Mobile-based AR’s immersive capabilities are having a significant impact on entertainment, travel, retail and other industries. Using Apple’s ARKit and Google’s ARCore platforms, developers can build AR apps that can juxtapose digital environments and objects with realistic settings. Augmented Reality and Immersive Capabilities.Why You Should Be Incorporating Deep Learning Algorithms: By using mobile device computing capabilities to implement deep learning, it has greatly improved mobile device usability. Also, with neural networks on mobile devices, you do not need to connect to the internet to access every feature of your app. Since you do not have to question if data has been sent for processing, you will get an improved privacy, data protection and user security. Using Google’s ML Kit and Apple’s Core ML, deep learning libraries like Keras and TensorFLow Lite, our developers can create products with fewer errors, faster data processing and lower latency.Ī huge advantage of on-device machine learning is that it can offer users an accurate, seamless user experience. With the introduction of Bionic smartphone chips by Apple, built-in neural processing units help neural networks run directly on-device at an amazing speed. Close to zero latency is here, with real-time data processing speeds which delivers optimum results. We can forget about latency issues that crop up in cloud computing and mobile sensing. There has been an increased global demanded for a more personalised mobile experience, so a widespread adaption of deep learning and AI in the mobile app development industry is inevitable. May 22 - 4min readDeep Dive into Deep Learning By Jennifer Green
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