Results for: Machine Learning
Accelerate your AI workloads with Windows on Snapdragon
From health care to education and manufacturing, AI use cases grow exponentially. Developers choose popular AI Frameworks like PyTorch and TensorFlow to analyze predictions, train models, leverage...
https://developer.qualcomm.com/blog/accelerate-your-ai-workloads-windows-snapdragonTags:
Generating 3D scenes from 2D images more efficiently – Mobile NeRF rendering using Vulkan on Adreno GPU
Co-written with Aleksandra Krstic, Alex Bourd and Shuaib Arshad.
Suppose you came home from vacation with a few dozen photos from different perspectives of the Eiffel Tower or the Taj Mahal or...
https://developer.qualcomm.com/blog/generating-3d-scenes-2d-images-more-efficiently-mobile-nerf-rendering-using-vulkan-adreno-gpuTags:
Bare-metal, Hardware-Accelerated AI for Windows Apps Using ONNX RT
Today, you can’t help but read the media headlines about AI and the growing sophistication of generative AI models like Stable Diffusion. A great example of a use case for generative AI on Windows is...
https://developer.qualcomm.com/blog/bare-metal-hardware-accelerated-ai-windows-apps-using-onnx-rtTags:
Give your Hybrid AI the edge with Windows on Snapdragon
Today, AI is everywhere, and generative AI is being touted as its killer app. We are seeing large language models (LLMs) like ChatGPT, a generative pre-trained transformer, being applied in new and...
https://developer.qualcomm.com/blog/give-your-hybrid-ai-edge-windows-snapdragonTags:
Updating Deep Learning Models Right on the Mobile Device — Transfer Learning and Fine-Tuning
“It’s a good model,” you say, thinking about the model you’ve trained in the cloud for your machine learning application. “I just wish we could fine-tune it on the user’s device.”
Now you can do...
https://developer.qualcomm.com/blog/updating-deep-learning-models-right-mobile-device-transfer-learning-and-fine-tuningTags:
Accelerate your machine learning networks using TVM and the Adreno OpenCL ML APIs on Adreno GPUs
You like running your machine learning (ML) workloads with the Qualcomm Adreno OpenCL ML SDK on Adreno GPUs. But you also want to use the optimized kernel library for Adreno, with the kind of end-to-...
https://developer.qualcomm.com/blog/accelerate-your-machine-learning-networks-using-tvm-and-adreno-opencl-ml-apis-adreno-gpusTags:
Smart Sensors II – How Adding AI Can Predict the Future for IIoT
In many industrial settings, determining the current health of assets still involves a technician putting their ear to a machine to detect any ominous sound deviations. What they hear may indicate...
https://developer.qualcomm.com/blog/smart-sensors-ii-how-adding-ai-can-predict-future-iiotTags:
Exploring AIMET’s Quantization-aware Training Functionality
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In Exploring AIMET’s Post-Training Quantization Methods, we discussed Cross-layer Equalization (CLE), Bias Correction, and AdaRound in AIMET. Using these methods, the...
https://developer.qualcomm.com/blog/exploring-aimet-s-quantization-aware-training-functionalityTags:
Five IoT Home Projects You Can Build
Whether you’re a professional or hobbyist developer, you likely have some side-projects to help you discover new technology, learn how it works, or build solutions to hopefully make life easier. With...
https://developer.qualcomm.com/blog/five-iot-home-projects-you-can-buildTags:
Exploring AIMET’s Post-Training Quantization Methods
*/ AIMET White Paper
Usually, when you’re presented with three options, such as powerful, efficient, and low cost, you’re also faced with the conundrum where you’re only allowed to pick one...
https://developer.qualcomm.com/blog/exploring-aimet-s-post-training-quantization-methods