Introduction: Artificial Intelligence as a Service (AIaaS) is a cloud-based service that provides access to various AI technologies and tools, allowing businesses to leverage the benefits of AI without having to invest in developing and maintaining their own AI infrastructure. AIaaS includes natural language processing, computer vision, predictive analytics, and speech recognition.  ...

Introduction :    The digital identity solutions market is growing rapidly, driven by the increasing demand for secure and convenient ways to authenticate and verify users online. Digital identity solutions enable users to create and manage digital representations of their identities, which can then be used to access a wide range of online services, such as banking, government...

Introduction : FPGA Market growth can be attributed to its increasing adoption across applications including telecom, data center computing, automotive, industrial aerospace and defense and medical.   FPGAs (Field Programmable Gate Arrays) are integrated circuits designed to be programmed digitally for multiple digital functions. In contrast to ASICs (application-specific integrated...

Introduction : In recent years, the Restaurant Digitalization Market has experienced staggering growth driven by technological innovations and shifting consumer tastes. As global dining landscape changes, more restaurants are turning to digital solutions in order to enhance customer experiences, streamline operations and remain competitive in today's digital-centric environment. This market...

Introduction:    On-demand transportation (ODT) services provide passengers with transportation that meets their individual needs and requests. ODT booking can typically be done using mobile apps or websites and passengers can choose their pick-up and drop-off location within the service area. ODT vehicles tend to be smaller and more agile than traditional buses or taxis, enabling...

Introduction:    Federated learning (FL) is a machine learning technique used to train a shared model on multiple devices without exchanging their data. Instead, each device trains the model on its local data and shares only any updates to model parameters with the central server; then this central server aggregates updates from all devices and develops a global model before sending...