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Reported on September 19, with the development of technology, the hardware is upgraded to intelligent hardware, with the addition of CPU, operating system, and networking, health monitoring, etc. The application of AI technology, in turn, upgraded the ordinary AI of intelligent hardware to generative AI.Nowadays, we are not unfamiliar with generative AI, which brings a more personalized recommendation and a more humanized way of interaction.

Hybrid AI accelerates to the ground, and processors and sensors keep up the iterative pace

The progress of generative AI is not just in smartwatches. In the wearables market, the most popular vendors are vendors Apple and Samsung, which announced their respective latest advances in generative AI in June and July of this year, respectively.

Apple launched Apple Intelligence personalized intelligence system, can understand personal context, built-in large model can deeply understand natural language, can complete the generation of language, pictures, and cross-APP linkage and other functions, Apple Intelligence is integrated into the core of the iPhone, iPad and Mac chips, and empowered it to Siri Siri is an important layout of Apple in the field of AI, and in the future Apple Intelligence will be integrated with Siri into more wearable devices.

Apple as a latecomer to the generative AI track, in the next time, Apple will continue to train Apple Intelligence, and launch more generative AI-based functions, for hardware can bring a new AI experience.

Samsung, on the other hand, is the deep integration of AI functions into the new wearable device category - smart ring Galaxy Ring. Unlike Apple's focus on interaction in generative AI, Samsung's generative AI smart ring focuses more on health monitoring functions, which, of course, has a lot to do with the functional properties of the product. Samsung says that the Galaxy Ring can analyze data through AI to provide personalized health and sleep advice, and it's also capable of controlling Samsung smartphones with gestures.

Samsung also teased that the new Galaxy AI features will be updated to more Samsung Galaxy devices, with built-in AI algorithms that will develop a personal knowledge graph for each user and create a more personalized service. Samsung believes that multimodal and contextual AI will become a connected ecosystem.

From the layout of Apple and Samsung in wearable generative AI can also see a new direction of development: hybrid AI. for example, Apple chose OpenAI cooperation in the field of AI, and Samsung chose to join forces with Google. Specifically, Apple adopts self-research local large model + cloud, part of the AI function in the local end of the Apple Intelligence, beyond the local processing capacity based on OpenAI's GPT-4o model, in the cloud to achieve more complex task processing.

The hybrid AI strategy not only improves the intelligence level of the device, but also enhances the user experience by introducing advanced generative AI technology. Driven by Apple, the “hybrid AI” of wearable devices will accelerate in the future. However, the premise is that the end-side AI is strong enough.

It is not difficult to find, on the one hand, generative AI in more wearable categories on the ground, on the other hand, with the AI function of wearable devices is getting richer and richer, the performance of the main chip, sensors and other hardware needed to be more powerful to support the realization of more functions, which is also the key to the landing of the multimodal large model.

In my opinion, the core of wearable device AI includes sensors, storage and so on. In terms of the main chip, with the increase in AI functions, the performance of the processor needs to be more powerful to execute complex algorithms and tasks, and needs a higher degree of integration. On the sensor side, multimodality is based on multiple data detected from sensors, and Canalys says that for every additional sensor, AI is able to create dozens more brand new application scenarios based on that sensor. Of course, this requires a higher degree of accuracy from the sensor. In terms of storage, the increase in AI applications brings requirements for storage capacity and speed.