with menus, forms and buttons on a smartphone, the user speaks to an app, which is really an intelligent agent.
The complexities of digital business and the algorithmic economy, combined with an emerging "hacker industry," significantly increase the threat surface for an organization. IT leaders must focus on detecting and responding to threats, as well as more traditional blocking and other measures to prevent attacks.
The digital mesh and smart machines require intense computing architecture demands to make them viable for organizations. They'll get this added boost from ultra-efficient-neuromorphic architectures. Systems built on graphics processing units (GPUs) and field-programmable gate-arrays (FPGAs) will function more like human brains that are particularly suited to be applied to deep learning and other pattern-matching algorithms that smart machines use. FPGA-based architecture will allow distribution with less power into the tiniest Internet of Things (IoT) endpoints, such as homes, cars, wristwatches and even human beings.
The mesh app and service architecture are what enable delivery of apps and services to the flexible and dynamic environment of the digital mesh. This architecture will serve users' requirements as they vary over time. It brings together the many information sources, devices, apps, services and microservices into a flexible architecture in which apps extend across multiple endpoint devices and can coordinate with one another to produce a continuous digital experience.
IoT platforms exist behind the mesh app and service architecture. The technologies and standards in the IoT platform form a base set of capabilities for communicating, controlling, managing and securing endpoints in the IoT. The platforms aggregate data from endpoints behind the scenes from an architectural and a technology standpoint to make the IoT a reality.
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