Artificial intelligence is experiencing explosive growth, opening up numerous business opportunities across all major industries. While cloud computing giants have already emerged, the opportunities for newcomers in this field are becoming increasingly limited. In contrast, the future of artificial intelligence is expected to be driven by advancements on the terminal side, attracting both manufacturers and investors to focus their efforts there.
After years of development, with the progress of infrastructure such as ICT, cloud computing has become more robust. Many internet giants have entered the market, but for new entrepreneurs and investors, the "winner-takes-all" effect of dominant players and the high valuations of established companies have made it difficult to enter. As a result, the opportunities in the cloud domain are gradually shrinking.
With the continuous advancement of algorithms, improved terminal-side computing power, and faster network connectivity, more workloads can now be processed directly on the device rather than relying solely on the cloud. According to Gartner, smartphone shipments are expected to reach 8.5 billion units in the next five years. In 2016 alone, global smartphone shipments reached 1.47 billion units. Qualcomm predicts that mobile devices will soon become the most popular AI platform worldwide.
In the future, terminal-side AI is set to experience tremendous growth. The shift from cloud-centric AI to more distributed, edge-based computing is gaining momentum. This trend is being driven by the need for lower latency, better privacy, and more efficient use of network resources. For example, autonomous vehicles require real-time decision-making without relying on constant cloud connectivity, making on-device processing essential.
Manufacturers and investors are increasingly focusing on the terminal side due to its advantages. These include reduced dependency on the cloud, enhanced data privacy, and faster response times. As mobile processors advance—such as reaching 10nm process nodes—computing power on devices continues to improve while power consumption decreases.
The scale effect of smartphones is also playing a crucial role. With over 8.5 billion units expected to be shipped in the next five years, smartphones are becoming the ideal platform for AI deployment. Companies like Qualcomm are investing heavily in terminal-side AI, introducing dedicated hardware such as neural processing units (NPUs) and developing software frameworks to support AI workloads on mobile devices.
Qualcomm, a leader in mobile technology, has been actively involved in AI research for over a decade. It has developed tools like the Snapdragon Neural Processing Engine (SNPE), which supports deep learning frameworks and enables developers to optimize AI applications for mobile and edge devices. Recently, Qualcomm acquired Scyfer BV, a company specializing in machine learning, to further strengthen its capabilities in this area.
Investors are also showing growing interest in terminal-side AI. Startups like Cambrian Technology and Shenjian Technology have raised significant funding, signaling the rising importance of AI chips and on-device processing. Meanwhile, companies like Huawei, Intel, and Apple are integrating AI-specific hardware into their products, demonstrating the industry's shift toward decentralized AI solutions.
As 5G networks expand, the synergy between cloud and terminal AI will continue to evolve. 5G's low latency and high bandwidth will enable seamless communication between devices and the cloud, enhancing the overall performance of AI systems. However, the focus on terminal-side AI is clear: it offers greater flexibility, security, and efficiency in an increasingly connected world.
In conclusion, while the cloud remains important, the future of AI lies in the convergence of powerful terminals and intelligent infrastructure. Companies that adapt to this shift will be well-positioned to lead the next wave of innovation.
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