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With the impending rise of AI PCs, Qualcomm wants to help developers get ahead of the game. The company is releasing an update for its AI hub which supports the Snapdragon X processor series. App builders can now respond to this The latest chips from Qualcomm that power on-device AI and optimize their programs to run efficiently on next-generation Windows computers and laptops.
Additionally, the Qualcomm AI Hub is opening up to more models. When it debuted in February, it had 75 pre-trained models. Today there are more than a hundred. In the future, developers will no longer be limited to what Qualcomm has: they can bring their own products.
Training models to work on PCs
Qualcomm's AI Hub is a good place for developers to start when looking for models from which to build their applications. If you are building for a smart device, robot or drone, you can find a model. The same goes for developing an AI-powered app for mobile devices and, soon enough, computers. Many of the popular models are also available on Hugging Face and GitHub. All can be easily deployed to Qualcomm devices and run on CPUs, GPUs, and NPUs using TensorFlow Lite or Qualcomm's AI Engine Direct.
The support for Snapdragon X is an attempt to stay one step ahead of the competition. Rivals AMD And Intel have announced AI PC processors, so today's announcement is more strategic in nature. Developers can run models on the Snapdragon X Series platforms to build AI-powered Windows applications, thanks to integrations with ONNX runtime, Cuddling face optimal And Bel.cpp. This potentially means developers could see their app used on a wide range of computers from Acer, ASUS, Dell, HP, Lenovo, Samsung and OEM7 – all companies with planned PCs powered by Qualcomm's Snapdragon X Elite or X Plus chips .
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Qualcomm has also tapped Andrew Ng's DeepLearning.ai to provide online courses that educate developers about AI on devices and ways to implement the technology into their programs.
Bring your own AI
Who knows better about your customer's data or space than you? While many developers will take advantage of the 100+ models available on Qualcomm's AI Hub, there may be cases where some apps require specialized models.
Developers can now upload, optimize and compile SLM and LLMs specifically for Qualcomm and Snapdragon platforms. These models can be quickly tested and validated on cloud-hosted devices with just a few lines of code.
Imagine that you are in the research field and want to develop a drug or compound. You may not use any of the popular models to accomplish this task, but you can create one trained on specific scientific data. You can then take that model, upload it to Qualcomm's AI Hub, and deploy it to AI PCs within your organization so fellow researchers can benefit locally instead of working in the cloud.
This example can be the same no matter what industry or profession you are in. Having models optimized for the PC can reduce latency in responses and enable faster iterations.