Fibocom Debuts the Fibocom AI Stack for Streamlined On-device AI Implementation, Offering a Manageable Service at CES 2025
Fibocom, a leading provider of wireless communication solutions, has announced the launch of the Fibocom AI Stack – an integrated solution designed to facilitate the deployment of AI models on smart devices.
The Fibocom AI Stack is equipped with a powerful on-device AI engine, ensuring efficient operation and minimizing power consumption. This makes it an ideal choice for various industries, including smart retail, autonomous vehicles, smart wearables, and robotics.
The versatile and compatible Fibocom AI Stack supports multi-language SDK interfaces, third-party apps, and hardware accelerators. It also offers cross-platform and cross-system flexibility, compatible with mainstream AI frameworks. Moreover, it works across multiple Fibocom AI module and smart module series, supporting computation power from entry to premium level.
One of the standout features of the Fibocom AI Stack is its extensive library of AI models. It also provides a value-added model selection and fine-tuning service, aiming to enable businesses to scale smart devices in various industries with high-efficiency, cost-effective approaches.
Fibocom is looking forward to collaborating with more industry customers to build their smart devices with Fibocom-empowered on-device AI solutions. For more information, visit the Fibocom AI Stack homepage.
The Fibocom AI Stack can be explored at IMC's booth #10577 in the North hall at CES 2025 from January 7-10. To stay updated on the latest news about the Fibocom AI Stack, follow Fibocom on LinkedIn, Facebook, and YouTube.
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Please note that there is no available information about Willson Liu, the president of the Fibocom AI Research Institute, in the provided search results.
The Fibocom AI Stack is designed to provide a complete solution for facilitating the deployment of AI models on smart devices. It is expected to enable businesses to scale smart devices in various industries with high-efficiency, cost-effective approaches.
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