Find and compare the best Artificial Intelligence software for Apple tvOS in 2025
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Use the comparison tool below to compare the top Artificial Intelligence software for Apple tvOS on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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New Relic
New Relic
Free 2,650 RatingsAround 25 million engineers work across dozens of distinct functions. Engineers are using New Relic as every company is becoming a software company to gather real-time insight and trending data on the performance of their software. This allows them to be more resilient and provide exceptional customer experiences. New Relic is the only platform that offers an all-in one solution. New Relic offers customers a secure cloud for all metrics and events, powerful full-stack analytics tools, and simple, transparent pricing based on usage. New Relic also has curated the largest open source ecosystem in the industry, making it simple for engineers to get started using observability. -
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Siri stands out as the most widely used intelligent assistant globally. By utilizing SiriKit and Shortcuts, developers can enable their applications to assist users in completing tasks through voice commands, smart recommendations, or the Shortcuts app. Moreover, your applications can engage users across various Apple devices, including watchOS through Shortcuts, SiriKit Music on HomePod, and SiriKit Media on Apple TV. The Shortcuts API empowers users to efficiently execute actions related to your app either via voice commands or simple taps. Siri smartly integrates with users' everyday activities, offering timely shortcut suggestions right when they are most useful, whether on the Lock screen, within widgets, in Search, or via the Siri watch face. Additionally, Siri's ability to pose follow-up questions enhances the functionality of shortcuts, allowing for more comprehensive task management. For instance, if a user states, "Order takeout," Siri can further inquire, "Which order would you like?" and provide a curated list of favorite meals from a food delivery service for the user to select from. This interactive capability not only streamlines the ordering process but also personalizes the experience for each user.
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Core ML
Apple
Core ML utilizes a machine learning algorithm applied to a specific dataset to generate a predictive model. This model enables predictions based on incoming data, providing solutions for tasks that would be challenging or impossible to code manually. For instance, you could develop a model to classify images or identify particular objects within those images directly from their pixel data. Following the model's creation, it is essential to incorporate it into your application and enable deployment on users' devices. Your application leverages Core ML APIs along with user data to facilitate predictions and to refine or retrain the model as necessary. You can utilize the Create ML application that comes with Xcode to build and train your model. Models generated through Create ML are formatted for Core ML and can be seamlessly integrated into your app. Alternatively, a variety of other machine learning libraries can be employed, and you can use Core ML Tools to convert those models into the Core ML format. Once the model is installed on a user’s device, Core ML allows for on-device retraining or fine-tuning, enhancing its accuracy and performance. This flexibility enables continuous improvement of the model based on real-world usage and feedback.
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