How generative AI may be integrated into edge devices with constrained resources via pruning, quantization, and knowledge distillation
Do you belong to that group? An worldwide AI craze was ignited in November 2022 when OpenAI debuted ChatGPTFurthermore, even though the majority of generative AI applications now operate on the cloud
Since edge devices have substantial on-device AI processing capabilities, such as smartphones, laptops, and extended reality (XR) headsets, moving some or all of the AI burden to these devices is one of the most promising
They showcased her text-to-image generative AI model, Stable Diffusion, at Mobile World Congress earlier this year using a Snapdragon 8 Gen 2 smartphone
AI recently declared that to want to provide large language models (LLMs) on Snapdragon platforms in 2024, based on Meta’s Llama
Artificial intelligence (AI) models used on edge devices or even in the cloud compromise accuracy for computational efficiency, while neural network models are typically taught in a data center with excellent accuracy
This reduces the bit-precision that the AI model uses for the neural network’s weight and activation values The model size is halved by quantizing from 32 to 8 bits