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Just a year ago, Qualcomm was struggling as a tech stock, experiencing slow growth in China and facing challenges in the PC and smartphone markets. However, in just six months, Qualcomm’s shares have reached an all-time high as the company has shifted its focus towards AI technology. The market has recognized Qualcomm’s potential in the AI market, particularly in the area of AI inferencing on devices like smartphones and PCs.

The launch of Qualcomm’s new Snapdragon X series of chips, designed for AI inferencing, has also contributed to the company’s newfound success. Partnering with key players like Microsoft, Qualcomm is making strides in AI processing on consumer devices. This shift towards AI technology comes as the business media and Wall St. are realizing the broad scope of AI requirements beyond just large language models and chatbots.

The thirst for computing power for AI is expanding to encompass billions of connected devices in the Internet of Things (IoT) ecosystem. This trend indicates a shift in the AI infrastructure discussion from cloud-based models like LLMs and chatbots to more vertically focused AI applications. These applications extend beyond consumer information to industries like data analytics, robotics, healthcare, and finance, requiring more specific AI technologies.

The AI market is expected to extend far beyond consumer information and chatbots, with diverse applications across various industries. As AI deployments move into verticals, private AI, edge, and distributed cloud, the need for new infrastructure and innovative thinking is becoming increasingly apparent. The potential for AI in vertical and domain-specific models, as well as AI inferencing across different hardware platforms, is vast.

As AI continues to drive private AI models and hybrid infrastructure, the market for AI edge infrastructure is expected to be significant. Technologists suggest that the AI market could shift from a focus on modeling to a focus on inferencing, with CIOs emphasizing the importance of private AI models in specific industries like healthcare and finance. This shift towards private, hybrid, and multicloud architectures is expected to meet the diverse needs for data, analytics, and connectivity.

Business leaders like George Maddalino of MasterCard and Nizar Trigui of GXO Logistics emphasize the importance of a hybrid cloud model and seamless connectivity for AI applications. The rise of AI everywhere signals a new era of processing and inferencing data across all infrastructures, not just those owned by the major players in hyperscale computing. Qualcomm’s success story serves as a testament to the growing enthusiasm for AI technology in diverse industries and the vast potential for AI applications in the future.

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