Qualcomm is a leading AI technology company that has been improving its AI skills for more than ten years. In both hardware and software, Qualcomm has a big advantage over its mobile competitors. The Snapdragon 8 Gen 3, the Cloud AI100 Ultra for data center AI, and the Snapdragon X Elite are all part of the company’s large SoC family. Qualcomm AI was first shown off at a luncheon in San Francisco in 2017. It does great AI work while using very little power. The company’s CloudAI 100, which came out in 2020 and had 400 TOPS at 75 watts, was the best inference processor at the edge on the market. Based on its AI capabilities, Qualcomm is a major market player.
AI on Edge Devices: Challenges and Solutions
Ziad Asghar, Sr. VP of Product Management at Qualcomm, says that AI inference will be done on edge devices more and more because they have enough processing power and memory. This could eventually allow AI apps like Microsoft Co-Pilot, which can only be used in the Azure cloud right now, to run on devices. But getting big language models to work on a phone or car SoC is hard. You have to reduce the size of the model, prune the network for better performance, use compression, and add new methods like speculative decoding. Qualcomm is looking into these areas and putting them to use on Snapdragon and Cloud AI100. It is also being looked into how MX6 compression could be used to make networks even smaller.
Qualcomm: A Strong Player in Early Edge AI
Qualcomm’s Snapdragon processors have built-in AI engines like the Hexagon DSP that make AI tasks run faster on the device itself without having to send data to the cloud. This puts Qualcomm in a good position in the early days of AI. These processors also have great performance and good power management, which is important for edge AI applications. A lot of smartphones and other devices use Qualcomm’s Snapdragon processors. This has created a strong community of developers and apps that work best with Qualcomm’s hardware. Qualcomm also offers a wide range of software tools for AI development, such as the AI Engine and developer-specific SDKs, which make it easier to add AI features to services and applications.
Snapdragon Workforce
Powerful AI chips like the Snapdragon X Elite have been praised for how well they handle single-threaded, multi-threaded, and AI workloads. Its Hexagon NPU has 45 TOPS (tera operations per second) performance, which is faster than Intel and AMD’s AI inference processors. Benchmarks like Geekbench and Cinebench show that the X Elite’s CPU performance is on par with that of the Intel Core i7 and the AMD Ryzen chips. It was found to be 21% faster than the Apple M3. Partners such as Amazon AWS, HP Enterprise, Dell, and Lenovo have come on board with Cloud AI 100 because of its performance and low power use. These companies want to lower costs and power use in inference processing. Cerebras, the company that created the Wafer Scale Engine 3, has also teamed up with Qualcomm to use this platform to get a 10X cost advantage. The X Elite has a new core that was designed by Nuvia and was bought in 2021. This core will likely be used in future mobile and data center devices. The X Elite, on the other hand, has a big problem with Windows apps.
Streamlining On-Device AI Development
The Qualcomm AI Hub is a place where developers can find information about working on devices with Qualcomm’s Snapdragon and other platforms. It comes with more than 75 AI models that are already optimized to do things like speech processing, object detection, and image recognition. The hub is focused on on-device AI, which means that processing happens right on the device. This has benefits like faster response times, better privacy, and less reliance on internet connectivity. The AI models have been tweaked to work best with Qualcomm processors. This makes sure that the devices run smoothly and make good use of their resources. These models can be found on Qualcomm’s AI Hub, Hugging Face, and GitHub, among other places, due to the hub. The goal is to make it easier and faster to make AI-powered apps for Qualcomm Snapdragon and other platforms by giving developers pre-optimized models and resources that are made for AI that runs on the device.
Conclusion
Qualcomm is focusing on AI as the main thing that will set it apart in the future, and its own research group and SoC teams are doing a great job. Edge AI hardware and software will be made by this company, since AMD, Intel, and Apple are not in the mobile space. With Microsoft’s help, Qualcomm needs to come up with and implement a winning ecosystem strategy for Windows on X Elite. Nvidia is the leader in AI for the data center, but Qualcomm is the leader where AI is being used: at the edge. The value of AI on the Edge can already be seen in some cool phones that are out there.
