Results for: TensorFlow
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:
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:
AI for Qualcomm Compute: How to add AI to your Windows on Snapdragon App
Windows on Snapdragon is the next-generation Windows platform. Powered by Qualcomm Technologies’ mobile compute platforms like the Snapdragon 8cx Gen 3, Windows on Snapdragon offers powerful...
https://developer.qualcomm.com/blog/ai-qualcomm-compute-how-add-ai-your-windows-snapdragon-appTags:
From A to Z – Learn the Fundamentals of Qualcomm AI in our new course
You might have seen a few headlines lately about AI, most notably generative AI. While most people tend to think that AI requires powerful, cloud-based servers, today’s edge devices, like...
https://developer.qualcomm.com/blog/learn-fundamentals-of-qualcomm-ai-our-new-courseTags:
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:
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-methodsTags:
Neural Network Optimization with AIMET
To run neural networks efficiently at the edge on mobile, IoT, and other embedded devices, developers strive to optimize their machine learning (ML) models' size and complexity while taking advantage...
https://developer.qualcomm.com/blog/neural-network-optimization-aimetTags:
Training ML Models at the Edge with Federated Learning
Centralized machine learning (ML) is the ML workflow that most of us are familiar with today, where training is allocated to powerful servers which update model parameters using large datasets. The...
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New projects for video capture/playback and AI on QCS610
Start and stop video recording through an Azure IoT hub.
Send the status of your camera recordings to the AWS IoT console.
Use GStreamer plug-ins to record 4K@30fps, 1080p@30fps and 1080p video...
https://developer.qualcomm.com/blog/new-projects-video-captureplayback-and-ai-qcs610