Shulou(Shulou.com)11/24 Report--

Qualcomm President and CEO Ammon

Generative AI is innovating and evolving faster than ever before, and this is just the beginning. The ways, scenarios, and reasons people will use this technology will be very wide, even beyond imagination. Preliminary estimates suggest that the generative AI market will reach $1 trillion.

Generative AI promises not only to change the way people search and create content, but also to improve everyday life. With generative AI, smartphones can become true digital assistants, allowing users to communicate naturally and get appropriate answers. PC users can use this technology to read or compose emails, draft documents, and automatically create presentations. While driving, conversational in-car assistants can offer advice on charging the car, buying parking tickets or ordering dinner on the way home. Store AI help desks and smart shopping carts can help consumers craft recipes based on weekly specials, budget amounts and family preferences.

To unlock the full potential of this technology and meet the growing demand, generative AI will require both cloud and billions of connected devices capable of high-performance AI computing at low power consumption, such as smartphones, PCs and cars. This is hybrid AI. Hybrid AI computing architectures distribute processing in the cloud and on the endpoint, optimizing efficiency and improving the overall user experience.

Generative AI processing can run directly on the terminal side, can be sent to the cloud on demand, or a combination of the two-either way, it's seamless for the user.

Users expect an experience similar to traditional search, which is the ability to instantly display search results. To meet these expectations and maintain quality of service, cloud processing alone is too expensive, especially during peak demand periods, making it difficult to scale.

Data centers are energy-intensive and expensive. It has been estimated that a generative AI-based web search query costs 10 times more than traditional search. At more than 10 billion queries per day, the incremental cost could run into billions of dollars per year. Web search is just one of many ways generative AI is transforming multiple industries.

In addition to cost, there are privacy, reliability, and performance challenges associated with performing all inference processing in the cloud. When requests enter the cloud and data leaves the terminal, potential security issues arise. In fact, there have been cases where models have been disabled or temporarily disabled due to regulatory and compliance issues such as the collection and storage of personal data.

Hybrid AI is unstoppable. As people continue to explore new ways to use generative AI, the demand for cloud infrastructure will surge. Hybrid AI processing will be the next transformation of computing, just as we've seen the evolution from mainframe to desktop to today's model of cloud combined with endpoints in our hands.

Taking advantage of the processing power of high-performance, low-power terminals, it will be able to efficiently promote the scale expansion of generative AI. The cloud and endpoint will work together to create the next generation of user experiences with powerful, efficient and highly optimized AI capabilities.

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